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ORCIDGaurav Kumar Nayak
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2020 – today
- 2024
[c15]Gaurav Kumar Nayak, Inder Khatri, Ruchit Rawal, Anirban Chakraborty:
Data-free Defense of Black Box Models Against Adversarial Attacks. CVPR Workshops 2024: 254-263- [c14]Parth Parag Kulkarni, Gaurav Kumar Nayak, Mubarak Shah:
CityGuessr: City-Level Video Geo-Localization on a Global Scale. ECCV (63) 2024: 293-311 - [c13]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: 2276-2285 - 2023
- [c12]Indu Joshi, Priyank Upadhya, Gaurav Kumar Nayak, Peter J. Schüffler, Nassir Navab:
DISBELIEVE: Distance Between Client Models Is Very Essential for Effective Local Model Poisoning Attacks. ISIC/Care-AI/MedAGI/DeCaF@MICCAI 2023: 297-310 - [c11]Vicente Vivanco Cepeda, Gaurav Kumar Nayak, Mubarak Shah:
GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization. NeurIPS 2023 - [c10]Gaurav Kumar Nayak
, Ruchit Rawal, Anirban Chakraborty:
DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers. WACV 2023: 4611-4620 - [i17]M. Yashwanth, Gaurav Kumar Nayak, Arya Singh, Yogesh Singh, Anirban Chakraborty:
Federated Learning on Heterogeneous Data via Adaptive Self-Distillation. CoRR abs/2305.19600 (2023) - [i16]Indu Joshi, Priyank Upadhya, Gaurav Kumar Nayak, Peter J. Schüffler, Nassir Navab:
DISBELIEVE: Distance Between Client Models is Very Essential for Effective Local Model Poisoning Attacks. CoRR abs/2308.07387 (2023) - [i15]Gaurav Kumar Nayak, Inder Khatri, Shubham Randive, Ruchit Rawal, Anirban Chakraborty:
DAD++: Improved Data-free Test Time Adversarial Defense. CoRR abs/2309.05132 (2023) - [i14]Vicente Vivanco Cepeda, Gaurav Kumar Nayak, Mubarak Shah:
GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization. CoRR abs/2309.16020 (2023) - 2022
- [j1]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): 8465-8481 (2022) - [c9]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: 4331-4340 - [c8]Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty:
DAD: Data-free Adversarial Defense at Test Time. WACV 2022: 3788-3797 - [i13]Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty:
DAD: Data-free Adversarial Defense at Test Time. CoRR abs/2204.01568 (2022) - [i12]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 abs/2205.02604 (2022) - [i11]Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty:
DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers. CoRR abs/2210.08929 (2022) - [i10]Gaurav Kumar Nayak, Inder Khatri, Shubham Randive, Ruchit Rawal, Anirban Chakraborty:
Data-free Defense of Black Box Models Against Adversarial Attacks. CoRR abs/2211.01579 (2022) - [i9]Gaurav Kumar Nayak, Ruchit Rawal, Inder Khatri, Anirban Chakraborty:
Robust Few-shot Learning Without Using any Adversarial Samples. CoRR abs/2211.01598 (2022) - [i8]Rohit Gupta, Naveed Akhtar, Gaurav Kumar Nayak, Ajmal Mian, Mubarak Shah:
Query Efficient Cross-Dataset Transferable Black-Box Attack on Action Recognition. CoRR abs/2211.13171 (2022) - 2021
- [c7]Gaurav Kumar Nayak, Monish Keswani, Sharan Seshadri, Anirban Chakraborty:
Beyond Classification: Knowledge Distillation using Multi-Object Impressions. BMVC 2021: 65 - [c6]Gaurav Kumar Nayak, Het Shah, Anirban Chakraborty:
Incremental Learning for Animal Pose Estimation using RBF k-DPP. BMVC 2021: 188 - [c5]Gaurav Kumar Nayak, Konda Reddy Mopuri, Anirban Chakraborty:
Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation. WACV 2021: 1429-1437 - [i7]Gaurav Kumar Nayak, Konda Reddy Mopuri, Saksham Jain, Anirban Chakraborty:
Data Impressions: Mining Deep Models to Extract Samples for Data-free Applications. CoRR abs/2101.06069 (2021) - [i6]Gaurav Kumar Nayak, Het Shah, Anirban Chakraborty:
Incremental Learning for Animal Pose Estimation using RBF k-DPP. CoRR abs/2110.13598 (2021) - [i5]Gaurav Kumar Nayak, Monish Keswani, Sharan Seshadri, Anirban Chakraborty:
Beyond Classification: Knowledge Distillation using Multi-Object Impressions. CoRR abs/2110.14215 (2021) - 2020
- [c4]Sravanti Addepalli, Gaurav Kumar Nayak, Anirban Chakraborty, Venkatesh Babu Radhakrishnan:
DeGAN: Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier. AAAI 2020: 3130-3137 - [c3]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: 267-271 - [i4]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 abs/2008.00878 (2020) - [i3]Gaurav Kumar Nayak, Konda Reddy Mopuri, Anirban Chakraborty:
Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation. CoRR abs/2011.09113 (2020)
2010 – 2019
- 2019
- [c2]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: 4569-4573 - [c1]Gaurav Kumar Nayak, Konda Reddy Mopuri, Vaisakh Shaj, Venkatesh Babu Radhakrishnan, Anirban Chakraborty:
Zero-Shot Knowledge Distillation in Deep Networks. ICML 2019: 4743-4751 - [i2]Gaurav Kumar Nayak, Konda Reddy Mopuri, Vaisakh Shaj, R. Venkatesh Babu, Anirban Chakraborty:
Zero-Shot Knowledge Distillation in Deep Networks. CoRR abs/1905.08114 (2019) - [i1]Sravanti Addepalli, Gaurav Kumar Nayak, Anirban Chakraborty, R. Venkatesh Babu:
DeGAN : Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier. CoRR abs/1912.11960 (2019)
Coauthor Index
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