4 citations · 4 across the 3 of their papers we have counts for
6 papers · 1 filter
MoGA: 3D Generative Avatar Prior for Monocular Gaussian Avatar Reconstruction
Zijian Dong, Longteng Duan, Jie Song +2
We present MoGA, a novel method to reconstruct high-fidelity 3D Gaussian avatars from a single-view image. The main challenge lies in inferring unseen appearance and geometric deta…
AvatarPose: Avatar-guided 3D Pose Estimation of Close Human Interaction from Sparse Multi-view Videos
Feichi Lu, Zijian Dong, Jie Song +1
Despite progress in human motion capture, existing multi-view methods often face challenges in estimating the 3D pose and shape of multiple closely interacting people. This difficu…
AG3D: Learning to Generate 3D Avatars from 2D Image Collections
Zijian Dong, Xu Chen, Jinlong Yang +3
While progress in 2D generative models of human appearance has been rapid, many applications require 3D avatars that can be animated and rendered. Unfortunately, most existing meth…
PINA: Learning a Personalized Implicit Neural Avatar from a Single RGB-D Video Sequence
Zijian Dong, Chen Guo, Jie Song +3
We present a novel method to learn Personalized Implicit Neural Avatars (PINA) from a short RGB-D sequence. This allows non-expert users to create a detailed and personalized virtu…
Shape-aware Multi-Person Pose Estimation from Multi-View Images
Zijian Dong, Jie Song, Xu Chen +2
In this paper we contribute a simple yet effective approach for estimating 3D poses of multiple people from multi-view images. Our proposed coarse-to-fine pipeline first aggregates…
Category Level Object Pose Estimation via Neural Analysis-by-Synthesis
Xu Chen, Zijian Dong, Jie Song +2
Many object pose estimation algorithms rely on the analysis-by-synthesis framework which requires explicit representations of individual object instances. In this paper we combine…