Efficient Person Re-Identification in Videos Using Sequence Lazy Greedy Determinantal Point Process (SLGDPP). - Gaurav Kumar Nayak; Utkarsh Shreemali; R. Venkatesh Babu; Anirban Chakraborty 001 (ICIP, 2019)

Zero-Shot Knowledge Distillation in Deep Networks. - Gaurav Kumar Nayak; Konda Reddy Mopuri; Vaisakh Shaj; Venkatesh Babu Radhakrishnan; Anirban Chakraborty 001 (ICML, 2019)

DeGAN: Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier. - Sravanti Addepalli; Gaurav Kumar Nayak; Anirban Chakraborty 001; Venkatesh Babu Radhakrishnan (AAAI, 2020)

Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images. - Gaurav Kumar Nayak; Saksham Jain; R. Venkatesh Babu; Anirban Chakraborty 001 (BigMM, 2020)

Beyond Classification: Knowledge Distillation using Multi-Object Impressions. - Gaurav Kumar Nayak; Monish Keswani; Sharan Seshadri; Anirban Chakraborty 001 (BMVC, 2021)

Incremental Learning for Animal Pose Estimation using RBF k-DPP. - Gaurav Kumar Nayak; Het Shah; Anirban Chakraborty 001 (BMVC, 2021)

Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation. - Gaurav Kumar Nayak; Konda Reddy Mopuri; Anirban Chakraborty 001 (WACV, 2021)

Data Impressions: Mining Deep Models to Extract Samples for Data-free Applications. - Gaurav Kumar Nayak; Konda Reddy Mopuri; Saksham Jain; Anirban Chakraborty 001 (CoRR, 2021)

Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems. - Gaurav Kumar Nayak; Ruchit Rawal; Rohit Lal; Himanshu Patil; Anirban Chakraborty 001 (CVPR Workshops, 2022)

DAD: Data-free Adversarial Defense at Test Time. - Gaurav Kumar Nayak; Ruchit Rawal; Anirban Chakraborty 001 (WACV, 2022)

Data-free Defense of Black Box Models Against Adversarial Attacks. - Gaurav Kumar Nayak; Inder Khatri; Shubham Randive; Ruchit Rawal; Anirban Chakraborty 001 (CoRR, 2022)

Query Efficient Cross-Dataset Transferable Black-Box Attack on Action Recognition. - Rohit Gupta 012; Naveed Akhtar; Gaurav Kumar Nayak; Ajmal Mian; Mubarak Shah (CoRR, 2022)

Mining Data Impressions From Deep Models as Substitute for the Unavailable Training Data. - Gaurav Kumar Nayak; Konda Reddy Mopuri; Saksham Jain; Anirban Chakraborty 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

DISBELIEVE: Distance Between Client Models Is Very Essential for Effective Local Model Poisoning Attacks. - Indu Joshi; Priyank Upadhya; Gaurav Kumar Nayak; Peter J. Schüffler; Nassir Navab (ISIC/Care-AI/MedAGI/DeCaF@MICCAI, 2023)

GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization. - Vicente Vivanco Cepeda; Gaurav Kumar Nayak; Mubarak Shah (NeurIPS, 2023)

DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers. - Gaurav Kumar Nayak; Ruchit Rawal; Anirban Chakraborty 001 (WACV, 2023)

Federated Learning on Heterogeneous Data via Adaptive Self-Distillation. - M. Yashwanth; Gaurav Kumar Nayak; Arya Singh; Yogesh Singh; Anirban Chakraborty 001 (CoRR, 2023)

Data-free Defense of Black Box Models Against Adversarial Attacks. - Gaurav Kumar Nayak; Inder Khatri; Ruchit Rawal; Anirban Chakraborty 001 (CVPR Workshops, 2024)

CityGuessr: City-Level Video Geo-Localization on a Global Scale. - Parth Parag Kulkarni; Gaurav Kumar Nayak; Mubarak Shah (ECCV (63), 2024)

Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning. - M. Yashwanth; Gaurav Kumar Nayak; Harsh Rangwani; Arya Singh; R. Venkatesh Babu; Anirban Chakraborty 001 (WACV, 2024)

Adaptive Self-Distillation for Minimizing Client Drift in Heterogeneous Federated Learning. - M. Yashwanth; Gaurav Kumar Nayak; Arya Singh; Yogesh Simmhan; Anirban Chakraborty 001 (Trans. Mach. Learn. Res., 2024)

DLCR: A Generative Data Expansion Framework via Diffusion for Clothes-Changing Person Re-Id. - Nyle Siddiqui; Florinel-Alin Croitoru; Gaurav Kumar Nayak; Radu Tudor Ionescu; Mubarak Shah (WACV, 2025)

DAD++: Improved data-free test time adversarial defense. - Gaurav Kumar Nayak; Inder Khatri; Shubham Randive; Ruchit Rawal; Anirban Chakraborty 001 (Neurocomputing, 2025)

Robust Few-Shot Learning Without Using Any Adversarial Samples. - Gaurav Kumar Nayak; Ruchit Rawal; Inder Khatri; Anirban Chakraborty 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

MGD3: Mode-Guided Dataset Distillation using Diffusion Models. - Jeffrey A. Chan-Santiago; Praveen Tirupattur; Gaurav Kumar Nayak; Gaowen Liu; Mubarak Shah (CoRR, 2025)