34 citations · 48 across the 15 of their papers we have counts for
12 papers · 1 filter
CrossPortrait: Cross-Species Portrait Animation via Adversarial Motion Alignment
Gezhong Pan, Zhe Li, Yunfan Tao +7
Cross-species portrait animation, which aims to animate a source portrait of species A using a driving video of species B, is particularly challenging due to substantial anatomical…
DeX-Portrait: Disentangled and Expressive Portrait Animation via Explicit and Latent Motion Representations
Yuxiang Shi, Zhe Li, Yanwen Wang +3
Portrait animation from a single source image and a driving video is a long-standing problem. Recent approaches tend to adopt diffusion-based image/video generation models for real…
MeshAvatar: Learning High-quality Triangular Human Avatars from Multi-view Videos
Yushuo Chen, Zerong Zheng, Zhe Li +2
We present a novel pipeline for learning high-quality triangular human avatars from multi-view videos. Recent methods for avatar learning are typically based on neural radiance fie…
LayGA: Layered Gaussian Avatars for Animatable Clothing Transfer
Siyou Lin, Zhe Li, Zhaoqi Su +3
Animatable clothing transfer, aiming at dressing and animating garments across characters, is a challenging problem. Most human avatar works entangle the representations of the hum…
TexVocab: Texture Vocabulary-conditioned Human Avatars
Yuxiao Liu, Zhe Li, Yebin Liu +1
To adequately utilize the available image evidence in multi-view video-based avatar modeling, we propose TexVocab, a novel avatar representation that constructs a texture vocabular…
HHAvatar: Gaussian Head Avatar with Dynamic Hairs
Zhanfeng Liao, Yuelang Xu, Zhe Li +6
Creating high-fidelity 3D head avatars has always been a research hotspot, but it remains a great challenge under lightweight sparse view setups. In this paper, we propose HHAvatar…
Animatable and Relightable Gaussians for High-fidelity Human Avatar Modeling
Zhe Li, Yipengjing Sun, Zerong Zheng +3
Modeling animatable human avatars from RGB videos is a long-standing and challenging problem. Recent works usually adopt MLP-based neural radiance fields (NeRF) to represent 3D hum…
PoseVocab: Learning Joint-structured Pose Embeddings for Human Avatar Modeling
Zhe Li, Zerong Zheng, Yuxiao Liu +2
Creating pose-driven human avatars is about modeling the mapping from the low-frequency driving pose to high-frequency dynamic human appearances, so an effective pose encoding meth…
AvatarCap: Animatable Avatar Conditioned Monocular Human Volumetric Capture
Zhe Li, Zerong Zheng, Hongwen Zhang +2
To address the ill-posed problem caused by partial observations in monocular human volumetric capture, we present AvatarCap, a novel framework that introduces animatable avatars in…
Lightweight Multi-person Total Motion Capture Using Sparse Multi-view Cameras
Yuxiang Zhang, Zhe Li, Liang An +3
Multi-person total motion capture is extremely challenging when it comes to handle severe occlusions, different reconstruction granularities from body to face and hands, drasticall…
POSEFusion: Pose-guided Selective Fusion for Single-view Human Volumetric Capture
Zhe Li, Tao Yu, Zerong Zheng +2
We propose POse-guided SElective Fusion (POSEFusion), a single-view human volumetric capture method that leverages tracking-based methods and tracking-free inference to achieve hig…
Robust 3D Self-portraits in Seconds
Zhe Li, Tao Yu, Chuanyu Pan +2
In this paper, we propose an efficient method for robust 3D self-portraits using a single RGBD camera. Benefiting from the proposed PIFusion and lightweight bundle adjustment algor…