1 citations · 2 across the 12 of their papers we have counts for
13 papers
PhyMo: Learning Physical Dynamics with Accurate and Continuous Motion from Multi-View Videos
Shangjia Liu, Jinxi Li, Siyuan Zhou +2
Recovering dynamic 3D scene geometry, appearance, and the physical motion states that govern scene evolution from multi-view videos is important yet challenging. A key difficulty i…
NeoMap: Training-free Novel-View Synthesis from Single Images and Videos
Jinxi Li, Tianyi Zhang, Yafei Yang +4
We study the challenging problem of novel view video synthesis from single images or monocular videos. Existing methods, which operate under the assumption that pre-trained video m…
PhysMani: Physics-principled 3D World Model for Dynamic Object Manipulation
Peng Yun, Shouwang Huang, Hao Li +3
Manipulating fast and dynamically moving targets in unstructured 3D environments remains challenging for embodied AI. Existing visual-language-action models and world models strugg…
FoundObj: Self-supervised Foundation Models as Rewards for Label-free 3D Object Segmentation
Zihui Zhang, Zhixuan Sun, Yafei Yang +3
We address the challenging task of 3D object segmentation in complex scene point clouds without relying on any scene-level human annotations during training. Existing methods are t…
EvObj: Learning Evolving Object-centric Representations for 3D Instance Segmentation without Scene Supervision
Jiahao Chen, Zihui Zhang, Yafei Yang +4
We introduce EvObj for unsupervised 3D instance segmentation that bridges the geometric domain gap between synthetic pretraining data and real-world point clouds. Current methods s…
PhysInOne: Visual Physics Learning and Reasoning in One Suite
Siyuan Zhou, Hejun Wang, Hu Cheng +36
We present PhysInOne, a large-scale synthetic dataset addressing the critical scarcity of physically-grounded training data for AI systems. Unlike existing datasets limited to mere…
FashionMAC: Deformation-Free Fashion Image Generation with Fine-Grained Model Appearance Customization
Rong Zhang, Jinxiao Li, Jingnan Wang +6
Garment-centric fashion image generation aims to synthesize realistic and controllable human models dressing a given garment, which has attracted growing interest due to its practi…
RayletDF: Raylet Distance Fields for Generalizable 3D Surface Reconstruction from Point Clouds or Gaussians
Shenxing Wei, Jinxi Li, Yafei Yang +2
In this paper, we present a generalizable method for 3D surface reconstruction from raw point clouds or pre-estimated 3D Gaussians by 3DGS from RGB images. Unlike existing coordina…
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…
RayDF: Neural Ray-surface Distance Fields with Multi-view Consistency
Zhuoman Liu, Bo Yang, Yan Luximon +2
In this paper, we study the problem of continuous 3D shape representations. The majority of existing successful methods are coordinate-based implicit neural representations. Howeve…