Exploring category-agnostic clusters for open-set domain adaptation

Exploring category-agnostic clusters for open-set domain adaptation

Unsupervised domain adaptation has received significant attention in recent years. Most of existing works tackle the closed-set scenario, assuming that the source and target domains share the exactly same categories. In practice, nevertheless, a target domain often contains samples of classes unseen...

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Bibliographic Details
Main Authors: PAN, Yingwei, YAO, Ting, LI, Yehao, NGO, Chong-wah, MEI, Tao
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2020
Subjects:
Computer Sciences
Graphics and Human Computer Interfaces
Online Access:https://ink.library.smu.edu.sg/sis_research/6485
https://ink.library.smu.edu.sg/context/sis_research/article/7488/viewcontent/Pan_Exploring_Category_Agnostic_Clusters_for_Open_Set_Domain_Adaptation_CVPR_2020_paper.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/6485
https://ink.library.smu.edu.sg/context/sis_research/article/7488/viewcontent/Pan_Exploring_Category_Agnostic_Clusters_for_Open_Set_Domain_Adaptation_CVPR_2020_paper.pdf

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