TP1.L2.3
APNET: GENERATING PRECISE ANOMALY PRIOR INFORMATION FOR MIXED-SUPERVISED DEFECT DETECTION
Guanji Li, Hongxia Gao, South China University of Technology, China
Session:
TP1.L2: Deep Neural Architecture Generation for Generative Models and Adversarial Learning Lecture
Track:
Special Sessions
Location:
Capital Suite - 16
Presentation Time:
Tue, 29 Oct, 15:06 - 15:24 Gulf Standard Time (UTC +4)
Session Chair:
Karen Eguiazarian, Tampere University
Session TP1.L2
TP1.L2.1: Towards Better Control of Latent Spaces for Face Editing
Savas Ozkan, Mete Ozay, Samsung Research UK, United Kingdom of Great Britain and Northern Ireland
TP1.L2.2: HOW TO TRAIN YOUR VAE
Mariano Rivera, Centro de Investigacion en Matematicas AC, Mexico
TP1.L2.3: APNET: GENERATING PRECISE ANOMALY PRIOR INFORMATION FOR MIXED-SUPERVISED DEFECT DETECTION
Guanji Li, Hongxia Gao, South China University of Technology, China
TP1.L2.4: DEFENDING AGAINST PHYSICAL ADVERSARIAL PATCH ATTACKS ON INFRARED HUMAN DETECTION
Lukas Strack, University of Freiburg, Germany; Futa Waseda, The University of Tokyo, National Institute of Informatics, Japan; Huy H. Nguyen, National Institute of Informatics, Japan; Yinqiang Zheng, The University of Tokyo, Japan; Isao Echizen, The University of Tokyo, National Institute of Informatics, Japan
TP1.L2.5: TRUSTWORTHY SR: RESOLVING AMBIGUITY IN IMAGE SUPER-RESOLUTION VIA DIFFUSION MODELS AND HUMAN FEEDBACK
Cansu Korkmaz, Koc University, Türkiye; Ege Cirakman, Istanbul Technical University, Türkiye; Ahmet Murat TEKALP, Zafer Dogan, Koc University, Türkiye
Contacts