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GLASS: Graph and Vision-Language Assisted Semantic Shape Correspondence
Qinfeng Xiao, Guofeng Mei, Qilong Liu +5
Establishing dense correspondence across 3D shapes is crucial for fundamental downstream tasks, including texture transfer, shape interpolation, and robotic manipulation. However,…
Universal 3D Shape Matching via Coarse-to-Fine Language Guidance
Qinfeng Xiao, Guofeng Mei, Bo Yang +3
Establishing dense correspondences between shapes is a crucial task in computer vision and graphics, while prior approaches depend on near-isometric assumptions and homogeneous sub…
TRACE: Learning 3D Gaussian Physical Dynamics from Multi-view Videos
Jinxi Li, Ziyang Song, Bo Yang
In this paper, we aim to model 3D scene geometry, appearance, and physical information just from dynamic multi-view videos in the absence of any human labels. By leveraging physics…
FreeGave: 3D Physics Learning from Dynamic Videos by Gaussian Velocity
Jinxi Li, Ziyang Song, Siyuan Zhou +1
In this paper, we aim to model 3D scene geometry, appearance, and the underlying physics purely from multi-view videos. By applying various governing PDEs as PINN losses or incorpo…
OSN: Infinite Representations of Dynamic 3D Scenes from Monocular Videos
Ziyang Song, Jinxi Li, Bo Yang
It has long been challenging to recover the underlying dynamic 3D scene representations from a monocular RGB video. Existing works formulate this problem into finding a single most…
NVFi: Neural Velocity Fields for 3D Physics Learning from Dynamic Videos
Jinxi Li, Ziyang Song, Bo Yang
In this paper, we aim to model 3D scene dynamics from multi-view videos. Unlike the majority of existing works which usually focus on the common task of novel view synthesis within…