9 papers
Real2Sim in HOI: Toward Physically Plausible HOI Reconstruction from Monocular Videos
Yubo Zhao, Yujin Chai, Yunao Dong +4
Recovering 4D human-object interaction (HOI) from monocular video is a key step toward scalable 3D content creation, embodied AI, and simulation-based learning. Recent methods can…
CoMoVi: Co-Generation of 3D Human Motions and Realistic Videos
Chengfeng Zhao, Jiazhi Shu, Yubo Zhao +7
In this paper, we find that the generation of 3D human motions and 2D human videos is intrinsically coupled. 3D motions provide the structural prior for plausibility and consistenc…
UNIC: Neural Garment Deformation Field for Real-time Clothed Character Animation
Chengfeng Zhao, Junbo Qi, Yulou Liu +6
Simulating physically realistic garment deformations is an essential task for virtual immersive experience, which is often achieved by physics simulation methods. However, these me…
GO-Renderer: Generative Object Rendering with 3D-aware Controllable Video Diffusion Models
Zekai Gu, Shuoxuan Feng, Yansong Wang +6
Reconstructing a renderable 3D model from images is a useful but challenging task. Recent feedforward 3D reconstruction methods have demonstrated remarkable success in efficiently…
Track4World: Feedforward World-centric Dense 3D Tracking of All Pixels
Jiahao Lu, Jiayi Xu, Wenbo Hu +5
Estimating the 3D trajectory of every pixel from a monocular video is crucial and promising for a comprehensive understanding of the 3D dynamics of videos. Recent monocular 3D trac…
UniSH: Unifying Scene and Human Reconstruction in a Feed-Forward Pass
Mengfei Li, Peng Li, Zheng Zhang +9
We present UniSH, a unified, feed-forward framework for joint metric-scale 3D scene and human reconstruction. A key challenge in this domain is the scarcity of large-scale, annotat…