Yang Fu 付旸
Yang is currently a Ph.D student in Electrical and Computer Engineering (ECE) at University of California San Diego (UCSD), advised by Prof. Xiaolong Wang. Before that, he obtained his M.S. in ECE at UIUC in 2020 under the supervision of Prof. Thomas S. Huang (1936-2020) and Prof. Humphrey Shi.
Research Interests
My current research focuses on computer vision and machine learning. Specifically, I have recently worked in
Computer Vision
- Neural Radiance Fields, 6D pose estimation, video instance/object segmentation.
Machine Learning
- semi-supervised learning, self-supervised representation learning, test-time training.
Please refer to my Google scholar for a full list of my publications.
News
- [2024.02] Three papers are accepted to CVPR 2024.
- [2024.01] 3D Reconstruction with Generalizable Neural Fields using Scene Prior is accepted to ICLR 2024.
- [2023.09] I start my internship at NVIDIA Learning and Perception Research Group advised by Sifei Liu.
- [2023.07] I’m selected to be a recipient of Qualcomm Innovation Fellowship 2023.
- [2023.05] MonoNeRF: Learning Generalizable NeRFs from Monocular Videos without Camera Poses is accepted to ICML 2023.
- [2023.01] Self-Supervised Geometric Correspondence for Category-Level 6D Object Pose Estimation in the Wild is accepted to ICLR 2023.
[2022.09] Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset is accepted to NeurIPS 2022.
[2022.06] DexMV: Imitation Learning for Dexterous Manipulation from Human Videos is accepted to ECCV 2022.
[2022.06] Check out our Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset which introduces an in-the-wild object-centric RGBD dataset with 5000+ videos over 1700+ objects. We peform semi-supervised 6D object pose estimation on it without human annotations.
- [2022.06] I start my summer internship at NVIDIA Learning and Perception Research Group advised by Sifei Liu.
[2022.06] I start my Ph.D journey at UCSD under the supervision of Prof. Xiaolong Wang.
[2021.03] One paper accepted to CVPR 2021 as oral presentation (paper).