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MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning
Suning Huang*,
Zheyu Zhang*,
Tianhai Liang,
Yihan Xu,
Zhehao Kou,
Chenhao Lu,
Guowei Xu,
Zhengrong Xue,
Huazhe Xu,
arXiv, 2024
project page
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arXiv
A leading model-free visual RL algorithm which achieves state-of-the-art performances in learning efficiency and performance on various tasks. We can even directly train it on the real robot!
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Catch It! Learning to Catch in Flight with Mobile Dexterous Hands
Yuanhang Zhang*,
Tianhai Liang*,
Zhenyang Chen,
Yanjie Ze,
Huazhe Xu,
arXiv, 2024
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arXiv
We build a mobile manipulator with a dexterous hand, and leverage reinforcement learning to train a whole-body control policy for the robot to catch diverse objects randomly thrown by humans.
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Data Completion-guided Unified Graph Learning for Incomplete Multi-View Clustering
Tianhai Liang*,
Qiangqiang Shen*,
Shuqin Wang,
Yongyong Chen,
Guokai Zhang,
Junxin Chen,
ACM Transactions on Knowledge Discovery from Data (TKDD), 2024
paper
We propose one novel IMVC method named Data Completion-guided Unified Graph Learning (DCUGL), which could complete the data of missing views and fuse multiple learned view-specific similarity matrices into one unified graph.
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RiEMann: Near Real-Time SE(3)-Equivariant Robot Manipulation without Point Cloud Segmentation
Chongkai Gao,
Zhengrong Xue,
Shuying Deng,
Tianhai Liang,
Siqi Yang,
Lin Shao,
Huazhe Xu
Conference on Robot Learning (CoRL), 2024
project page
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arXiv
We present RiEMann, an end-to-end near Real-time SE(3)-Equivariant Robot Manipulation imitation learning framework from scene point cloud input. Compared to previous methods that rely on descriptor field matching, RiEMann directly predicts the target poses of objects for manipulation without any object segmentation.
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ClothesNet: An Information-Rich 3D Garment Model Repository with Simulated Clothes Environment
Bingyang Zhou,
Haoyu Zhou*,
Tianhai Liang*,
Qiaojun Yu,
Siheng Zhao,
Yuwei Zeng,
Jun Lv,
Siyuan Luo,
Qiancai Wang,
Xinyuan Yu,
Haonan Chen,
Cewu Lu,
Lin Shao
IEEE International Conference on Computer Vision (ICCV), 2023
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arXiv
We present ClothesNet: a large-scale dataset of 3D clothes objects with information-rich annotations. Our dataset consists of around 4400 models covering 11 categories annotated with clothes features, boundary lines, and key points.
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Tsinghua University, China
2024.07 - Present
Master Student in Computer Science
Advisor: Prof. Huazhe Xu
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Shanghai Qi Zhi Institute, China
2024.06 - Present
Intern
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Harbin Institute of Technology, Shenzhen, China
2020.09 - 2024.06
B.Eng. in Automation with a Minor in Computer Science
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Selected Awards and Honors
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2024: Best Bachelor Thesis Award of HITsz in Automation
2024: Best Bachelor Thesis Award of HITsz in Computer Science
2024: Outstanding Graduates of HITsz
2023: National Scholarship (Top 0.2% nationwide)
2023: First Class Academic Scholarship (top 5% in Harbin Institute of Technology, Shenzhen)
2022: Top Ten Outstanding Studying Stars (10 out of all students in Harbin Institute of Technology)
2022: First Class Academic Scholarship (top 5% in Harbin Institute of Technology, Shenzhen)
2022: TOPBAND Outstanding Scholarship (top 1% in Harbin Institute of Technology, Shenzhen)
2021: National Scholarship (Top 0.2% nationwide)
2021: Outstanding student model
2021: First Class Academic Scholarship (top 5% in Harbin Institute of Technology, Shenzhen)
2022: National First Prize in RoboMaster University Championship (RMUC)
2021: National Second Prize in National Undergraduate Electronics Design Contest (NUEDC)
2021: National Third Prize in National Undergraduate Smart Car Contest
2022: Provincial First Prize in China Undergraduate Mathematical Contest in Modeling (CUMCM)
2022: Provincial Second Prize in National Undergraduate Smart Car Contest
2022: Honorable Mention in Mathematical Contest in Modeling (MCM)
2021: Provincial Third Prize in China Undergraduate Mathematical Contest in Modeling (CUMCM)
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GPA: 3.921/4.0
Achieved A+ in more than 60 Courses.
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Guitar🎸: I love playing fingerstyle guitar. Music always makes me happy.
Hardware⚙️: I am an electronics enthusiast and I enjoy working on hardware projects in my spare time.
Medicine🫀: I like reading professional medical books, which is how I understand that the human body is a great mysterious structure.
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The source code is stolen from Jon Barron. What a concise tempelate!
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