13 citations · 20 across the 6 of their papers we have counts for
6 papers
Improving Domain Adaptation Through Class Aware Frequency Transformation
Vikash Kumar, Himanshu Patil, Rohit Lal +1
In this work, we explore the usage of the Frequency Transformation for reducing the domain shift between the source and target domain (e.g., synthetic image and real image respecti…
Prior-guided Source-free Domain Adaptation for Human Pose Estimation
Dripta S. Raychaudhuri, Calvin-Khang Ta, Arindam Dutta +2
Domain adaptation methods for 2D human pose estimation typically require continuous access to the source data during adaptation, which can be challenging due to privacy, memory, or…
Open-Set Multi-Source Multi-Target Domain Adaptation
Rohit Lal, Arihant Gaur, Aadhithya Iyer +2
Single-Source Single-Target Domain Adaptation (1S1T) aims to bridge the gap between a labelled source domain and an unlabelled target domain. Despite 1S1T being a well-researched t…
CoNMix for Source-free Single and Multi-target Domain Adaptation
Vikash Kumar, Rohit Lal, Himanshu Patil +1
This work introduces the novel task of Source-free Multi-target Domain Adaptation and proposes adaptation framework comprising of \textbf{Co}nsistency with \textbf{N}uclear-Norm Ma…
Efficient Neural Net Approaches in Metal Casting Defect Detection
Rohit Lal, Bharath Kumar Bolla, Sabeesh Ethiraj
One of the most pressing challenges prevalent in the steel manufacturing industry is the identification of surface defects. Early identification of casting defects can help boost p…
Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems
Gaurav Kumar Nayak, Ruchit Rawal, Rohit Lal +2
Adversarial attack perturbs an image with an imperceptible noise, leading to incorrect model prediction. Recently, a few works showed inherent bias associated with such attack (rob…