Discrepancy and Structure-Based Contrast for Test-Time Adaptive Retrieval-Reference-Cited by-同舟云学术

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Discrepancy and Structure-Based Contrast for Test-Time Adaptive Retrieval

Published:2024 Issue: Volume:26 Page:8665-8677
ISSN:1520-9210
Container-title:IEEE Transactions on Multimedia
language:
Short-container-title:IEEE Trans. Multimedia

Author:

Ma Zeyu¹^ORCID,Li Yuqi²^ORCID,Luo Yizhi³^ORCID,Luo Xiao⁴^ORCID,Li Jinxing¹^ORCID,Chen Chong⁵^ORCID,Hua Xian-Sheng⁵^ORCID,Lu Guangming¹^ORCID

Affiliation:

1. Harbin Institute of Technology, Shenzhen, China

2. Chengdu NiuRuijie Technology Company, Chengdu, China

3. Sichuan Intelligent Transportation System Management Company, Ltd., Chengdu, China

4. Department of Computer Science, University of California, Los Angeles, CA, USA

5. Terminus Group, Beijing, China

Funder

National Natural Science Foundation of China

Shenzhen Key Technical Project

Guangdong International Science and Technology Cooperation Project

Shenzhen Fundamental Research and Discipline Layout project

Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies

Shenzhen Colleges and Universities Stable Support Program

Key Laboratory of Industrial Equipment Quality Big Data

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6046/10384483/10478505.pdf?arnumber=10478505

Reference70 articles.

1. Improved Deep Unsupervised Hashing via Prototypical Learning

2. Unsupervised Hashing with Semantic Concept Mining

3. Deep Hash Distillation for Image Retrieval

4. A Survey on Deep Hashing Methods

5. Improved Deep Unsupervised Hashing with Fine-grained Semantic Similarity Mining for Multi-Label Image Retrieval

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1. Automatic Meter Pointer Reading Based on Knowledge Distillation;Lecture Notes in Computer Science;2024

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