Tal Reiss

19 papers A* 3Journal 13Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Alterbute: Editing Intrinsic Attributes of Objects in Images.
CoRR
Tal Reiss, Daniel Winter, Matan Cohen, Alex Rav-Acha, Yael Pritch, Ariel Shamir, Yedid Hoshen
2025 J jnl
An Attribute-based Method for Video Anomaly Detection.
Trans. Mach. Learn. Res.
Tal Reiss, Yedid Hoshen
2025 J jnl
Enabling Users to Falsify Deepfake Attacks.
Trans. Mach. Learn. Res.
Tal Reiss, Bar Cavia, Yedid Hoshen
2024 — conf
From Zero to Hero: Cold-Start Anomaly Detection.
ACL (Findings)
Tal Reiss, George Kour, Naama Zwerdling, Ateret Anaby-Tavor, Yedid Hoshen
2024 J jnl
From Zero to Hero: Cold-Start Anomaly Detection.
CoRR
Tal Reiss, George Kour, Naama Zwerdling, Ateret Anaby-Tavor, Yedid Hoshen
2024 J jnl
Real-Time Deepfake Detection in the Real-World.
CoRR
Bar Cavia, Eliahu Horwitz, Tal Reiss, Yedid Hoshen
2023 J jnl
Detecting Deepfakes Without Seeing Any.
CoRR
Tal Reiss, Bar Cavia, Yedid Hoshen
2023 A* conf
Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond.
ICCV
Oren Barkan, Tal Reiss, Jonathan Weill, Ori Katz, Roy Hirsch, Itzik Malkiel, Noam Koenigstein
2023 J jnl
Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond.
CoRR
Oren Barkan, Tal Reiss, Jonathan Weill, Ori Katz, Roy Hirsch, Itzik Malkiel, Noam Koenigstein
2023 A* conf
Mean-Shifted Contrastive Loss for Anomaly Detection.
AAAI
Tal Reiss, Yedid Hoshen
2023 J jnl
No Free Lunch: The Hazards of Over-Expressive Representations in Anomaly Detection.
CoRR
Tal Reiss, Niv Cohen, Yedid Hoshen
2022 — conf
Anomaly Detection Requires Better Representations.
ECCV Workshops (4)
Tal Reiss, Niv Cohen, Eliahu Horwitz, Ron Abutbul, Yedid Hoshen
2022 J jnl
Anomaly Detection Requires Better Representations.
CoRR
Tal Reiss, Niv Cohen, Eliahu Horwitz, Ron Abutbul, Yedid Hoshen
2022 J jnl
Attribute-based Representations for Accurate and Interpretable Video Anomaly Detection.
CoRR
Tal Reiss, Yedid Hoshen
2021 J jnl
Mean-Shifted Contrastive Loss for Anomaly Detection.
CoRR
Tal Reiss, Yedid Hoshen
2021 A* conf
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation.
CVPR
Tal Reiss, Niv Cohen, Liron Bergman, Yedid Hoshen
2021 — conf
Use and Perceptions of Multi-Monitor Workstations: A Natural Experiment.
SER&IP@ICSE
Guy Amir, Ayala Prusak, Tal Reiss, Nir Zabari, Dror G. Feitelson
2021 J jnl
Use and Perceptions of Multi-Monitor Workstations: A Natural Experiment.
CoRR
Guy Amir, Ayala Prusak, Tal Reiss, Nir Zabari, Dror G. Feitelson
2020 J jnl
PANDA - Adapting Pretrained Features for Anomaly Detection.
CoRR
Tal Reiss, Niv Cohen, Liron Bergman, Yedid Hoshen