Gaurav Kumar Nayak

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 31

Top Topics

Pose Estimation

Top Venues

Publications

M. Yashwanth, Gaurav Kumar Nayak, Harsh Rangwani, Arya Singh, R. Venkatesh Babu, Anirban Chakraborty
Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning. WACV (2024)
M. Yashwanth, Gaurav Kumar Nayak, Arya Singh, Yogesh Singh, Anirban Chakraborty
Federated Learning on Heterogeneous Data via Adaptive Self-Distillation. CoRR (2023)
Vicente Vivanco Cepeda, Gaurav Kumar Nayak, Mubarak Shah
GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization. NeurIPS (2023)
Indu Joshi, Priyank Upadhya, Gaurav Kumar Nayak, Peter Schüffler, Nassir Navab
DISBELIEVE: Distance Between Client Models Is Very Essential for Effective Local Model Poisoning Attacks. ISIC/Care-AI/MedAGI/DeCaF@MICCAI (2023)
Gaurav Kumar Nayak, Inder Khatri, Shubham Randive, Ruchit Rawal, Anirban Chakraborty
DAD++: Improved Data-free Test Time Adversarial Defense. CoRR (2023)
Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty
DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers. WACV (2023)
Indu Joshi, Priyank Upadhya, Gaurav Kumar Nayak, Peter Schüffler, Nassir Navab
DISBELIEVE: Distance Between Client Models is Very Essential for Effective Local Model Poisoning Attacks. CoRR (2023)
Vicente Vivanco Cepeda, Gaurav Kumar Nayak, Mubarak Shah
GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization. CoRR (2023)
Gaurav Kumar Nayak, Ruchit Rawal, Rohit Lal, Himanshu Patil, Anirban Chakraborty
Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems. CVPR Workshops (2022)
Rohit Gupta, Naveed Akhtar, Gaurav Kumar Nayak, Ajmal Mian, Mubarak Shah
Query Efficient Cross-Dataset Transferable Black-Box Attack on Action Recognition. CoRR (2022)
Gaurav Kumar Nayak, Ruchit Rawal, Inder Khatri, Anirban Chakraborty
Robust Few-shot Learning Without Using any Adversarial Samples. CoRR (2022)
Gaurav Kumar Nayak, Inder Khatri, Shubham Randive, Ruchit Rawal, Anirban Chakraborty
Data-free Defense of Black Box Models Against Adversarial Attacks. CoRR (2022)
Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty
DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers. CoRR (2022)
Gaurav Kumar Nayak, Konda Reddy Mopuri, Saksham Jain, Anirban Chakraborty
Mining Data Impressions From Deep Models as Substitute for the Unavailable Training Data. IEEE Trans. Pattern Anal. Mach. Intell. 44 (11) (2022)
Gaurav Kumar Nayak, Ruchit Rawal, Rohit Lal, Himanshu Patil, Anirban Chakraborty
Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems. CoRR (2022)
Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty
DAD: Data-free Adversarial Defense at Test Time. WACV (2022)
Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty
DAD: Data-free Adversarial Defense at Test Time. CoRR (2022)
Gaurav Kumar Nayak, Het Shah, Anirban Chakraborty
Incremental Learning for Animal Pose Estimation using RBF k-DPP. CoRR (2021)
Gaurav Kumar Nayak, Monish Keswani, Sharan Seshadri, Anirban Chakraborty
Beyond Classification: Knowledge Distillation using Multi-Object Impressions. BMVC (2021)
Gaurav Kumar Nayak, Konda Reddy Mopuri, Anirban Chakraborty
Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation. WACV (2021)
Gaurav Kumar Nayak, Het Shah, Anirban Chakraborty
Incremental Learning for Animal Pose Estimation using RBF k-DPP. BMVC (2021)
Gaurav Kumar Nayak, Monish Keswani, Sharan Seshadri, Anirban Chakraborty
Beyond Classification: Knowledge Distillation using Multi-Object Impressions. CoRR (2021)
Gaurav Kumar Nayak, Konda Reddy Mopuri, Saksham Jain, Anirban Chakraborty
Data Impressions: Mining Deep Models to Extract Samples for Data-free Applications. CoRR (2021)
Gaurav Kumar Nayak, Konda Reddy Mopuri, Anirban Chakraborty
Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation. CoRR (2020)
Sravanti Addepalli, Gaurav Kumar Nayak, Anirban Chakraborty, Venkatesh Babu Radhakrishnan
DeGAN: Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier. AAAI (2020)
Gaurav Kumar Nayak, Saksham Jain, R. Venkatesh Babu, Anirban Chakraborty
Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images. BigMM (2020)
Gaurav Kumar Nayak, Saksham Jain, R. Venkatesh Babu, Anirban Chakraborty
Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images. CoRR (2020)
Gaurav Kumar Nayak, Konda Reddy Mopuri, Vaisakh Shaj, R. Venkatesh Babu, Anirban Chakraborty
Zero-Shot Knowledge Distillation in Deep Networks. CoRR (2019)
Gaurav Kumar Nayak, Utkarsh Shreemali, R. Venkatesh Babu, Anirban Chakraborty
Efficient Person Re-Identification in Videos Using Sequence Lazy Greedy Determinantal Point Process (SLGDPP). ICIP (2019)
Sravanti Addepalli, Gaurav Kumar Nayak, Anirban Chakraborty, R. Venkatesh Babu
DeGAN : Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier. CoRR (2019)
Gaurav Kumar Nayak, Konda Reddy Mopuri, Vaisakh Shaj, Venkatesh Babu Radhakrishnan, Anirban Chakraborty
Zero-Shot Knowledge Distillation in Deep Networks. ICML (2019)