1 code implementation • 28 Sep 2023 • Yilei Wu, Zijian Dong, Chongyao Chen, Wangchunshu Zhou, Juan Helen Zhou
In representation learning, regression has traditionally received less attention than classification.
1 code implementation • 3 Jul 2023 • Zijian Dong, Yilei Wu, Yu Xiao, Joanna Su Xian Chong, Yueming Jin, Juan Helen Zhou
In this work, we proposed the first interpretable framework for brain FC trajectory embedding with application to neurodegenerative disease diagnosis and prognosis, namely Brain Tokenized Graph Transformer (Brain TokenGT).
no code implementations • ICCV 2023 • Zijian Dong, Xu Chen, Jinlong Yang, Michael J. Black, Otmar Hilliges, Andreas Geiger
The key to progress is hence to learn generative models of 3D avatars from abundant unstructured 2D image collections.
no code implementations • CVPR 2022 • Zijian Dong, Chen Guo, Jie Song, Xu Chen, Andreas Geiger, Otmar Hilliges
We present a novel method to learn Personalized Implicit Neural Avatars (PINA) from a short RGB-D sequence.
no code implementations • ICCV 2021 • Zijian Dong, Jie Song, Xu Chen, Chen Guo, Otmar Hilliges
In this paper we contribute a simple yet effective approach for estimating 3D poses of multiple people from multi-view images.
Ranked #16 on 3D Multi-Person Pose Estimation on Shelf
3D Multi-Person Pose Estimation Multi-Person Pose Estimation
no code implementations • ECCV 2020 • Xu Chen, Zijian Dong, Jie Song, Andreas Geiger, Otmar Hilliges
Many object pose estimation algorithms rely on the analysis-by-synthesis framework which requires explicit representations of individual object instances.