Adil Karjauv

According to our database, Adil Karjauv authored at least 15 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

MoViE: Mobile Diffusion for Video Editing.

Adil Karjauv, Noor Fathima, Ioannis Lelekas, Fatih Porikli, Amir Ghodrati, Amirhossein Habibian

CoRR, 2024

Object-Centric Diffusion for Efficient Video Editing.

Kumara Kahatapitiya, Adil Karjauv, Davide Abati, Fatih Porikli, Yuki M. Asano, Amirhossein Habibian

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Simple Techniques are Sufficient for Boosting Adversarial Transferability.

Chaoning Zhang, Philipp Benz, Adil Karjauv, In So Kweon, Choong Seon Hong

Proceedings of the 31st ACM International Conference on Multimedia, 2023

2022

Investigating Top-k White-Box and Transferable Black-box Attack.

Chaoning Zhang, Philipp Benz, Adil Karjauv, Jae-Won Cho, Kang Zhang, In So Kweon

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Towards Robust Data Hiding Against (JPEG) Compression: A Pseudo-Differentiable Deep Learning Approach.

Chaoning Zhang, Adil Karjauv, Philipp Benz, In So Kweon

CoRR, 2021

Revisiting Batch Normalization for Improving Corruption Robustness.

Philipp Benz, Chaoning Zhang, Adil Karjauv, In So Kweon

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Towards Robust Deep Hiding Under Non-Differentiable Distortions for Practical Blind Watermarking.

Chaoning Zhang, Adil Karjauv, Philipp Benz, In So Kweon

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

A Survey on Universal Adversarial Attack.

Chaoning Zhang, Philipp Benz, Chenguo Lin, Adil Karjauv, Jing Wu, In So Kweon

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Motionsnap: A Motion Sensor-Based Approach for Automatic Capture and Editing of Photos and Videos on Smartphones.

Adil Karjauv, Sanzhar Bakhtiyarov, Chaoning Zhang, Jean-Charles Bazin, In So Kweon

Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

Universal Adversarial Training with Class-Wise Perturbations.

Philipp Benz, Chaoning Zhang, Adil Karjauv, In So Kweon

Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

Data-free Universal Adversarial Perturbation and Black-box Attack.

Chaoning Zhang, Philipp Benz, Adil Karjauv, In So Kweon

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Adversarial Robustness Comparison of Vision Transformer and MLP-Mixer to CNNs.

Philipp Benz, Soomin Ham, Chaoning Zhang, Adil Karjauv, In So Kweon

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards a Fourier Perspective.

Chaoning Zhang, Philipp Benz, Adil Karjauv, In So Kweon

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Robustness May Be at Odds with Fairness: An Empirical Study on Class-wise Accuracy.

Philipp Benz, Chaoning Zhang, Adil Karjauv, In So Kweon

Proceedings of the NeurIPS 2020 Workshop on Pre-registration in Machine Learning, 2020

UDH: Universal Deep Hiding for Steganography, Watermarking, and Light Field Messaging.

Chaoning Zhang, Philipp Benz, Adil Karjauv, Geng Sun, In So Kweon

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020