55 citations · 195 across the 24 of their papers we have counts for
4 papers · 1 filter
CHORUS: Learning Canonicalized 3D Human-Object Spatial Relations from Unbounded Synthesized Images
Sookwan Han, Hanbyul Joo
We present a method for teaching machines to understand and model the underlying spatial common sense of diverse human-object interactions in 3D in a self-supervised way. This is a…
NCHO: Unsupervised Learning for Neural 3D Composition of Humans and Objects
Taeksoo Kim, Shunsuke Saito, Hanbyul Joo
Deep generative models have been recently extended to synthesizing 3D digital humans. However, previous approaches treat clothed humans as a single chunk of geometry without consid…
Chupa: Carving 3D Clothed Humans from Skinned Shape Priors using 2D Diffusion Probabilistic Models
Byungjun Kim, Patrick Kwon, Kwangho Lee +4
We propose a 3D generation pipeline that uses diffusion models to generate realistic human digital avatars. Due to the wide variety of human identities, poses, and stochastic detai…
Locomotion-Action-Manipulation: Synthesizing Human-Scene Interactions in Complex 3D Environments
Jiye Lee, Hanbyul Joo
Synthesizing interaction-involved human motions has been challenging due to the high complexity of 3D environments and the diversity of possible human behaviors within. We present…