Jingbo Wang/ 王靖博
Researcher at Shanghai AI Lab

Jingbo Wang

I obtained my Ph.D. from The Chinese University of Hong Kong ( MMLAB ), supervised by Prof. Dahua Lin. Before that, I received my Master degree from Peking University in 2019, supervised by Prof. Gang Zeng, and my Bachelor degree from Beijing Institute of Technology in July 2016.

I'm interested in computer vision, deep learning, generative AI, character animation, and embodied AI. Most of my research is about generating realistic character animations as human in the real world. Before this, I also did research on scene understanding with efficient model (A.K.A BiseNet V1/V2) and multi-modality input.

  • Always looking for research interns with strong CV/CG/ML background. Recently, we are working on motion simulation for human/hand-scene interaction, next generation animation system, and 2D/3D character generation.

Selected Publications for Recent Interests ( Full List in Google Scholar)

Jingbo Wang*, Zhengyi Luo*, Ye Yuan, Yixuan Li, Bo Dai ('*' donats equal contribution.)
PACER+: On-Demand Pedestrian Animation Controller in Driving Scenarios
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
[Project] [Paper] [Video]
Yi Shi, Jingbo Wang, Xuekun Jiang, Bo Dai
Controllable Motion Diffusion Model
[Paper] [Project]
Zeqi Xiao, Tai Wang, Jingbo Wang, Jinkun Cao, Wenwei Zhang, Bo Dai, Dahua Lin, Jiangmiao Pang
Unified Human-Scene Interaction via Prompted Chain-of-Contacts
The International Conference on Learning Representations (ICLR), 2024
[Paper] [Project]
Liang Pan, Jingbo Wang, Buzhen Huang, Junyu Zhang, Haofan Wang, Xu Tang, Yangang Wang
Synthesizing Physically Plausible Human Motions in 3D Scenes
International Conference on 3D Vision (3DV), 2024
[Paper] [Project]
Jingbo Wang, Ye Yuan, Zhengyi Luo, Kevin Xie, Dahua Lin, Umar Iqbal, Sanja Fidler, Sameh Khamis
Learning Human Dynamics in Autonomous Driving Scenarios
IEEE International Conference on Computer Vision (ICCV), 2023
[Paper] [Video]
Jingbo Wang, Yu Rong, Jingyuan Liu, Sijie Yan, Dahua Lin, Bo Dai
Towards Diverse and Natural Scene-aware 3d Human Motion Synthesis
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
[Paper] [Video]
Yu Rong, Jingbo Wang, Ziwei Liu, Chen Change Loy
Monocular 3D Reconstruction of Interacting Hands via Collision-Aware Factorized Refinements
International Conference on 3D Vision (3DV), 2021
[Project] [Paper]
Jingbo Wang, Sijie Yan, Bo Dai, and Dahua Lin
Scene-aware Generative Network for Human Motion Synthesis
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
[Project] [Paper] [Supp] [Demo Video]
Jingbo Wang, Sijie Yan, Yuanjun Xiong,and Dahua Lin
Motion Guided 3D Pose Estimation from Videos
European Conference on Computer Vision (ECCV), 2020
[Paper] [Project] [Demo Video]
Changqian Yu*, Jingbo Wang*, Chao Peng, Changxin Gao, Gang Yu and Nong Sang ('*' donates equal contribution.)
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
European Conference on Computer Vision (ECCV), 2018
[BiSeNet] [BiSeNetv2] [Project]


  • [2020.08-2023.08]   Ph.D student at MMLab, IE Department, The Chinese University of Hong Kong.
  • [2016.09-2019.07]   Key Laboratory of Machine Perception (MOE), School of EECS, Peking University.
  • [2012.09-2016.07]   Beijing Institute of Technology, School of Mathematics and Statistics.


  • [2022.05-2023.06]   Research Intern at Nvidia Toronto AI Lab. Supervised by Dr Ye Yuan, Dr Sameh Khamis, and Prof. Sanja Filder.
  • [2022.01-2022.05]   Research Intern at Shanghai AI Lab. Supervised by Dr. Bo Dai.
  • [2020.01-2021.12]   Research Intern at SenseTime Research. Supervised by Dr. Ding Liang.
  • [2019.08-2020.07]   Research Assistant at MMLAB, CUHK. Supervised by Prof. Dahua Lin.
  • [2017.06-2018.12]   Research Intern at Megvii Research. Supervise by Dr, Gang Yu.

Academic Competition

  • Winner of COCO 2018 Challenge in Panoptic Segmentation Track
  • Winner of Mapillary 2018 Challenge in Panoptic Segmentation Track

Professional Activities

  • Conference Reviewer:

  • Journal Reviewer: