62 citations · 118 across the 15 of their papers we have counts for
11 papers · 1 filter
3D-Adapter: Geometry-Consistent Multi-View Diffusion for High-Quality 3D Generation
Hansheng Chen, Bokui Shen, Yulin Liu +7
Multi-view image diffusion models have significantly advanced open-domain 3D object generation. However, most existing models rely on 2D network architectures that lack inherent 3D…
MultiPhys: Multi-Person Physics-aware 3D Motion Estimation
Nicolas Ugrinovic, Boxiao Pan, Georgios Pavlakos +5
We introduce MultiPhys, a method designed for recovering multi-person motion from monocular videos. Our focus lies in capturing coherent spatial placement between pairs of individu…
Generic 3D Diffusion Adapter Using Controlled Multi-View Editing
Hansheng Chen, Ruoxi Shi, Yulin Liu +5
Open-domain 3D object synthesis has been lagging behind image synthesis due to limited data and higher computational complexity. To bridge this gap, recent works have investigated…
CAD: Photorealistic 3D Generation via Adversarial Distillation
Ziyu Wan, Despoina Paschalidou, Ian Huang +5
The increased demand for 3D data in AR/VR, robotics and gaming applications, gave rise to powerful generative pipelines capable of synthesizing high-quality 3D objects. Most of the…
PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point Tracking
Yang Zheng, Adam W. Harley, Bokui Shen +2
We introduce PointOdyssey, a large-scale synthetic dataset, and data generation framework, for the training and evaluation of long-term fine-grained tracking algorithms. Our goal i…
Banana: Banach Fixed-Point Network for Pointcloud Segmentation with Inter-Part Equivariance
Congyue Deng, Jiahui Lei, Bokui Shen +2
Equivariance has gained strong interest as a desirable network property that inherently ensures robust generalization. However, when dealing with complex systems such as articulate…
NAP: Neural 3D Articulation Prior
Jiahui Lei, Congyue Deng, Bokui Shen +2
We propose Neural 3D Articulation Prior (NAP), the first 3D deep generative model to synthesize 3D articulated object models. Despite the extensive research on generating 3D object…
GINA-3D: Learning to Generate Implicit Neural Assets in the Wild
Bokui Shen, Xinchen Yan, Charles R. Qi +5
Modeling the 3D world from sensor data for simulation is a scalable way of developing testing and validation environments for robotic learning problems such as autonomous driving.…
COPILOT: Human-Environment Collision Prediction and Localization from Egocentric Videos
Boxiao Pan, Bokui Shen, Davis Rempe +4
The ability to forecast human-environment collisions from egocentric observations is vital to enable collision avoidance in applications such as VR, AR, and wearable assistive robo…
ACID: Action-Conditional Implicit Visual Dynamics for Deformable Object Manipulation
Bokui Shen, Zhenyu Jiang, Christopher Choy +4
Manipulating volumetric deformable objects in the real world, like plush toys and pizza dough, bring substantial challenges due to infinite shape variations, non-rigid motions, and…
ADeLA: Automatic Dense Labeling with Attention for Viewpoint Adaptation in Semantic Segmentation
Yanchao Yang, Hanxiang Ren, He Wang +5
We describe an unsupervised domain adaptation method for image content shift caused by viewpoint changes for a semantic segmentation task. Most existing methods perform domain alig…