I am currently working as Boya Postdoctoral Researcher at Peking University with Prof. Song-Chun Zhu. Before that, I received Ph.D in Computer Science from EECS, Peking University, supervised by Prof. Yizhou Wang, and received B.Sc in Communication Engineering from Beijing Jiaotong University.
My current research interests are robot learning, multi-agent learning, and computer vision, particularly in building embodied agents with physical and social common sense.
- 2023.11: Siyuan and I will organize a workshop on Multi-Agent Systems in Complex Environments at DAI 2023.
- 2023.11: Guest lecture about Utility at PKU Cognitive Reasoning.
- 2023.11: 🎉🎉 One paper about Bimanual Dexterous Manipulation was accepted by IEEE T-PAMI.
- 2023.07: Talk at ACM TURC 2023 Symposiums (SIGAI China) in Wuhan.
- 2023.07: 🎉🎉 One paper was accepted by Machine Learning (Journal).
- 2023.05: Talk at CVG group in ETH Zurich (Online).
- 2023.04: 🎉🎉 One paper was accepted by IEEE RA-L.
- 2023.02: 🎉🎉 One paper was accepted by CVPR’23.
- 2022.01: 🎉🎉 One paper was accepted by ICLR’23.
📝 Selected Publications
* : co-first author, ✉ : corresponding author
GFPose: Learning 3D Human Pose Prior with Gradient Fields
Hai Ci, Mingdong Wu, Wentao Zhu, Xiaoxuan Ma, Hao Dong, Fangwei Zhong✉, Yizhou Wang
Proc. of the IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), 2023
- A versatile framework to model plausible 3D human poses in gradient fields for various applications.
Proactive Multi-Camera Collaboration for 3D Human Pose Estimation
Hai Ci*, Mickel Liu*, Xuehai Pan*, Fangwei Zhong✉, Yizhou Wang
International Conference on Learning Representations (ICLR), 2023
- A novel MARL framework to solve proactive multi-camrea collaborations for 3D HPE in human crowds.
RSPT: Reconstruct Surroundings and Predict Trajectories for Generalizable Active Object Tracking
Fangwei Zhong*, Xiao Bi*, Yudi Zhang, Wei Zhang, Yizhou Wang
Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023 (Oral)
- A framework to form a structure-aware motion representation by Reconstructing Surroundings and Predicting the target Trajectory.
TarGF: Learning Target Gradient Field to Rearrange Objects without Explicit Goal Specification
Mingdong Wu*, Fangwei Zhong*, Yulong Xia, Hao Dong
Advances in Neural Information Processing Systems (NeurIPS), 2022
- A framework based on a target gradient field trained by score-matching to tackle object rearrangement without explicit goal specification.
MATE: Benchmarking Multi-Agent Reinforcement Learning in Distributed Target Coverage Control
Xuehai Pan*, Mickel Liu*, Fangwei Zhong✉, Yaodong Yang✉, Song-Chun Zhu, Yizhou Wang
Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (NeurIPS D&B), 2022
- A gamification of the multi-camera multi-target target coverage problem, and an all-in-one multi-agent reinforcement learning benchmark
ToM2C: Target-oriented Multi-agent Communication and Cooperation with Theory of Mind
Yuanfei Wang*, Fangwei Zhong*, Jing Xu, Yizhou Wang
International Conference on Learning Representations (ICLR), 2022
- A Target-oriented Multi-agent Communication and Cooperation mechanism using Theory of Mind.
Towards Distraction-Robust Active Visual Tracking
Fangwei Zhong, Peng Sun, Wenhan Luo, Tingyun Yan, Yizhou Wang
International Conference on Machine Learning (ICML), 2021
- A mixed cooperative-competitive multi-agent game: a target and multiple distractors form a collaborative team to play against a tracker.
- A bunch of practical methods: a reward function for distractors, a cross-modal teacher-student learning strategy, and a recurrent attention module for the tracker.
AD-VAT+: An Asymmetric Dueling Mechanism for Learning and Understanding Visual Active Tracking
Fangwei Zhong, Peng Sun, Wenhan Luo, Tingyun Yan, Yizhou Wang
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2021
- Employ more advanced environment augmentation technique and two-stage training strategies to improve the performance of the tracker in the case of challenging scenarios such as obstacles.
- Analyze the target’s behaviors as the training proceeds and visualize the latent space of the tracker for a better understanding.
CRAVES: Controlling Robotic Arm with a Vision-based, Economic System
Yiming Zuo*, Weichao Qiu*, Lingxi Xie, Fangwei Zhong, Yizhou Wang, Alan L Yuille
Proc. of the IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), 2019
- A vision system for low-cost arm control: trains a vision model in virtual environment, and applies it to real-world images after domain adaptation (a semi-supervised approach).
- One virtual environment for collection data and reinforcement learning.
- Two real-world datasets for evaluation.
End-to-end Active Object Tracking and Its Real-world Deployment via Reinforcement Learning
Wenhan Luo*, Peng Sun*, Fangwei Zhong*, Wei Liu, Tong Zhang, Yizhou Wang
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2020
- Deploy End-to-end active object tracker trained in virtual environment in real-world robot.
Unrealcv: Virtual worlds for computer vision
Weichao Qiu, Fangwei Zhong, Yi Zhang, Siyuan Qiao, Zihao Xiao, Tae Soo Kim, Yizhou Wang, Alan Yuille
ACM Multimedia Open Source Software Competition, 2017
- An open-sourced project to help computer vision researchers build virtual worlds using Unreal Engine 4 (UE4).
🎖 Selected Honors and Awards
- 2021.09 ACM China SIGAI Doctoral Dissertation Award.
- 2021.06 China National Postdoctoral Program for Innovative Talents.
- 2021.06 Outstanding Graduate in Peking University and Beijing.
- 2021.05 Top 10 Outstanding Research Award in the School of EECS, Peking University.
- 2016.08 The Second Place in DJI RoboMasters Summer Camp Competition (2/10).
- 2016.09 - 2021.07, Peking University, Ph.D in Computer Science.
- 2012.09 - 2016.07, Beijing Jiaotong University, B.S. in Communication Engineering.
💻 Professional Service
- Journal Reviewer: Nature Machine Intelligence, IJRR, IEEE TIP, IEEE TVT, IEEE TIV,IEEE RA-L, ACM TOMM, Sensors, IEEE Access, RAS
- Conference Reviewer: ICML 2020/21/22/23, NeurIPS 2020/21/22/23, ICLR 2020/21/22/23/24, CVPR 2020/21/22/23/24, ICCV 2019/21/23, ECCV 2020/22, ACCV 2020, WACV 2021/22/23//24
- PC Member: AAAI 2020/21/22/23/24