activity
20222024
most citedImproving Domain Adaptation Through Class Aware Frequency Transformation

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

collaborators

5 papers

cs.CV202413 cited

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…

cs.CV2024

Sketch-guided Image Inpainting with Partial Discrete Diffusion Process

Nakul Sharma, Aditay Tripathi, Anirban Chakraborty +1

In this work, we study the task of sketch-guided image inpainting. Unlike the well-explored natural language-guided image inpainting, which excels in capturing semantic details, th…

cs.CV2023

DAD++: Improved Data-free Test Time Adversarial Defense

Gaurav Kumar Nayak, Inder Khatri, Shubham Randive +2

With the increasing deployment of deep neural networks in safety-critical applications such as self-driving cars, medical imaging, anomaly detection, etc., adversarial robustness h…

cs.CV2023

Query-guided Attention in Vision Transformers for Localizing Objects Using a Single Sketch

Aditay Tripathi, Anand Mishra, Anirban Chakraborty

In this work, we investigate the problem of sketch-based object localization on natural images, where given a crude hand-drawn sketch of an object, the goal is to localize all the…

cs.LG2022

DAD: Data-free Adversarial Defense at Test Time

Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty

Deep models are highly susceptible to adversarial attacks. Such attacks are carefully crafted imperceptible noises that can fool the network and can cause severe consequences when…