Research map / Label-efficient and robust learning / Domain adaptation and generalization
Domain Adaptive Hashing Retrieval via VLM Assisted Pseudo-Labeling and Dual Space Adaptation
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Proposes a domain adaptive hashing method for cross-domain retrieval that uses VLM-assisted pseudo-labeling and dual-space adaptation to generate binary codes for unlabeled target samples.
Problem
Unsupervised domain adaptive hashing: learning compact binary codes for unlabeled target-domain samples using labeled source data, so that semantically similar samples map to nearby Hamming codes.
Approach
Uses a vision-language model to assist pseudo-labeling of unlabeled target samples and performs adaptation in dual spaces (per the title; details beyond the abstract are not available).
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