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Article
Estimation of Near-Instance-Level Attribute Bottleneck for Zero-Shot Learning
Zero-Shot Learning (ZSL) involves transferring knowledge from seen classes to unseen classes by establishing connections between visual and semantic spaces. Traditional ZSL methods identify novel classes by cl...
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Article
Combining Pixel-Level and Structure-Level Adaptation for Semantic Segmentation
Domain adaptation for semantic segmentation requires pixel-level knowledge transfer from a labeled source domain to an unlabeled target domain. Existing approaches typically align the features of the source an...
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Chapter and Conference Paper
Weighted Contrastive Hashing
The development of unsupervised hashing is advanced by the recent popular contrastive learning paradigm. However, previous contrastive learning-based works have been hampered by (1) insufficient data similarit...