Self-supervised Image Retrieval
Self-Supervised Image Retrieval is a machine learning approach within image retrieval that leverages self-supervised pretraining to learn discriminative visual representations from unlabeled image data by generating pseudo-labels through intrinsic data properties, thereby eliminating the need for human-annotated supervision.
25
Publications
916
Citations
112
Authors
55
Institutions
Publications per year
2017–2026
25
Parents
25
Self-Supervised Learning of Visual Features through Embedding Images into Text Topic Spaces
Lluís Gómez, Yash Patel, Marçal Rusiñol et al. · 2017 · 100 citations
Solving Mixed-Modal Jigsaw Puzzle for Fine-Grained Sketch-Based Image Retrieval
Kaiyue Pang, Yongxin Yang, Timothy M. Hospedales et al. · 2020 · 93 citations
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55

Harbin Institute of Technology
Harbin, China
3 h-index
7 publications
128 citations

Shanghai Jiao Tong University
Shanghai, China
2 h-index
9 publications
249 citations

Huazhong University of Science and Technology
Wuhan, China
2 h-index
7 publications
182 citations
Wuhan National Laboratory for Optoelectronics
Wuhan, China
2 h-index
6 publications
153 citations
Tencent (China)
Shenzhen, China
2 h-index
3 publications
52 citations

University of Edinburgh
Edinburgh, United Kingdom
2 h-index
3 publications
151 citations
Institució Catalana de Recerca i Estudis Avançats
Barcelona, Spain
1 h-index
1 publications
21 citations

Sorbonne Université
Paris, France
1 h-index
1 publications
72 citations
1–8 of 55
Repository · 3 publications · 80 citations
3
h-index
3 publications · 67 citations
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Conference · 2 publications · 146 citations
2
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1 publications · 32 citations
1
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TPAMI · 1 publications · 16 citations
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