activity
20192024
most citedDriving-Signal Aware Full-Body Avatars

71 citations · 130 across the 6 of their papers we have counts for

collaborators

8 papers

cs.GR2024

CHOICE: Coordinated Human-Object Interaction in Cluttered Environments for Pick-and-Place Actions

Jintao Lu, He Zhang, Yuting Ye +3

Animating human-scene interactions such as pick-and-place tasks in cluttered, complex layouts is a challenging task, with objects of a wide variation of geometries and articulation…

cs.CV2021

Active Learning of Neural Collision Handler for Complex 3D Mesh Deformations

Qingyang Tan, Zherong Pan, Breannan Smith +2

We present a robust learning algorithm to detect and handle collisions in 3D deforming meshes. Our collision detector is represented as a bilevel deep autoencoder with an attention…

cs.CV20213 cited

FrankMocap: A Monocular 3D Whole-Body Pose Estimation System via Regression and Integration

Yu Rong, Takaaki Shiratori, Hanbyul Joo

Most existing monocular 3D pose estimation approaches only focus on a single body part, neglecting the fact that the essential nuance of human motion is conveyed through a concert…

cs.CV202171 cited

Driving-Signal Aware Full-Body Avatars

Timur Bagautdinov, Chenglei Wu, Tomas Simon +6

We present a learning-based method for building driving-signal aware full-body avatars. Our model is a conditional variational autoencoder that can be animated with incomplete driv…

cs.CV20201 cited

InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Image

Gyeongsik Moon, Shoou-i Yu, He Wen +2

Analysis of hand-hand interactions is a crucial step towards better understanding human behavior. However, most researches in 3D hand pose estimation have focused on the isolated s…

cs.CV202055 cited

FrankMocap: Fast Monocular 3D Hand and Body Motion Capture by Regression and Integration

Yu Rong, Takaaki Shiratori, Hanbyul Joo

Although the essential nuance of human motion is often conveyed as a combination of body movements and hand gestures, the existing monocular motion capture approaches mostly focus…