WE5.L4.5
ENHANCING ADVERSARIAL ROBUSTNESS OF FOUNDATION MODELS WITHOUT DATA CENTRALIZATION
Koshiro Toishi, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama, Hokkaido University, Japan
Session:
WE5.L4: Information Forensics and Security 2 Lecture
Track:
[IF] Information Forensics and Security
Location:
Room 2
Presentation Time:
Wed, 17 Sep, 17:30 - 17:45 Anchorage Time (UTC -8)
Session Chair:
William Puech, Univ Montpellier
Presentation
Discussion
Resources
No resources available.
Session WE5.L4
WE5.L4.1: DIFFDEMORPH: EXTENDING REFERENCE-FREE DEMORPHING TO UNSEEN FACES
Nitish Shukla, Arun Ross, Michigan State University, United States
WE5.L4.2: FACIAL IDENTITY EDITING: TOWARDS EFFECTIVE DE-IDENTIFICATION
Jinhyeong Park, Seangmin Lee, Muhammad Shaheryar, Soon Ki Jung, Kyungpook National University, Korea (South)
WE5.L4.3: FACELIVT: FACE RECOGNITION USING LINEAR VISION TRANSFORMER WITH STRUCTURAL REPARAMETERIZATION FOR MOBILE DEVICE
Novendra Setyawan, National Formosa University, Taiwan; Chi-Chia Sun, National Taipei University, Taiwan; Mao-Hsiu Hsu, Wen-Kai Kuo, National Formosa University, Taiwan; Jun-Wei Hsieh, National Yang Ming Chiao Tung University, Taiwan
WE5.L4.4: WaViT-CDC : Wavelet Vision Transformer with Central Difference Convolutions for Spatial-Frequency Deepfake Detection
Nour Eldin Alaa Badr, Jean-Christophe Nebel, Darrel Greenhill, Xing Liang, Kingston University School of Computer Science and Mathematics, United Kingdom of Great Britain and Northern Ireland
WE5.L4.5: ENHANCING ADVERSARIAL ROBUSTNESS OF FOUNDATION MODELS WITHOUT DATA CENTRALIZATION
Koshiro Toishi, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama, Hokkaido University, Japan
WE5.L4.6: FEW-SHOT CLASS-INCREMENTAL LEARNING FOR EFFICIENT SAR AUTOMATIC TARGET RECOGNITION
George Karantaidis, Athanasios Pantsios, Ioannis Kompatsiaris, Symeon Papadopoulos, Information Technologies Institute, Centre for Research and Technology Hellas, Greece
Contacts