个人主页：https://ha0tang.github.io/
主要研究方向
AIGC、AI4Science
个人简介
唐浩，bwin必赢助理教授，国家级海外高水平人才计划入选者。他曾收到美国麻省理工学院（MIT）和哈佛大学的邀请，但最终选择回国。在此之前，他曾在美国卡耐基梅隆大学（CMU）机器人研究所（Robotics Institute）和瑞士苏黎世联邦理工学院（ETH Zurich）计算机视觉实验室（CVL）担任博士后研究员。他分别于2021年和2016年在意大利特伦托大学和北京大学获得博士和硕士学位。在攻读博士学位期间，他曾在英国牛津大学和阿联酋的IIAI研究院进行学术访问和实习，积累了跨国界的学术经验。
他在国际顶级会议和期刊上发表了100多篇论文，包括CVPR、ECCV、ICCV、NeurIPS、ICLR、ICML、ACM MM、AAAI、IJCAI、TPAMI、IJCV和TIP等。其研究工作获得了多项荣誉，包括ACM MM 2018最佳论文提名奖（提名率仅为4/757）。
Selected Publications
[1] Hao Tang, Ling Shao, Nicu Sebe, Luc Van Gool. Graph Transformer GANs with Graph Masked Modeling for Architectural Layout Generation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
[2] Hao Tang, Guolei Sun, Nicu Sebe, Luc Van Gool. Edge Guided GANs with Multi-Scale Contrastive Learning for Semantic Image Synthesis. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
[3] Hao Tang, Philip HS Torr, Nicu Sebe. Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
[4] Hao Tang, Ling Shao, Philip HS Torr, Nicu Sebe. Local and Global GANs with Semantic-Aware Upsampling for Image Generation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
[5] Hao Tang, Ling Shao, Philip HS Torr, Nicu Sebe. Bipartite Graph Reasoning GANs for Person Pose and Facial Image Synthesis. Springer International Journal of Computer Vision (IJCV), 2022
[6] Hao Tang, Zhenyu Zhang, Humphrey Shi, Bo Li, Ling Shao, Nicu Sebe, Radu Timofte, Luc Van Gool. Graph Transformer GANs for Graph-Constrained House Generation. In CVPR 2023, Vancouver, Canada
[7] Hao Tang, Xiaojuan Qi, Guolei Sun, Dan Xu, Nicu Sebe, Radu Timofte, Luc Van Gool. Edge Guided GANs with Contrastive Learning for Semantic Image Synthesis. In ICLR 2023, Kigali, Rwanda
[8] Hao Tang, Dan Xu, Yan Yan, Philip H.S. Torr, Nicu Sebe. Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation. In CVPR 2020, Seattle, USA
[9] Hao Tang, Dan Xu, Nicu Sebe, Yanzhi Wang, Jason J. Corso, Yan Yan. Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation. In CVPR 2019, Long Beach, USA
[10] Hao Tang, Song Bai, Li Zhang, Philip H.S. Torr, Nicu Sebe. XingGAN for Person Image Generation. In ECCV 2020, Glasgow, UK
[11] Zeyu Zhang, Akide Liu, Ian Reid, Richard Hartley, Bohan Zhuang, Hao Tang. Motion Mamba: Efficient and Long Sequence Motion Generation with Hierarchical and Bidirectional Selective SSM. In ECCV 2024, Milan, Italy
[12] Zichong Meng, Changdi Yang, Jun Liu, Hao Tang, Pu Zhao, Yanzhi Wang. InstructGIE: Towards Generalizable Image Editing. In ECCV 2024, Milan, Italy
[13] Wencan Cheng, Hao Tang, Luc Van Gool, Jong Hwan Ko. HandDiff: 3D Hand Pose Estimation with Diffusion on Image-Point Cloud. In CVPR 2024, Seattle, USA
[14] Gengyu Zhang, Hao Tang, Yan Yan. Versatile Navigation under Partial Observability via Value-guided Diffusion Policy. In CVPR 2024, Seattle, USA
[15] Pan Xie, Qipeng Zhang, Peng Taiying, Hao Tang, Yao Du, Zexian Li. G2P-DDM: Generating Sign Pose Sequence from Gloss Sequence with Discrete Diffusion Model. In AAAI 2024, Vancouver, Canada
[16] Peiyan Dong, Zhenglun Kong, Xin Meng, Pinrui Yu, Yifan Gong, Geng Yuan, Hao Tang, Yanzhi Wang. HotBEV: Hardware-oriented Transformer-based Multi-View 3D Detector for BEV Perception. In NeurIPS 2023, New Orleans, USA
[17] Haoyu Chen, Hao Tang, Radu Timofte, Luc Van Gool, Guoying Zhao. LART: Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer. In NeurIPS 2023, New Orleans, USA
[18] Jianbing Wu, Hong Liu, Yuxin Su, Wei Shi, Hao Tang. Learning Concordant Attention via Target-aware Alignment for Visible-Infrared Person Re-identification. In ICCV 2023, Paris, France
[19] Peiyan Dong, Zhenglun Kong, Xin Meng, Peng Zhang, Hao Tang, Yanzhi Wang, Chih-Hsien Chou. SpeedDETR: Speed-aware Transformers for End-to-end Object Detection. In ICML 2023, Hawaii, USA
[20] Ming Tao, Hao Tang, Fei Wu, Xiaoyuan Jing, Bingkun Bao, Changsheng Xu. DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis. In CVPR 2022, New Orleans, USA
