6 citations · 7 across the 8 of their papers we have counts for
4 papers · 1 filter
A Generative Adversarial Approach to Adversarial Attacks Guided by Contrastive Language-Image Pre-trained Model
Sampriti Soor, Alik Pramanick, Jothiprakash K +1
The rapid growth of deep learning has brought about powerful models that can handle various tasks, like identifying images and understanding language. However, adversarial attacks,…
Trans-defense: Transformer-based Denoiser for Adversarial Defense with Spatial-Frequency Domain Representation
Alik Pramanick, Mayank Bansal, Utkarsh Srivastava +2
In recent times, deep neural networks (DNNs) have been successfully adopted for various applications. Despite their notable achievements, it has become evident that DNNs are vulner…
C-LEAD: Contrastive Learning for Enhanced Adversarial Defense
Suklav Ghosh, Sonal Kumar, Arijit Sur
Deep neural networks (DNNs) have achieved remarkable success in computer vision tasks such as image classification, segmentation, and object detection. However, they are vulnerable…
Funnel-HOI: Top-Down Perception for Zero-Shot HOI Detection
Sandipan Sarma, Agney Talwarr, Arijit Sur
Human-object interaction detection (HOID) refers to localizing interactive human-object pairs in images and identifying the interactions. Since there could be an exponential number…