{"id":16,"date":"2019-08-30T17:26:10","date_gmt":"2019-08-30T09:26:10","guid":{"rendered":"http:\/\/123.56.72.43\/?page_id=16"},"modified":"2026-03-16T15:46:15","modified_gmt":"2026-03-16T07:46:15","slug":"publications","status":"publish","type":"page","link":"https:\/\/www.njumeta.com\/index.php\/publications","title":{"rendered":"Publications"},"content":{"rendered":"<h2 class=\"STYLE2\"><b>Selected Publications\u00a0<\/b><a href=\"\/index.php\/papers\">(complete list&#8230;)<\/a><\/h2>\n<p><!-- CVPR 2026 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1105 size-full lazyload\" data-src=\"\/\/www.njumeta.com\/wp-content\/uploads\/2026\/03\/overview.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong><a href=\"https:\/\/arxiv.org\/abs\/2602.21105\">BrepGaussian: CAD reconstruction from Multi-View Images with Gaussian Splatting<\/a><\/strong><br \/>Jiaxing Yu, Dongyang Ren, Hangyu Xu, Zhouyuxiao Yang, Jie Guo, Zhengkang Zhou, Yanwen Guo, Yuanqi Li*<br \/><em>CVPR 2026<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n<p><!-- ICLR 2026 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1105 size-full lazyload\" data-src=\"\/\/www.njumeta.com\/wp-content\/uploads\/2026\/03\/image.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong><a href=\"https:\/\/hmwang2002.github.io\/release\/internsvg\/\">InternSVG: Towards Unified SVG Tasks with Multimodal Large Language Models<\/a><\/strong><br \/>Haomin Wang, Jinhui Yin, Qi Wei, Wenguang Zeng, Lixin Gu, Shenglong Ye, Zhangwei Gao, Yaohui Wang, Yanting Zhang, Yuanqi Li, Yanwen Guo, Wenhai Wang, Kai Chen, Yu Qiao, Hongjie Zhang<br \/><em>ICLR 2026<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n<p><!-- SIGGRAPH Asia 2025 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1105 size-full lazyload\" data-src=\"\/\/www.njumeta.com\/wp-content\/uploads\/2026\/03\/spectralgs_teaser.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong><a href=\"https:\/\/letianhuang.github.io\/spectralgs\/\">Spectral-GS: Taming 3D Gaussian Splatting with Spectral Entropy<\/a><\/strong><br \/>Letian Huang, Jie Guo, Jialin Dan, Ruoyu Fu, Yuanqi Li, Yanwen Guo<br \/><em>SIGGRAPH Asia 2025<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n<p><!-- SIGGRAPH 2025 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1105 size-full lazyload\" data-src=\"\/\/www.njumeta.com\/wp-content\/uploads\/2026\/03\/transparent_teaser.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong><a href=\"https:\/\/letianhuang.github.io\/transparentgs\/\">TransparentGS: Fast Inverse Rendering of Transparent Objects with Gaussians<\/a><\/strong><br \/>Letian Huang, Dongwei Ye, Jialin Dan, Chengzhi Tao, Huiwen Liu, Kun Zhou, Bo Ren, Yuanqi Li, Yanwen Guo, Jie Guo<br \/><em>ACM Transactions on Graphics (Proceedings of SIGGRAPH 2025)<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n<p><!-- 3DV 2025 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1105 size-full lazyload\" data-src=\"\/\/www.njumeta.com\/wp-content\/uploads\/2026\/03\/360gs.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong><a href=\"https:\/\/github.com\/LeoDarcy\/360GS\">360-GS: Layout-guided Panoramic Gaussian Splatting For Indoor Roaming<\/a><\/strong><br \/>Jiayang Bai, Letian Huang, Jie Guo, Wen Gong, Yuanqi Li, Yanwen Guo<br \/><em>International Conference on 3D Vision (3DV), 2025<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n<p><!-- TVCG 2025 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1105 size-full lazyload\" data-src=\"\/\/www.njumeta.com\/wp-content\/uploads\/2026\/03\/glossygs_teaser.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong><a href=\"https:\/\/letianhuang.github.io\/glossygs\/\">GlossyGS: Inverse Rendering of Glossy Objects with 3D Gaussian Splatting<\/a><\/strong><br \/>Shuichang Lai*, Letian Huang*, Jie Guo, Kai Cheng, Bowen Pan, Xiaoxiao Long, Jiangjing Lyu, Chengfei Lv, Yanwen Guo<br \/><em>IEEE Transactions on Visualization and Computer Graphics (TVCG), 2025<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1105 size-full lazyload\" data-src=\"\/wp-content\/uploads\/2025\/04\/IMG_20250414_150553-scaled.jpg\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Deep Point Cloud Edge Reconstruction Via Surface Patch Segmentation<\/strong><br \/>Yuanqi Li, Hongshen Wang, Yansong Liu, Jingcheng Huang, Shun Liu, Chenyu Huang, Jianwei Guo, Jie Guo, Yanwen Guo<br \/><em>TVCG 2025<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n<p><!-- CVPR 2025 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1105 size-full lazyload\" data-src=\"\/wp-content\/uploads\/2025\/04\/\u5fae\u4fe1\u56fe\u7247_20250417205144.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>High-quality Point Cloud Oriented Normal Estimation via Hybrid Angular and Euclidean Distance Encoding<\/strong><br \/>Yuanqi Li, Jingcheng Huang, Hongshen Wang, Peiyuan Lv, Yansong Liu, Jiuming Zheng, Jie Guo, Yanwen Guo<br \/><em>CVPR 2025<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1105 size-full lazyload\" data-src=\"\/wp-content\/uploads\/2025\/04\/teaser0_clear.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>SGCR: Spherical Gaussians for Efficient 3D Curve Reconstruction<\/strong><br \/>Xinran Yang, Donghao Ji, Yuanqi Li, Jie Guo, Yanwen Guo, Junyuan Xie<br \/><em>CVPR 2025<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1105 size-full lazyload\" data-src=\"\/wp-content\/uploads\/2025\/04\/picture0_6.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>EdgeMovingNet: Edge-preserving Point Cloud Reconstruction via Joint Geometry Features<\/strong><br \/>Xinran Yang, Donghao Ji, Yuanqi Li, Junyuan Xie, Jie Guo, Yanwen Guo<br \/><em>CVPR 2025<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1104 size-full lazyload\" data-src=\"\/wp-content\/uploads\/2025\/04\/cvpr2025_intro_image_compressed.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong><a href=\"https:\/\/github.com\/murcherful\/GauPCRender?tab=readme-ov-file\" target=\"_blank\" rel=\"noopener\">Sparse Point Cloud Patches Rendering via Splitting 2D Gaussians<\/a><\/strong><br \/>Changfeng Ma, Ran Bi, Jie Guo, Chongjun Wang, Yanwen Guo<br \/><em>CVPR 2025<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n<p><!-- AAAI 2025 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1105 size-full lazyload\" data-src=\"\/wp-content\/uploads\/2024\/12\/aaai.jpg\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong><a href=\"https:\/\/saltfishmx.github.io\/RAKD_website\/\">Real-time Neural Denoising with Render-aware Knowledge Distillation<\/a><\/strong><br \/>Mengxun Kong, Jie Guo, Chen Wang, Ye Yuan, and Yanwen Guo<br \/><em>AAAI 2025<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n\n<p><!-- ECCV 2024 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignnone wp-image-1105 size-full lazyload\" data-src=\"\/\/www.njumeta.com\/wp-content\/uploads\/2026\/03\/thumbnail.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong><a href=\"https:\/\/letianhuang.github.io\/op43dgs\/\">On the Error Analysis of 3D Gaussian Splatting and an Optimal Projection Strategy<\/a><\/strong><br \/>Letian Huang, Jiayang Bai, Jie Guo, Yuanqi Li, Yanwen Guo<br \/><em>ECCV 2024<\/em><\/div>\n<div style=\"clear: both;\">\u00a0<\/div>\n<\/div>\n<p><!-- SIGGRAPH 2024 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2024\/12\/\u5fae\u4fe1\u56fe\u7247_20241223172636.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong><a href=\"https:\/\/iamxym.github.io\/DFASRR.github.io\/\" target=\"_blank\" rel=\"noopener\">Deep Fourier-based Arbitrary-scale Super-resolution for Real-time Rendering<\/a><\/strong><br \/>Haonan Zhang, Jie Guo, Jiawei Zhang, Haoyu Qin, Zesen Feng, Ming Yang, and Yanwen Guo<br \/><em>SIGGRAPH 2024<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2024\/05\/Snipaste_2024-05-30_17-12-10.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Specular Polynomials<\/strong><br \/>Zhimin Fan, Jie Guo,Yiming Wang, Tianyu Xiao,Hao Zhang,Changqing Zou,Zhenyu Chen,Pengpei Hong,Yanwen Guo and Lingqi Yan<br \/><em>SIGGRAPH 2024<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2024\/05\/Snipaste_2024-05-30_17-29-12.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Practical Measurements of Translucent Materials with Inter-Pixel Translucency Prior<\/strong><br \/>Zhenyu Chen, Jie Guo, Shuichang Lai, Ruoyu Fu, Mengxun Kong, Chen Wang,Hongyu Sun, Zhebin Zhang, Chen Li, Yanwen Guo1<br \/><em>CVPR 2024<\/em><\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2024\/05\/Snipaste_2024-05-30_16-47-55.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong> Prompt3D: Random Prompt AssistedWeakly-Supervised 3D Object Detection<\/strong><br \/>Xiaohong Zhang, Huisheng Ye, Jingwen Li, Qinyu Tang, Yuanqi Li, Yanwen Guo and Jie Guo<br \/><em>CVPR 2024<\/em><\/div>\n<div style=\"clear: both; margin-bottom: 20px; margin-top: 10px; height: 150px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2024\/05\/Snipaste_2024-05-30_16-39-05.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong> LiDAR-Net: A Real-scanned 3D Point Cloud Dataset for Indoor Scenes<\/strong><br \/>Yanwen Guo, Yuanqi Li, Dayong Ren, Xiaohong Zhang, Jiawei Li, Liang Pu, Changfeng Ma, Xiaoyu Zhan, Jie Guo, Mingqiang Wei, Yan Zhang, Piaopiao Yu, Shuangyu Yang, Donghao Ji, Huisheng Ye, Hao Sun, Yansong Liu, Yinuo Chen, Jiaqi Zhu, Hongyu Liu<br \/><em>CVPR 2024<\/em><\/div>\n<\/div>\n<div style=\"clear: both; margin-bottom: 20px; margin-top: 10px; height: 150px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2024\/05\/Snipaste_2024-05-30_16-07-52.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong> Semantic Human Mesh Reconstruction with Textures<\/strong><br \/>Xiaoyu Zhan, Jianxin Yang, Yuanqi Li, Jie Guo, Yanwen Guo, Wenping Wang<br \/><em>CVPR 2024(oral)<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2024\/05\/Snipaste_2024-05-30_17-06-56.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Manifold Path Guiding for Importance Sampling Specular Chains<\/strong><br \/>Zhimin Fan,Pengpei Hong, Jie Guo, Changqing Zou, Yanwen Guo and Lingqi Yan<br \/><em>SIGGRAPH Asia 2023<\/em><\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2023\/05\/\u5fae\u4fe1\u56fe\u7247_20230507183724.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong> Surface and Edge Detection for Primitive Fitting of Point Clouds<\/strong><br \/>Yuanqi Li, Shun Liu, Xinran Yang, Jianwei Guo, Jie Guo, Yanwen Guo<br \/><em>ACM SIGGRAPH 2023<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2023\/05\/Snipaste_2023-05-15_11-10-33.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong> AGConv: Adaptive Graph Convolution on 3D Point Clouds<\/strong><br \/>Mingqiang Wei, Zeyong Wei, Haoran Zhou, Fei Hu, Huajian Si, Zhilei Chen, Zhe Zhu, Jingbo Qiu, Xuefeng Yan, Yanwen Guo, Jun Wang, Jing Qin<br \/><em>IEEE T-PAMI 2023 <\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2023\/05\/Snipaste_2023-05-07_11-45-48.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong> Ultra-High Resolution SVBRDF Recovery from a Single Image<\/strong><br \/>Jie Guo, Shuichang Lai, Qinghao Tu,Chengzhi Tao, Changqing Zou, Yanwen Guo<br \/><em>ACM Transactions on Graphics 2023<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2023\/05\/Snipaste_2023-05-07_11-39-06.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong> Symmetric Shape-Preserving Autoencoder for Unsupervised Real Scene Point Cloud Completion<\/strong><br \/>Chanfeng Ma, Yinuo Chen, Pengxiao Guo, Jie Guo, Chongjun Wang, Yanwen Guo<br \/><em>CVPR 2023<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2023\/04\/Snipaste_2023-04-16_12-13-40.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Reflectance edge guided networks for detail-preserving intrinsic image decomposition<\/strong><br \/>Quewei Li, Jie Guo, Zhengyi Wu, Yang Fei, Yanwen Guo<br \/><em>Sci. China Inf. Sci. 66(2) 2023<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2023\/04\/Snipaste_2023-04-16_12-53-44.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>ShadowMover: Automatically Projecting Real Shadows onto Virtual Object<\/strong><br \/>Piaopiao Yu, Jie Guo, Fan Huang, Zhenyu Chen, Chen Wang, Yan Zhang, Yanwen Guo<br \/><em>IEEE Trans. Vis. Comput. Graph. 29(5): 2379-2389 2023 <\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2023\/04\/Snipaste_2023-04-16_12-59-28.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Point attention network for point cloud semantic segmentation <\/strong><br \/>Dayong Ren, Zhengyi Wu, Jiawei Li, Piaopiao Yu, Jie Guo, Mingqiang Wei, Yanwen Guo<br \/><em>Sci. China Inf. Sci. 65(9): 1-14 2022 <\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2023\/04\/Snipaste_2023-04-16_13-05-29.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Affinity Fusion Graph-Based Framework for Natural Image Segmentation <\/strong><br \/>Yang Zhang, Moyun Liu, Jingwu He, Fei Pan, Yanwen Guo<br \/><em>IEEE Trans. Multim. 24: 440-450 2022 <\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2023\/04\/Snipaste_2023-04-16_13-21-05.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Video Vectorization via Bipartite Diffusion Curves Propagation and Optimization <\/strong><br \/>Yuanqi Li, Chuan Wang, Jing Hong, Jie Zhu, Jie Guo, Jue Wang, Yanwen Guo, Wenping Wang<br \/><em>IEEE Trans. Vis. Comput. Graph. 28(9): 3265-3276 2022 <\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2023\/04\/\u5fae\u4fe1\u56fe\u7247_20230416132346.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Efficient Light Probes for Real-Time Global Illumination<\/strong><br \/>Jie Guo, Zijing Zong, Yadong Song, Xihao Fu, Chengzhi Tao, Yanwen Guo, Ling-Qi Yan<br \/><em>ACM Trans. Graph. 41(6): 202:1-202:14 2022<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2023\/04\/Snipaste_2023-04-16_13-27-20.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>NeuLighting: Neural Lighting for Free Viewpoint Outdoor Scene Relighting with Unconstrained Photo Collections <\/strong><br \/>Quewei Li, Jie Guo, Yang Fei, Feichao Li, Yanwen Guo<br \/><em>SIGGRAPH Asia 2022: 13:1-13:9<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2023\/04\/Snipaste_2023-04-16_13-32-39.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Unsupervised Point Cloud Completion and Segmentation by Generative Adversarial Autoencoding Network<\/strong><br \/>Changfeng Ma, Yang Yang, Jie Guo, Fei Pan, Chongjun Wang, Yanwen Guo<br \/><em>NeurIPS 2022<\/em><\/div>\n<\/div>\n<div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2021\/03\/PAMI-300x199.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Learning Graph Convolutional Networks for Multi-Label Recognition and Applications<\/strong><br \/>Zhao-Min Chen, Xiu-Shen Wei*, Peng Wang, and Yanwen Guo*<br \/><em>IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2021<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2021\/07\/czm.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Hierarchical Context Embedding for Region-based Object Detection<\/strong><br \/>Zhao-Min Chen, Xin Jin, Bo-Rui Zhao, Yanwen Guo*<br \/><em>IEEE Transactions on Image Processing (TIP), 2021 To appear.<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2021\/08\/2021-08-23-172353.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Semi-supervised Pixel-level Scene Text Segmentation by Mutually Guided Network<\/strong><br \/>Chuan Wang*, Shan Zhao*, Shuaicheng Liu, Li Zhu, Kunming Luo, Yanwen Guo, and Jue Wang<br \/><em>IEEE Transactions on Image Processing (TIP), 2021 To appear.<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2021\/07\/WechatIMG121.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Hierarchical Disentangled Representation Learning for Outdoor Illumination Estimation and Editing<\/strong><br \/>Piaopiao Yu, Jie Guo*, Fan Huang, Cheng Zhou, Hongewi Che, Xiao Ling, and Yanwen Guo*<br \/><em>ICCV 2021, To appear.<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2021\/08\/a1aa83894d6df1070eeaf6be5d4d474.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Dual attention autoencoder for all-weather outdoor lighting estimation<\/strong><br \/>Piaopiao Yu, Jie Guo*, Longhai Wu, Cheng Zhou, Mengtian Li, Chenchen Wang, and Yanwen Guo*<br \/><em>Sci China Inf Sci, To appear.<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/af0c5f989b8d69c50ba4df3e8215c69.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong> Highlight-Aware Two-Stream Network for Single-Image SVBRDF Acquisition<\/strong><br \/>Jie Guo, Shuichang Lai, Chengzhi Tao, Yuelong Cai, Lei Wang, Yanwen Guo*, Ling-qi Yan<br \/><em>ACM Transactions on Graphics (Proceedings of SIGGRAPH 2021)<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/rep.jpg\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Volumetric Appearance Stylization with Stylizing Kernel Prediction Network<\/strong><br \/>Jie Guo*, Mengtian Li*, Zijing Zong, Yuntao Liu, Jingwu He, Yanwen Guo\u2020, and Ling-qi Yan<br \/><em>ACM Transactions on Graphics (SIGGRAPH), 2021<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2021\/03\/fmCVPR-300x185.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>GLAVNet: Global-Local Audio-Visual Cues for Fine-Grained Material Recognition<\/strong><br \/>Fengmin Shi, Jie Guo*, Haonan Zhang, Shan Yang, Xiying Wang, and Yanwen Guo*<br \/><em>IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2021\/03\/videovectorization-300x186.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Video Vectorization via Bipartite Diffusion Curves Propagation and Optimization<\/strong><br \/>Yuanqi Li, Chuan Wang, Jing Hong, Jie Zhu, Jie Guo*, Jue Wang, Yanwen Guo*, and Wenping Wang<br \/><em>IEEE Transactions on Visalization &amp; Computer Graphics (TVCG), 2021<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2021\/03\/TMM-300x176.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Disentangling, Embedding and Ranking Label Cues for Multi-Label Image Recognition<\/strong><br \/>Zhao-Min Chen, Quan Cui, Xiu-Shen Wei, Xin Jin, and Yanwen Guo*<br \/><em>IEEE Transactions on Multimedia (TMM), 2021<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2021\/03\/AffinityFusion.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Affinity fusion graph-based framework for natural image segmentation<\/strong><br \/>Yang Zhang, Moyun Liu, Jingwu He, Fei Pan, and Yanwen Guo*<br \/><em>IEEE Transactions on Multimedia (TMM), 2021<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2021\/03\/TII-feright-detection-300x181.png\" alt=\"\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>A Unified Light Framework for Real-time Fault Detection of Freight Train Images<\/strong><br \/>Yang Zhang, Moyun Liu, Yang Yang, and Yanwen Guo*<br \/><em>IEEE Transactions on Industrial Informatics (TII), 2021<\/em><\/div>\n<\/div>\n<p><!-- 2020-2021 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2020\/07\/HM.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Hybrid Models for Open Set Recognition<\/strong><br \/>Hongjie Zhang, Ang Li, Jie Guo, and Yanwen Guo<br \/><em>European Conference on Computer Vision (ECCV), 2020,<\/em><a href=\"https:\/\/arxiv.org\/pdf\/2003.12506.pdf\">[Pdf]<\/a><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2020\/07\/HCE.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Hierarchical Context Embedding for Region-based Object Detection<\/strong><br \/>Zhao-Min Chen, Xin Jin, Borui Zhao, Xiu-Shen Wei, Yanwen Guo<br \/><em>European Conference on Computer Vision (ECCV), 2020<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2020\/07\/DSNE.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Deep Surface Normal Estimation on the 2-Sphere with Confidence Guided Semantic Attention<\/strong><br \/>Quewei Li, Jie Guo, Yang Fei, Qinyu Tang, Wenxiu Sun, Jin Zeng, Yanwen Guo<br \/><em>European Conference on Computer Vision (ECCV), 2020<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-175 alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/DISM-e1567775958751-300x220.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Data-driven Indoor Scene Modeling from a Single Color Image with Iterative Object Segmentation and Model Retrieval<\/strong><br \/>Mingming Liu,\u00a0Kexin Zhang,\u00a0Jie Zhu,\u00a0Jun Wang,\u00a0Jie Guo,\u00a0Yanwen Guo<br \/><em>IEEE Transactions on Visualization and Computer Graphics (TVCG), 2020,<\/em>\u00a0<a href=\"https:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?tp=&amp;arnumber=8531721\">[Pdf]<\/a>\u00a0<a href=\"\/wp-content\/uploads\/publications\/bibtex_dism.txt\">[BibTex]<\/a><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-390 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0b\u53481.12.38-e1568697415293-300x189.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>BRDF Analysis with Directional Statistics and Its Applications<\/strong><br \/>Jie Guo, Yanwen Guo, Jingui Pan, Wenzhou Lu<br \/><em>IEEE Transactions on Visualization and Computer Graphics (TVCG), 2020<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-390 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/Figure1b-1-e1574732398912.jpg\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Real-time Vision Based System of Fault Detection for Freight Trains.<\/strong><br \/>Yang Zhang, Moyun Liu, Yunian Chen, Hongjie Zhang, Yanwen Guo*<br \/><em>IEEE Transactions on Instrumentation and Measurement (TIM), 2020<\/em><\/div>\n<\/div>\n<p><!-- 2020 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-148 lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/GradNet-300x199.jpeg\" width=\"180\" height=\"120\" data-srcset=\"https:\/\/www.njumeta.com\/wp-content\/uploads\/2019\/08\/GradNet-300x199.jpeg 300w, https:\/\/www.njumeta.com\/wp-content\/uploads\/2019\/08\/GradNet-768x510.jpeg 768w, https:\/\/www.njumeta.com\/wp-content\/uploads\/2019\/08\/GradNet-1024x681.jpeg 1024w, https:\/\/www.njumeta.com\/wp-content\/uploads\/2019\/08\/GradNet.jpeg 1777w\" data-sizes=\"(max-width: 180px) 100vw, 180px\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>GradNet: Unsupervised Deep Screened Poisson Reconstruction for Gradient-Domain Rendering<\/strong><br \/>Jie Guo, Mengtian Li, Quewei Li, Yuting Qiang, Bingyang Hu, Yanwen Guo, Ling-Qi Yan<br \/><em>ACM Transactions on Graphics (SIGGRAPH ASIA), 2019,<\/em><a href=\"\/wp-content\/uploads\/publications\/paper_gradnet.pdf\">[Pdf]<\/a>\u00a0<a href=\"\/wp-content\/uploads\/publications\/supplementary_gradnet.zip\">[Supplementary]<\/a><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-145 alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/fgf-300x200.jpeg\" width=\"180\" height=\"120\" data-srcset=\"https:\/\/www.njumeta.com\/wp-content\/uploads\/2019\/08\/fgf-300x200.jpeg 300w, https:\/\/www.njumeta.com\/wp-content\/uploads\/2019\/08\/fgf-768x512.jpeg 768w, https:\/\/www.njumeta.com\/wp-content\/uploads\/2019\/08\/fgf-1024x683.jpeg 1024w, https:\/\/www.njumeta.com\/wp-content\/uploads\/2019\/08\/fgf.jpeg 1536w\" data-sizes=\"(max-width: 180px) 100vw, 180px\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Fractional Gaussian Fields for Modeling and Rendering of Spatially-Correlated Media<\/strong><br \/>Jie Guo, Yanjun Chen, Bingyang Hu, Ling-Qi Yan, Yanwen Guo, Yuntao Liu<br \/><em>ACM Transactions on Graphics (SIGGRAPH), 2019,<\/em><a href=\"\/wp-content\/uploads\/publiations\/paper_fgf.pdf\">[Pdf]<\/a>\u00a0<a href=\"\/wp-content\/uploads\/publications\/bibtex_fgf.txt\">[BibTex]<\/a>\u00a0<a href=\"https:\/\/sites.cs.ucsb.edu\/~lingqi\/publications\/video_fgf.mp4\">[Video]<\/a>\u00a0<a href=\"\/wp-content\/uploads\/publications\/supplementary_gfg.zip\">[Supplementary]<\/a><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-207 lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/GCN2-300x191.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Multi-Label Image Recognition with Graph Convolutional Networks<\/strong><br \/>Zhao-Min Chen, Xiu-Shen Wei, Peng Wang, Yanwen Guo<br \/><em>IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019<\/em>\u00a0<a href=\"http:\/\/openaccess.thecvf.com\/content_CVPR_2019\/papers\/Chen_Multi-Label_Image_Recognition_With_Graph_Convolutional_Networks_CVPR_2019_paper.pdf\">[Pdf]<\/a>\u00a0<a href=\"\/wp-content\/uploads\/publications\/bibtex_gcn.txt\">[BibTex]<\/a><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-366 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.53.18-300x139.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Learning Actor Relation Graphs for Group Activity Recognition<\/strong><br \/>Jianchao Wu, Liming Wang, Li Wang, Jie Guo, Gangshan Wu<br \/><em>IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019<\/em><\/div>\n<\/div>\n<p><!-- 2018 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-176 alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/VAVR-300x176.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Viewpoint Assessment and Recommendation for Photographing Architectures<\/strong><br \/>Jingwu He, Linbo Wang, Wenzhe Zhou,\u00a0Hongjie Zhang,\u00a0Xiufen Cui,\u00a0Yanwen Guo<br \/><em>IEEE Transactions on Visualization and Computer Graphics (TVCG), 2018,<\/em>\u00a0<a href=\"https:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?tp=&amp;arnumber=8405559\">[Pdf]<\/a>\u00a0<a href=\"\/wp-content\/uploads\/publications\/bibtex_vavr.txt\">[BibTex]<\/a><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-367 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.53.55-300x184.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>A Data-driven Approach for Furniture and Indoor Scene Colorization<\/strong><br \/>Jie Zhu, Yanwen Guo*, and Han Ma<br \/><em>IEEE Transactions on Visualization and Computer Graphics (TVCG), 2018<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-368 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.54.09-300x152.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Correlation-preserving Photo Collage<\/strong><br \/>Lingjie Liu, Hongjie Zhang, Guanmei Jing, Yanwen Guo*, Zhonggui Chen, and Wenping Wang<br \/><em>IEEE Transactions on Visualization and Computer Graphics (TVCG), 2018<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-210 lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/SIHR-300x191.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Single Image Highlight Removal with a Sparse and Low-Rank Reflection Model<\/strong><br \/>Jie\u00a0Guo,\u00a0Zuojian\u00a0Zhou,\u00a0Limin\u00a0Wang<br \/><em>ECCV, 2018, <\/em><a href=\"http:\/\/mcg.nju.edu.cn\/publication\/2018\/ECCV18_gj_wlm.pdf\">[Pdf]<\/a> <a href=\"\/wp-content\/uploads\/publications\/bibtex_sihr.txt\">[BibTex]<\/a><\/div>\n<\/div>\n<p><!-- 2017 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-369 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.54.27-300x197.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Video Vectorization via Tetrahedral Remeshing<\/strong><br \/>Chuan Wang, Jie Zhu, Yanwen Guo*, Wenping Wang<br \/><em>IEEE Transactions on Image Processing (TIP), 2017<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-370 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.54.52-300x200.png\" width=\"180\" height=\"120\" data-srcset=\"https:\/\/www.njumeta.com\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.54.52-300x200.png 300w, https:\/\/www.njumeta.com\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.54.52.png 572w\" data-sizes=\"(max-width: 180px) 100vw, 180px\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Denoising of Hyperspectral Images Using Nonconvex Low Rank Matrix Approximation<\/strong><br \/>Yongyong Chen, Yanwen Guo*, Yongli Wang, Dong Wang, Chong Peng, and Guoping He<br \/><em>IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2017<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-371 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.55.03-300x160.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Object Detection and Tracking Under Occlusion for Object-level RGB-D Video Segmentation<\/strong><br \/>Qian Xie, Oussama Remil, Yanwen Guo, Meng Wang, Mingqiang Wei, Jun Wang<br \/><em> IEEE Transactions on Multimedia (TMM), 2017<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-372 size-medium lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.55.13-e1568694664809-300x178.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Rendering Thin Transparent Layers with Extended Normal Distribution Functions<\/strong><br \/>Jie Guo, Jinghui Qian, Yanwen Guo, and Jingui Pan<br \/><em>IEEE Transactions on Visualization and Computer Graphics (TVCG), 2017<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-390 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.55.58-1-300x211.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Cosegmentation for Object-Based Building Change Detection from High-Resolution Remotely Sensed Images<\/strong><br \/>Min Yuan, Pengfeng Xiao, Xueliang Zhang, Xuezhi Feng, Yanwen Guo, Shuyuan Zhou, and Jinjin Guo<br \/><em>IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2017<\/em><\/div>\n<\/div>\n<p><!-- 2016 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-391 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.56.49-1-300x170.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Learning to Generate Posters of Scientific Papers<\/strong><br \/>Yuting Qiang, Yanwei Fu, Yanwen Guo, Zhi-hua Zhou, and Leonid Sigal<br \/><em>AAAI, 2016<\/em><\/div>\n<\/div>\n<p><!-- 2015 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-375 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.57.02-300x190.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Common Visual Pattern Discovery via Nonlinear Mean Shift Clustering<\/strong><br \/>Linbo Wang, Dong Tang, Yanwen Guo*, and Minh N. Do<br \/><em>IEEE Transactions on Image Processing (TIP), 2015<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-376 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.57.14-300x197.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Content-Aware Video2Comics with Manga-Style Layout<\/strong><br \/>Guangmei Jing, Yongtao Hu, Yanwen Guo*, Yizhou Yu, Wenping Wang<br \/><em> IEEE Transactions on Multimedia (TMM), 2015<\/em><\/div>\n<\/div>\n<p><!-- 2014 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-392 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.57.22-1-300x184.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Video Object Co-Segmentation via Subspace Clustering and Quadratic Pseudo-Boolean Optimization in an MRF Framework<\/strong><br \/>Chuan Wang, Yanwen Guo, Jie Zhu, Linbo Wang, and Wenping Wang<br \/><em> IEEE Transactions on Multimedia (TMM), 2014<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"alignleft wp-image-378 size-medium lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.57.38-e1568694206401-300x180.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Content-aware Photo Collage Using Circle Packing<\/strong><br \/>Zongqiao Yu, Lin Lu, Yanwen Guo, Rongfei Fan, Mingming Liu, Wenping Wang<br \/><em>IEEE Transactions on Visualization and Computer Graphics (TVCG), 2014<\/em><\/div>\n<\/div>\n<p><!-- 2013 --><\/p>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-393 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.58.00-1-300x192.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Line Segment Sampling with Blue-Noise Properties<\/strong><br \/>Xin Sun, Kun Zhou, Jie Guo, Guofu Xie, Jingui Pan, Wencheng Wang and Baining Guo<br \/><em>ACM Transactions on Graphics (SIGGRAPH), 2013<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-381 size-full alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0b\u534812.36.32.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Multi-view Video Summarization<\/strong><br \/>Yanwei Fu, Yanwen Guo*, Yanshu Zhu, Feng Liu, Chuanming Song and Zhi-Hua Zhou<br \/><em> IEEE Transactions on Multimedia (TMM), 2010<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-394 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/\u5c4f\u5e55\u5feb\u7167-2019-09-17-\u4e0a\u534811.58.16-1-300x196.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Discriminative Nonorthogonal Binary Subspace Tracking<\/strong><br \/>Ang Li, Feng Tang, Yanwen Guo, and Hai Tao<br \/><em>ECCV, 2010<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-394 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/WechatIMG35-e1570885555238.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Image retargeting using mesh parametrization<\/strong><br \/>Yanwen Guo, Feng Liu, Jian Shi, Zhihua Zhou, Michael Gleicher<br \/><em> IEEE Transactions on Multimedia (TMM), 2009<\/em><\/div>\n<\/div>\n<div style=\"float: left; margin-bottom: 20px; margin-top: 10px;\">\n<div style=\"height: 120px; width: 180px; float: left;\"><img decoding=\"async\" class=\"wp-image-394 size-medium alignleft lazyload\" data-src=\"\/wp-content\/uploads\/2019\/08\/WechatIMG33-e1570885497607.png\" width=\"180\" height=\"120\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 180px; --smush-placeholder-aspect-ratio: 180\/120;\" \/><\/div>\n<div style=\"height: 120px; width: 530px; float: left; margin-left: 10px;\"><strong>Mesh-Guided Optimized Retexturing for Image and Video<\/strong><br \/>Yanwen Guo, Hanqiu Sun, Qunsheng Peng, Zhongding Jiang<br \/><em>IEEE Transactions on Visualization and Computer Graphics (TVCG), 2008<\/em><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Selected Publications\u00a0(complete list&#8230;) BrepGaussi &#8230; <a title=\"Publications\" class=\"read-more\" href=\"https:\/\/www.njumeta.com\/index.php\/publications\" aria-label=\"\u9605\u8bfb Publications\">\u9605\u8bfb\u66f4\u591a<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-16","page","type-page","status-publish"],"_links":{"self":[{"href":"https:\/\/www.njumeta.com\/index.php\/wp-json\/wp\/v2\/pages\/16","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.njumeta.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.njumeta.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.njumeta.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.njumeta.com\/index.php\/wp-json\/wp\/v2\/comments?post=16"}],"version-history":[{"count":112,"href":"https:\/\/www.njumeta.com\/index.php\/wp-json\/wp\/v2\/pages\/16\/revisions"}],"predecessor-version":[{"id":1209,"href":"https:\/\/www.njumeta.com\/index.php\/wp-json\/wp\/v2\/pages\/16\/revisions\/1209"}],"wp:attachment":[{"href":"https:\/\/www.njumeta.com\/index.php\/wp-json\/wp\/v2\/media?parent=16"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}