34 citations · 51 across the 7 of their papers we have counts for
7 papers
Split4D: Decomposed 4D Scene Reconstruction Without Video Segmentation
Yongzhen Hu, Yihui Yang, Haotong Lin +8
This paper addresses the problem of decomposed 4D scene reconstruction from multi-view videos. Recent methods achieve this by lifting video segmentation results to a 4D representat…
NaviNeRF: NeRF-based 3D Representation Disentanglement by Latent Semantic Navigation
Baao Xie, Bohan Li, Zequn Zhang +4
3D representation disentanglement aims to identify, decompose, and manipulate the underlying explanatory factors of 3D data, which helps AI fundamentally understand our 3D world. T…
Animatable Implicit Neural Representations for Creating Realistic Avatars from Videos
Sida Peng, Zhen Xu, Junting Dong +5
This paper addresses the challenge of reconstructing an animatable human model from a multi-view video. Some recent works have proposed to decompose a non-rigidly deforming scene i…
Animatable Neural Radiance Fields for Modeling Dynamic Human Bodies
Sida Peng, Junting Dong, Qianqian Wang +4
This paper addresses the challenge of reconstructing an animatable human model from a multi-view video. Some recent works have proposed to decompose a non-rigidly deforming scene i…
Reconstructing 3D Human Pose by Watching Humans in the Mirror
Qi Fang, Qing Shuai, Junting Dong +2
In this paper, we introduce the new task of reconstructing 3D human pose from a single image in which we can see the person and the person's image through a mirror. Compared to gen…
Motion Capture from Internet Videos
Junting Dong, Qing Shuai, Yuanqing Zhang +3
Recent advances in image-based human pose estimation make it possible to capture 3D human motion from a single RGB video. However, the inherent depth ambiguity and self-occlusion i…