21 citations · 57 across the 9 of their papers we have counts for
9 papers
Weakly-supervised 3D Pose Transfer with Keypoints
Jinnan Chen, Chen Li, Gim Hee Lee
The main challenges of 3D pose transfer are: 1) Lack of paired training data with different characters performing the same pose; 2) Disentangling pose and shape information from th…
OD-NeRF: Efficient Training of On-the-Fly Dynamic Neural Radiance Fields
Zhiwen Yan, Chen Li, Gim Hee Lee
Dynamic neural radiance fields (dynamic NeRFs) have demonstrated impressive results in novel view synthesis on 3D dynamic scenes. However, they often require complete video sequenc…
Overcoming the Trade-off Between Accuracy and Plausibility in 3D Hand Shape Reconstruction
Ziwei Yu, Chen Li, Linlin Yang +4
Direct mesh fitting for 3D hand shape reconstruction is highly accurate. However, the reconstructed meshes are prone to artifacts and do not appear as plausible hand shapes. Conver…
ScarceNet: Animal Pose Estimation with Scarce Annotations
Chen Li, Gim Hee Lee
Animal pose estimation is an important but under-explored task due to the lack of labeled data. In this paper, we tackle the task of animal pose estimation with scarce annotations,…
NeRF-DS: Neural Radiance Fields for Dynamic Specular Objects
Zhiwen Yan, Chen Li, Gim Hee Lee
Dynamic Neural Radiance Field (NeRF) is a powerful algorithm capable of rendering photo-realistic novel view images from a monocular RGB video of a dynamic scene. Although it warps…
Coarse-to-fine Animal Pose and Shape Estimation
Chen Li, Gim Hee Lee
Most existing animal pose and shape estimation approaches reconstruct animal meshes with a parametric SMAL model. This is because the low-dimensional pose and shape parameters of t…