10 papers · 1 filter
TGRHuman: Text-Guided Realistic 3D Human Generation via Diffusion Renderer
Muxin Zhang, Chaohui Yu, Yuanwang Yang +3
Realistic 3D human generation plays a crucial role in many graphics applications. However, current methods still struggle to generate high-quality human geometry and texture while…
IMPose: Interactive Multi-person Pose Estimation with Dynamic Correction Propagation
Haoyang Ge, Jian Ma, Ziwen Wang +5
High-quality dynamic human pose annotation equips AI with precise motion kinematics to enable human behavior mastery, yet remains labor-intensive and time-consuming. Current annota…
Stability-Driven Motion Generation for Object-Guided Human-Human Co-Manipulation
Jiahao Xu, Xiaohan Yuan, Xingchen Wu +3
Co-manipulation requires multiple humans to synchronize their motions with a shared object while ensuring reasonable interactions, maintaining natural poses, and preserving stable…
Contrastive Multi-Modal Hypergraph Reasoning for 3D Crowd Mesh Recovery
Minghao Sun, Chongyang Xu, Yitao Xie +2
Multi-person 3D reconstruction is pivotal for real-world interaction analysis, yet remains challenging due to severe occlusions and depth ambiguity. Current approaches typically re…
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…
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…