许华哲 - 清华大学 - 交叉信息研究院

个人简介

I am a Tenure-Track Assistant Professor at Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University. I was a postdoctoral researcher at Stanford Vision and Learning Lab (SVL) advised by Prof. Jiajun Wu. I obtained my Ph.D. in Berkeley AI Research (BAIR) advised by Prof. Trevor Darrell. I obtained my bachelor degree from Tsinghua University.

研究领域

I am interested in Embodied AI: Reinforcement Learning, Robotics, and Computer Vision/Touch. Specifically, my research focuses on modeling the dynamics of the world, leveraging/finding human priors for policy learning, and further enabling algorithms to learn in a sample-efficient manner and generalize to unseen scenarios. I am also interested in solving complex real robot applications with deep learning and reinforcement learning.

近期论文

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Zhengrong Xue*, Han Zhang*, Jingwen Cheng, Zhengmao He, Yuanchen Ju, Changyi Lin, Gu Zhang, Huazhe Xu ArrayBot: Reinforcement Learning for Generalizable Distributed Manipulation through Touch arXiv preprint, 2023. Haochen Shi*, Huazhe Xu*, Samuel Clarke, Yunzhu Li, Jiajun Wu RoboCook: Long-Horizon Elasto-Plastic Object Manipulation with Diverse Tools arXiv preprint, 2023. Zhecheng Yuan*, Sizhe Yang*, Pu Hua, Can Chang, Kaizhe Hu, Xiaolong Wang, Huazhe Xu RL-ViGen: A Reinforcement Learning Benchmark for Visual Generalization arXiv preprint, 2023. Tianying Ji, Yu Luo, Fuchun Sun, Xianyuan Zhan, Jianwei Zhang, Huazhe Xu. Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Critic arXiv preprint, 2023. Ruijie Zheng, Xiyao Wang, Yanchao Sun, Shuang Ma, Jieyu Zhao, Huazhe Xu+, Hal Daumé III+, Furong Huang+ TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning arXiv preprint, 2023. Jialu Gao*, Kaizhe Hu*, Guowei Xu, Huazhe Xu Can Pre-Trained Text-to-Image Models Generate Visual Goals for Reinforcement Learning? arXiv preprint, 2023. Sizhe Yang*, Yanjie Ze*, Huazhe Xu MoVie: Visual Model-Based Policy Adaptation for View Generalization arXiv preprint, 2023. Jinxin Liu*, Li He*, Yachen Kang, Zifeng Zhuang, Donglin Wang, Huazhe Xu CEIL: Generalized Contextual Imitation Learning arXiv preprint, 2023. Nicklas Hansen*, Zhecheng Yuan*, Yanjie Ze*, Tongzhou Mu*, Aravind Rajeswaran+, Hao Su+, Huazhe Xu+, Xiaolong Wang+. On Pre-Training for Visuo-Motor Control: Revisiting a Learning-from-Scratch Baseline International Conference on Machine Learning (ICML), 2023. Zhengrong Xue, Zhecheng Yuan, Jiashun Wang, Xueqian Wang, Yang Gao, Huazhe Xu. USEEK: Unsupervised SE(3)-Equivariant 3D Keypoints for Generalizable Manipulation International Conference on Robot Automation (ICRA), 2023. Changyi Lin, Ziqi Lin, Shaoxiong Wang, Huazhe Xu. DTact: A Vision-Based Tactile Sensor that Measures High-Resolution 3D Geometry Directly from Darkness International Conference on Robot Automation (ICRA), 2023. Ray Chen Zheng*, Kaizhe Hu*, Zhecheng Yuan, Boyuan Chen, Huazhe Xu. Extraneousness-Aware Imitation Learning International Conference on Robot Automation (ICRA), 2023. Yunfei Li*, Chaoyi Pan*, Huazhe Xu, Xiaolong Wang, Yi Wu. Efficient Bimanual Handover and Rearrangement via Symmetry-Aware Actor-Critic Learning International Conference on Robot Automation (ICRA), 2023. Kaizhe Hu*, Ray Zheng*, Yang Gao, Huazhe Xu. Decision Transformer under Random Frame Dropping International Conference on Learning Representation (ICLR), 2023. Pu Hua, Yubei Chen+, Huazhe Xu+. Simple Emergent Action Representations from Multi-Task Policy Training International Conference on Learning Representation (ICLR), 2023. Linfeng Zhao, Huazhe Xu, Lawson L.S. Wong. Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation International Conference on Learning Representation (ICLR), 2023. Ruijie Zheng*, Xiyao Wang*, Huazhe Xu, Furong Huang. Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function International Conference on Learning Representation (ICLR), 2023. Abridged in NeurIPS 2022 DRL workshop (Spotlight). Zhecheng Yuan, Zhengrong Xue, Bo Yuan, Xueqian Wang, Yi Wu, Yang Gao, Huazhe Xu. Pre-Trained Image Encoder for Generalizable Visual Reinforcement Learning Conference on Neural Information Processing Systems (NeurIPS), 2022. (Spotlight) Can Chang, Ni Mu, Jiajun Wu, Ling Pan, Huazhe Xu. E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance Conference on Neural Information Processing Systems (NeurIPS), 2022. (Spotlight) Haoyu Xiong, Haoyuan Fu, Jieyi Zhang, Chen Bao, Qiang Zhang, Yongxi Huang, Wenqiang Xu, Animesh Garg, Huazhe Xu, Cewu Lu RoboTube: Learning Household Manipulation from Human Videos with Simulated Twin Environments RSS Workshop, 2022. Hao Li, Yizhi Zhang, Junzhe Zhu, Shaoxiong Wang, Michelle A Lee, Huazhe Xu, Edward Adelson, Li Fei-Fei, Ruohan Gao, Jiajun Wu. See, Hear, and Feel: Smart Sensory Fusion for Robotic Manipulation International Conference on Robots Learning (CORL), 2022. Yixing Wang*, Sifan Ye*, Jiaman Li, Dennis Lee, Karen Liu, Huazhe Xu+, Jiajun Wu+. Scene Synthesis from Human Motion Siggraph Asia, 2022. Huazhe Xu, Yuping Luo, Shaoxiong Wang, Trevor Darrell, Roberto Calandra. Towards Learning to Play Piano with Dexterous Hands and Touch International Conference on Intelligent Robots and Systems (IROS), 2022. Ling Pan, Longbo Huang, Tengyu Ma, Huazhe Xu. Plan Better amid Conservatism: Offline Multi-agent Reinforcement Learning with Actor Rectification International Conference on Machine Learning (ICML), 2022. Yunfei Li, Tian Gao, Jiaqi Yang, Huazhe Xu, Yi Wu. Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning International Conference on Machine Learning (ICML), 2022. Haochen Shi*, Huazhe Xu*, Zhiao Huang, Yunzhu Li, Jiajun Wu. RoboCraft: Learning to See, Simulate, and Shape Elasto-Plastic Objects with Graph Networks Robotics: Science and Systems (RSS), 2022. Zhecheng Yuan, Guozheng Ma, Yao Mu, Bo Xia, Bo Yuan, Xueqian Wang, Ping Luo, Huazhe Xu. Don't Touch What Matters: Task-Aware Lipschitz Data Augmentation for Visual Reinforcement Learning International Joint Conference on Artificial Intelligence (IJCAI), 2022. Ruihan Yang*, Minghao Zhang*, Nicklas Hansen, Huazhe Xu, Xiaolong Wang. Learning Vision-Guided Quadrupedal Locomotion End-to-End with Cross-Modal Transformers International Conference on Learning Representation (ICLR), 2022. (Spotlight) Jiashun Wang, Huazhe Xu, Medhini Narasimhan, Xiaolong Wang. Multi-Person 3D Motion Prediction with Multi-Range Transformers. Conference on Neural Information Processing Systems (NeurIPS), 2021. Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian. NovelD: A Simple yet Effective Exploration Criterion Conference on Neural Information Processing Systems (NeurIPS), 2021. Minghao Zhang*, Pingcheng Jian*, Yi Wu, Huazhe Xu, Xiaolong Wang. Disentangled Attention as Intrinsic Regularization for Bimanual Multi-Object Manipulation Arxiv Preprints. Huazhe Xu*, Boyuan Chen*, Yang Gao, Trevor Darrell. Zero-shot Policy Learning with Spatial Temporal Reward Decomposition on Contingency-aware Observation International Conference on Robot Automation (ICRA), 2021. Mike Lambeta, Huazhe Xu, Jingwei Xu, Po-Wei Chou, Shaoxiong Wang,Trevor Darrell, and Roberto Calandra PyTouch: A Machine Learning Library for Touch Processing International Conference on Robot Automation (ICRA), 2021. Jiashun Wang, Huazhe Xu, Jingwei Xu, Sifei Liu, Xiaolong Wang. Synthesizing Long-Term 3D Human Motion and Interaction in 3D Scenes. Conference on Computer Vision and Pattern Recognition (CVPR), 2021. Yunfei Li, Huazhe Xu, Yilin Wu, Xiaolong Wang, Yi Wu. Solving Compositional Reinforcement Learning Problems via Task Reduction. International Conference on Learning Representations (ICLR), 2021. Zhenggang Tang, Chao Yu, Boyuan Chen, Huazhe Xu, Xiaolong Wang, Fei Fang, Simon Shaolei Du, Yu Wang, Yi Wu. Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization. International Conference on Learning Representations (ICLR), 2021. Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian. Multi-Agent Collaboration via Reward Attribution Decomposition Arxiv preprints, 2020. Ruihan Yang, Huazhe Xu, Yi Wu, Xiaolong Wang. Multi-Task Reinforcement Learning with Soft Modularization. Conference on Neural Information Processing Systems (NeurIPS), 2020. Jingwei Xu*, Huazhe Xu*, Bingbing Ni, Xiaokang Yang, Xiaolong Wang, Trevor Darrell. Hierarchical Style-based Networks for Motion Synthesis. European Conference on Computer Vision (ECCV), 2020. Jingwei Xu*, Huazhe Xu*, Bingbing Ni, Xiaokang Yang, Trevor Darrell. Video Prediction via Demonstration Guidance International Conference on Machine Learning (ICML), 2020. (oral) Yuping Luo, Huazhe Xu, Tengyu Ma. Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling, International Conference on Learning Representation (ICLR), 2020. Jierui Lin*, Yifei Xing*, Huazhe Xu, Yang Gao. Learning a Perception-Logic Network for Unsupervised Scene Conditioned Driving Behavior, Robotics: Science and Systems IDA workshop (RSS workshop), 2020. Yuping Luo*, Huazhe Xu*, Yuanzhi Li, Yuandong Tian, Tengyu Ma. Algorithmic Framework for Model-based Reinforcement Learning with Theoretical Guarantees, International Conference on Learning Representation (ICLR), 2019. Hang Gao*, Huazhe Xu*, Qi-zhi Cai, Ruth Wang, Fisher Yu, Trevor Darrell. Disentangling Propagationand Generation for Video Prediction, International Conference on Computer Vision (ICCV), 2019. Yang Gao*,Huazhe Xu*, Fisher Yu, Sergey Levine, Trevor Darrell. Reinforcement Learning from Imperfect Demonstrations, Neurips 2018 Deep RL Symposium (Neurips Symposium), 2018. Haoran Tang*, Dennis Lee*, Jeffrey O Zhang, Huazhe Xu, Trevor Darrell, Pieter Abbeel. Modular Architecture for StarCraft II with Deep Reinforcement Learning, he 14th AAAI Conference on Artificial Intelligenceand Interactive Digital Entertainmen (AIIDE), 2018. Huazhe Xu*, Yang Gao*, Fisher Yu, Trevor Darrell. End-to-end Learning of Driving Models from Large-scale Video Datasets, Conference on Computer Vision and Pattern Recognition (CVPR), 2017. (oral) Ronghang Hu, Huazhe Xu, Marcus Rohrbach, Jiashi Feng, Kate Saeko, Trevor Darrell. atural Language Object Retrieval, Conference on Computer Vision and Pattern Recognition (CVPR), 2016. (oral)