1.1k citations · 3.7k across the 97 of their papers we have counts for
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InvGAN: Invertible GANs
Partha Ghosh, Dominik Zietlow, Michael J. Black +2
Generation of photo-realistic images, semantic editing and representation learning are a few of many potential applications of high resolution generative models. Recent progress in…
GOAL: Generating 4D Whole-Body Motion for Hand-Object Grasping
Omid Taheri, Vasileios Choutas, Michael J. Black +1
Generating digital humans that move realistically has many applications and is widely studied, but existing methods focus on the major limbs of the body, ignoring the hands and hea…
ICON: Implicit Clothed humans Obtained from Normals
Yuliang Xiu, Jinlong Yang, Dimitrios Tzionas +1
Current methods for learning realistic and animatable 3D clothed avatars need either posed 3D scans or 2D images with carefully controlled user poses. In contrast, our goal is to l…
Putting People in their Place: Monocular Regression of 3D People in Depth
Yu Sun, Wu Liu, Qian Bao +3
Given an image with multiple people, our goal is to directly regress the pose and shape of all the people as well as their relative depth. Inferring the depth of a person in an ima…
I M Avatar: Implicit Morphable Head Avatars from Videos
Yufeng Zheng, Victoria Fernández Abrevaya, Marcel C. Bühler +3
Traditional 3D morphable face models (3DMMs) provide fine-grained control over expression but cannot easily capture geometric and appearance details. Neural volumetric representati…
The Power of Points for Modeling Humans in Clothing
Qianli Ma, Jinlong Yang, Siyu Tang +1
Currently it requires an artist to create 3D human avatars with realistic clothing that can move naturally. Despite progress on 3D scanning and modeling of human bodies, there is s…