7 papers · 1 filter
Crowd4D: Scene-Aware Monocular 4D Crowd Reconstruction
Hongbo Kang, Tianyi Zhou, Qingyang Yang +4
Recovering scene-consistent 4D crowd motion from monocular video in large-scale scenes remains challenging due to severe depth ambiguity and complex scene geometry. Existing monocu…
OAHuman: Occlusion-Aware 3D Human Reconstruction from Monocular Images
Yuanwang Yang, Hongliang Liu, Muxin Zhang +4
Monocular 3D human reconstruction in real-world scenarios remains highly challenging due to frequent occlusions from surrounding objects, people, or image truncation. Such occlusio…
DyCrowd: Towards Dynamic Crowd Reconstruction from a Large-scene Video
Hao Wen, Hongbo Kang, Jian Ma +5
3D reconstruction of dynamic crowds in large scenes has become increasingly important for applications such as city surveillance and crowd analysis. However, current works attempt…
FOF-X: Towards Real-time Detailed Human Reconstruction from a Single Image
Qiao Feng, Yuanwang Yang, Yebin Liu +3
We introduce FOF-X for real-time reconstruction of detailed human geometry from a single image. Balancing real-time speed against high-quality results is a persistent challenge, ma…
HumanCoser: Layered 3D Human Generation via Semantic-Aware Diffusion Model
Yi Wang, Jian Ma, Ruizhi Shao +3
This paper aims to generate physically-layered 3D humans from text prompts. Existing methods either generate 3D clothed humans as a whole or support only tight and simple clothing…
R2Human: Real-Time 3D Human Appearance Rendering from a Single Image
Yuanwang Yang, Qiao Feng, Yu-Kun Lai +1
Rendering 3D human appearance from a single image in real-time is crucial for achieving holographic communication and immersive VR/AR. Existing methods either rely on multi-camera…
Layered 3D Human Generation via Semantic-Aware Diffusion Model
Yi Wang, Jian Ma, Ruizhi Shao +4
The generation of 3D clothed humans has attracted increasing attention in recent years. However, existing work cannot generate layered high-quality 3D humans with consistent body s…