activity
20192022
most citedLearning to Reconstruct People in Clothing from a Single RGB Camera

13 citations · 23 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2023

GAN-Avatar: Controllable Personalized GAN-based Human Head Avatar

Berna Kabadayi, Wojciech Zielonka, Bharat Lal Bhatnagar +2

Digital humans and, especially, 3D facial avatars have raised a lot of attention in the past years, as they are the backbone of several applications like immersive telepresence in…

cs.CV20221 cited

COUCH: Towards Controllable Human-Chair Interactions

Xiaohan Zhang, Bharat Lal Bhatnagar, Vladimir Guzov +2

Humans interact with an object in many different ways by making contact at different locations, creating a highly complex motion space that can be difficult to learn, particularly…

cs.CV20226 cited

BEHAVE: Dataset and Method for Tracking Human Object Interactions

Bharat Lal Bhatnagar, Xianghui Xie, Ilya A. Petrov +3

Modelling interactions between humans and objects in natural environments is central to many applications including gaming, virtual and mixed reality, as well as human behavior ana…

cs.CV2020

SIZER: A Dataset and Model for Parsing 3D Clothing and Learning Size Sensitive 3D Clothing

Garvita Tiwari, Bharat Lal Bhatnagar, Tony Tung +1

While models of 3D clothing learned from real data exist, no method can predict clothing deformation as a function of garment size. In this paper, we introduce SizerNet to predict…

cs.CV20203 cited

Unsupervised Shape and Pose Disentanglement for 3D Meshes

Keyang Zhou, Bharat Lal Bhatnagar, Gerard Pons-Moll

Parametric models of humans, faces, hands and animals have been widely used for a range of tasks such as image-based reconstruction, shape correspondence estimation, and animation.…

cs.CV2019

Multi-Garment Net: Learning to Dress 3D People from Images

Bharat Lal Bhatnagar, Garvita Tiwari, Christian Theobalt +1

We present Multi-Garment Network (MGN), a method to predict body shape and clothing, layered on top of the SMPL model from a few frames (1-8) of a video. Several experiments demons…