Open-set domain adaptation by deconfounding domain gaps

• Main Authors: ZHAO, Xin, WANG, Shengsheng, SUN, Qianru
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Open-set domain adaptation; Image classification; Artificial Intelligence and Robotics; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/7556; https://ink.library.smu.edu.sg/context/sis_research/article/8559/viewcontent/Open_Set_Domain_Adaptation_by_Deconfounding_Domain_Gaps__NeuroComputing_.pdf
• Institution: Singapore Management University

Open-Set Domain Adaptation (OSDA) aims to adapt the model trained on a source domain to the recognition tasks in a target domain while shielding any distractions caused by open-set classes, i.e., the classes “unknown” to the source model. Compared to standard DA, the key of OSDA lies in the separati...