Conventional Domain Adaptation (DA) methods aim to learn domain-invarian...
Universal Domain Adaptation (UniDA) deals with the problem of knowledge
...
The prime challenge in unsupervised domain adaptation (DA) is to mitigat...
Conventional domain adaptation (DA) techniques aim to improve domain
tra...
Available 3D human pose estimation approaches leverage different forms o...
Articulation-centric 2D/3D pose supervision forms the core training obje...
The advances in monocular 3D human pose estimation are dominated by
supe...
Open compound domain adaptation (OCDA) has emerged as a practical adapta...
Unsupervised domain adaptation (DA) has gained substantial interest in
s...
Multi-Source Domain Adaptation (MSDA) deals with the transfer of task
kn...
We introduce a practical Domain Adaptation (DA) paradigm called
Class-In...
We present a deployment friendly, fast bottom-up framework for multi-per...
We present a self-supervised human mesh recovery framework to infer huma...
Estimation of 3D human pose from monocular image has gained considerable...
Camera captured human pose is an outcome of several sources of variation...
There is a strong incentive to develop versatile learning techniques tha...
There has been a tremendous progress in Domain Adaptation (DA) for visua...
Despite the remarkable success of generative adversarial networks, their...
Aiming towards human-level generalization, there is a need to explore
ad...
An unsupervised human action modeling framework can provide useful
pose-...
Human motion prediction model has applications in various fields of comp...
Understanding the geometry and pose of objects in 2D images is a fundame...
Understanding and extracting 3D information of objects from monocular 2D...
Supervised deep learning methods have shown promising results for the ta...