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I am a tenure-track Assistant Professor of Tsinghua-Berkeley Shenzhen Institute/Shenzhen International Graduate School, Tsinghua University, where I direct the IVG@SZ (Intelligent Vision Group at Shenzhen, the sister group of the IVG at Beijing). Before that, I was a postdoctoral researcher at the Department of Engineering Science of the University of Oxford, working with Prof. Philip H. S. Torr and Prof. Victor Prisacariu. My research interests lie in computer vision. Currently, I am working in the fields of video analytics, vision-language understanding and 3D reconstruction. I received my Ph.D degree with honour at Tsinghua University, advised by Prof. Jie Zhou and Prof. Jiwen Lu, and B.S. degree in Automation from Tsinghua University. I have also spent time at Visual Computing Group of Microsoft Research Asia (MSRA), and Prof. Song-Chun Zhu’s VCLA lab of University of California, Los Angeles (UCLA). I am looking for self-motivated Master/PhD/Postdoc. If you have top grades or coding skill, and are highly creative and interested in joining my group, please do not hesitate to send me your CV and transcripts of grades by Email. Due to the large number of emails I receive, I appoligize that I may not respond to every email individually. |
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(*Equal Contribution, #Corresponding Author) |
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Yongming Rao*, Wenliang Zhao*, Yansong Tang, Jie Zhou, Ser-Nam Lim, Jiwen Lu Conference on Neural Information Processing Systems (NeurIPS), 2022 [arXiv] [Code] [Project Page] [中文解读] HorNet is a family of generic vision backbones that perform explicit high-order spatial interactions based on Recursive Gated Convolution. |
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Wanhua Li*, Xiaoke Huang*, Zheng Zhu, Yansong Tang, Xiu Li, Jiwen Lu, Jie Zhou Conference on Neural Information Processing Systems (NeurIPS), 2022 [arXiv] [Code] [Project Page] [中文解读] We present a language-powered paradigm for ordinal regression. |
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Zhao Yang*, Jiaqi Wang*, Yansong Tang#, Kai Chen, Hengshuang Zhao, Philip H.S. Torr IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 [arxiv] [code] [中文解读] We present an end-to-end hierarchical Transformer-based network for referring segmentation. |
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Kejie Li, Yansong Tang, Victor Adrian Prisacariu, Philip H.S. Torr IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 [arxiv] [code] [中文解读] We present Bi-level Neural Volume Fusion, which leverages recent advances in neural implicit representations and neural rendering for dense 3D reconstruction. In order to incrementally integrate new depth maps into a global neural implicit representation, we propose a novel bi-level fusion strategy that considers both efficiency and reconstruction quality by design. |
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Yongming Rao*, Wenliang Zhao*, Guangyi Chen, Yansong Tang, Zheng Zhu, Guan Huang, Jie Zhou, Jiwen Lu IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 [arXiv] [Code] [Project Page] [中文解读] DenseCLIP is a new framework for dense prediction by implicitly and explicitly leveraging the pre-trained knowledge from CLIP. |
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Yansong Tang, Jiwen Lu, and Jie Zhou IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 [arXiv] [Project Page] [中文解读] COIN is currently the largest and most comprehensive instructional video analysis datasets with rich annotations. |
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Yansong Tang*, Zanlin Ni*, Jiahuan Zhou, Danyang Zhang, Jiwen Lu, Ying Wu, and Jie Zhou IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 Oral Presentation [arxiv] [Code] We propose an uncertainty-aware score distribution learning method and extend it to a multi-path model for action quality assessment. |
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