activity
20222024
most citedLASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discovery

15 citations · 28 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20243 cited

SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image using Latent Video Diffusion

Vikram Voleti, Chun-Han Yao, Mark Boss +6

We present Stable Video 3D (SV3D) -- a latent video diffusion model for high-resolution, image-to-multi-view generation of orbital videos around a 3D object. Recent work on 3D gene…

cs.CV2024

ANIM: Accurate Neural Implicit Model for Human Reconstruction from a single RGB-D image

Marco Pesavento, Yuanlu Xu, Nikolaos Sarafianos +7

Recent progress in human shape learning, shows that neural implicit models are effective in generating 3D human surfaces from limited number of views, and even from a single RGB im…

cs.CV202310 cited

ARTIC3D: Learning Robust Articulated 3D Shapes from Noisy Web Image Collections

Chun-Han Yao, Amit Raj, Wei-Chih Hung +4

Estimating 3D articulated shapes like animal bodies from monocular images is inherently challenging due to the ambiguities of camera viewpoint, pose, texture, lighting, etc. We pro…

cs.CV2022

Learning Visibility for Robust Dense Human Body Estimation

Chun-Han Yao, Jimei Yang, Duygu Ceylan +3

Estimating 3D human pose and shape from 2D images is a crucial yet challenging task. While prior methods with model-based representations can perform reasonably well on whole-body…

cs.CV202215 cited

LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discovery

Chun-Han Yao, Wei-Chih Hung, Yuanzhen Li +3

Creating high-quality articulated 3D models of animals is challenging either via manual creation or using 3D scanning tools. Therefore, techniques to reconstruct articulated 3D obj…