Published multiple papers on topics such as object pose estimation, self-supervised monocular 6D object pose estimation, etc., at top conferences like CVPR, ECCV; GDRNPP work won most of the awards on BOP Challenge 2022; Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimation was ESI Highly Cited.
Research Experience
Joined JD.com as a member of DMT (Doctoral Management Trainee) in 2022; co-organized the 7th International Workshop on Recovering 6D Object Pose and BOP Challenge 2022 @ ECCV 22; won the Best Method on Single Dataset Award of BOP Challenge 2020 and the Best RGB-Only Method Award of BOP Challenge 2019.
Education
Received B.E. degree from the Department of Automation, School of Information Science and Technology, Tsinghua University in 2016, and Ph.D. degree under the supervision of Prof. Xiangyang Ji in 2022.
Background
Research interests lie in Computer Vision and Deep Learning. During his Ph.D., he focused on 6D object pose estimation with RGB based methods, and is also interested in other vision and robotics related perception problems in both 2D and 3D worlds.