TA2.L4.1
Decoupling Domain Invariance and Variance with Tailored Prompts for Open-Set Domain Adaptation
Shihao Zeng, Xinghong Liu, Yi Zhou, Southeast University, China
Session:
TA2.L4: Robust Machine Learning Methods for Image & Video Processing - IV Lecture
Track:
Visual Artificial Intelligence
Location:
Lecture Room 4
Presentation Time:
Tue, 29 Oct, 10:30 - 10:48 Gulf Standard Time (UTC +4)
Session Chair:
Ihsen Alouani, Queen’s University Belfast
Session TA2.L4
TA2.L4.1: Decoupling Domain Invariance and Variance with Tailored Prompts for Open-Set Domain Adaptation
Shihao Zeng, Xinghong Liu, Yi Zhou, Southeast University, China
TA2.L4.2: CASCADING UNKNOWN DETECTION WITH KNOWN CLASSIFICATION FOR OPEN SET RECOGNITION
Daniel Brignac, Abhijit Mahalanobis, University of Arizona, United States of America
TA2.L4.3: 3DLaneFormer: Rethinking Learning Views for 3D Lane Detection
Kun Dong, Jian Xue, Xing Lan, Ke Lu, University of Chinese Academy of Sciences, China
TA2.L4.4: AdvART: Adversarial Art for Camouflaged Object Detection Attacks
Amira Guesmi, New York University Abu Dhabi, United Arab Emirates; Ioan Marius Bilasco, University of Lille, France; Muhammad Shafique, New York University Abu Dhabi, United Arab Emirates; Ihsen Alouani, Queen’s University Belfast, United Kingdom of Great Britain and Northern Ireland
TA2.L4.5: LSDM-PCB: A Lightweight Small Defect Detection Model For Printed Circuit Board
Qi Zeng, Dongguan University Of Technology&OPT Machine Vision Tech Co., Ltd., China; Chongren Zhao, Pengfei He, Hongchao Gao, OPT Machine Vision Tech Co., Ltd., China
Contacts