46 citations · 47 across the 5 of their papers we have counts for
6 papers · 1 filter
Animal Pose Labeling Using General-Purpose Point Trackers
Zhuoyang Pan, Boxiao Pan, Guandao Yang +2
Automatically estimating animal poses from videos is important for studying animal behaviors. Existing methods do not perform reliably since they are trained on datasets that are n…
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…
ActAnywhere: Subject-Aware Video Background Generation
Boxiao Pan, Zhan Xu, Chun-Hao Paul Huang +4
Generating video background that tailors to foreground subject motion is an important problem for the movie industry and visual effects community. This task involves synthesizing b…
JacobiNeRF: NeRF Shaping with Mutual Information Gradients
Xiaomeng Xu, Yanchao Yang, Kaichun Mo +3
We propose a method that trains a neural radiance field (NeRF) to encode not only the appearance of the scene but also semantic correlations between scene points, regions, or entit…
PartNeRF: Generating Part-Aware Editable 3D Shapes without 3D Supervision
Konstantinos Tertikas, Despoina Paschalidou, Boxiao Pan +5
Impressive progress in generative models and implicit representations gave rise to methods that can generate 3D shapes of high quality. However, being able to locally control and e…
Efficient Geometry-aware 3D Generative Adversarial Networks
Eric R. Chan, Connor Z. Lin, Matthew A. Chan +9
Unsupervised generation of high-quality multi-view-consistent images and 3D shapes using only collections of single-view 2D photographs has been a long-standing challenge. Existing…