85 citations · 92 across the 10 of their papers we have counts for
11 papers
Query Efficient Cross-Dataset Transferable Black-Box Attack on Action Recognition
Rohit Gupta, Naveed Akhtar, Gaurav Kumar Nayak +2
Black-box adversarial attacks present a realistic threat to action recognition systems. Existing black-box attacks follow either a query-based approach where an attack is optimized…
Robust Few-shot Learning Without Using any Adversarial Samples
Gaurav Kumar Nayak, Ruchit Rawal, Inder Khatri +1
The high cost of acquiring and annotating samples has made the `few-shot' learning problem of prime importance. Existing works mainly focus on improving performance on clean data a…
DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers
Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty
Certified defense using randomized smoothing is a popular technique to provide robustness guarantees for deep neural networks against l2 adversarial attacks. Existing works use thi…
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…
Beyond Classification: Knowledge Distillation using Multi-Object Impressions
Gaurav Kumar Nayak, Monish Keswani, Sharan Seshadri +1
Knowledge Distillation (KD) utilizes training data as a transfer set to transfer knowledge from a complex network (Teacher) to a smaller network (Student). Several works have recen…
Incremental Learning for Animal Pose Estimation using RBF k-DPP
Gaurav Kumar Nayak, Het Shah, Anirban Chakraborty
Pose estimation is the task of locating keypoints for an object of interest in an image. Animal Pose estimation is more challenging than estimating human pose due to high inter and…