We present a method for teaching machines to understand and model the
un...
Deep generative models have been recently extended to synthesizing 3D di...
We propose a 3D generation pipeline that uses diffusion models to genera...
Synthesizing interaction-involved human motions has been challenging due...
We present a framework for modeling interactional communication in dyadi...
Prior work for articulated 3D shape reconstruction often relies on
speci...
How to build AI that understands human intentions, and uses this knowled...
We introduce D3D-HOI: a dataset of monocular videos with ground truth
an...
Most existing monocular 3D pose estimation approaches only focus on a si...
We consider the problem of obtaining dense 3D reconstructions of humans ...
Although the essential nuance of human motion is often conveyed as a
com...
We present a method that infers spatial arrangements and shapes of human...
We propose a novel learned deep prior of body motion for 3D hand shape
s...
We propose a method for building large collections of human poses with f...
Recent advances in image-based 3D human shape estimation have been drive...
We present the first single-network approach for 2D whole-body pose
esti...
We present a new research task and a dataset to understand human social
...
The body pose of a person wearing a camera is of great interest for
appl...
We present a method to combine markerless motion capture and dense pose
...
We present the first method to capture the 3D total motion of a target p...
This paper proposes a new method for Non-Rigid Structure-from-Motion (NR...
We present a unified deformation model for the markerless capture of mul...
We present an approach to capture the 3D motion of a group of people eng...