Tal Reiss

According to our database, Tal Reiss authored at least 13 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2025

An Attribute-based Method for Video Anomaly Detection.

Tal Reiss, Yedid Hoshen

Trans. Mach. Learn. Res., 2025

Enabling Users to Falsify Deepfake Attacks.

Tal Reiss, Bar Cavia, Yedid Hoshen

Trans. Mach. Learn. Res., 2025

2024

Real-Time Deepfake Detection in the Real-World.

Bar Cavia, Eliahu Horwitz, Tal Reiss, Yedid Hoshen

CoRR, 2024

From Zero to Hero: Cold-Start Anomaly Detection.

Tal Reiss, George Kour, Naama Zwerdling, Ateret Anaby-Tavor, Yedid Hoshen

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Detecting Deepfakes Without Seeing Any.

Tal Reiss, Bar Cavia, Yedid Hoshen

CoRR, 2023

No Free Lunch: The Hazards of Over-Expressive Representations in Anomaly Detection.

Tal Reiss, Niv Cohen, Yedid Hoshen

CoRR, 2023

Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond.

Oren Barkan, Tal Reiss, Jonathan Weill, Ori Katz, Roy Hirsch, Itzik Malkiel, Noam Koenigstein

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Mean-Shifted Contrastive Loss for Anomaly Detection.

Tal Reiss, Yedid Hoshen

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Attribute-based Representations for Accurate and Interpretable Video Anomaly Detection.

Tal Reiss, Yedid Hoshen

CoRR, 2022

Anomaly Detection Requires Better Representations.

Tal Reiss, Niv Cohen, Eliahu Horwitz, Ron Abutbul, Yedid Hoshen

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

2021

Use and Perceptions of Multi-Monitor Workstations: A Natural Experiment.

Guy Amir, Ayala Prusak, Tal Reiss, Nir Zabari, Dror G. Feitelson

Proceedings of the 8th IEEE/ACM International Workshop on Software Engineering Research and Industrial Practice, 2021

PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation.

Tal Reiss, Niv Cohen, Liron Bergman, Yedid Hoshen

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

PANDA - Adapting Pretrained Features for Anomaly Detection.

Tal Reiss, Niv Cohen, Liron Bergman, Yedid Hoshen

CoRR, 2020