Gaurav Kumar Nayak

Orcid: 0000-0002-6406-6178

According to our database1, Gaurav Kumar Nayak authored at least 22 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

CityGuessr: City-Level Video Geo-Localization on a Global Scale.
Proceedings of the Computer Vision - ECCV 2024, 2024

Data-free Defense of Black Box Models Against Adversarial Attacks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
DAD++: Improved Data-free Test Time Adversarial Defense.
CoRR, 2023

Federated Learning on Heterogeneous Data via Adaptive Self-Distillation.
CoRR, 2023

DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DISBELIEVE: Distance Between Client Models Is Very Essential for Effective Local Model Poisoning Attacks.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023

2022
Mining Data Impressions From Deep Models as Substitute for the Unavailable Training Data.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Query Efficient Cross-Dataset Transferable Black-Box Attack on Action Recognition.
CoRR, 2022

Robust Few-shot Learning Without Using any Adversarial Samples.
CoRR, 2022

Data-free Defense of Black Box Models Against Adversarial Attacks.
CoRR, 2022

DAD: Data-free Adversarial Defense at Test Time.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
Data Impressions: Mining Deep Models to Extract Samples for Data-free Applications.
CoRR, 2021

Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Incremental Learning for Animal Pose Estimation using RBF k-DPP.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Beyond Classification: Knowledge Distillation using Multi-Object Impressions.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020
Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images.
Proceedings of the 6th IEEE International Conference on Multimedia Big Data, 2020

DeGAN: Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Zero-Shot Knowledge Distillation in Deep Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

Efficient Person Re-Identification in Videos Using Sequence Lazy Greedy Determinantal Point Process (SLGDPP).
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019


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