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Deep Metric Learning (DML) has long attracted the attention of the machine learning community as a key objective.
A stochastic approximation method
Herbert Robbins and Sutton Monro · 1951
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Neighbourhood components analysis
Jacob Goldberger, Geoffrey E Hinton, Sam Roweis, and Russ R Salakhutdinov · 2004
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Learning a similarity metric discriminatively, with application to face verification
Sumit Chopra, Raia Hadsell, and Yann LeCun · 2005
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Dimensionality reduction by learning an invariant mapping
Raia Hadsell, Sumit Chopra, and Yann LeCun · 2006
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Rank-based distance metric learning: An application to image retrieval
Jung-Eun Lee, Rong Jin, and Anil K Jain · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Distance metric learning for large margin nearest neighbor classification
Kilian Q Weinberger and Lawrence K Saul · 2009
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The caltech-ucsd birds-200-2011 dataset
Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge Belongie · 2011
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3d object representations for fine-grained categorization
Jonathan Krause, Michael Stark, Jia Deng, and Li Fei-Fei · 2013
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Empirical evaluation of gated recurrent neural networks on sequence modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Localize me anywhere, anytime: a multi-task point-retrieval approach
Guoyu Lu, Yan Yan, Li Ren, Jingkuan Song, Nicu Sebe, and Chandra Kambhamettu · 2015
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Person re-identification by multi-channel parts-based cnn with improved triplet loss function
De Cheng, Yihong Gong, Sanping Zhou, Jinjun Wang, and Nanning Zheng · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Deepfashion: Powering robust clothes recognition and retrieval with rich annotations
Ziwei Liu, Ping Luo, Shi Qiu, Xiaogang Wang, and Xiaoou Tang · 2016
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Deep metric learning via lifted structured feature embedding
Hyun Oh Song, Yu Xiang, Stefanie Jegelka, and Silvio Savarese · 2016
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Learnable structured clustering framework for deep metric learning
Hyun Oh Song, Stefanie Jegelka, Vivek Rathod, and Kevin Murphy · 2016
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In defense of the triplet loss for person re-identification
Alexander Hermans, Lucas Beyer, and Bastian Leibe · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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No fuss distance metric learning using proxies
Yair Movshovitz-Attias, Alexander Toshev, Thomas K Leung, Sergey Ioffe, and Saurabh Singh · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Exploring the limits of weakly supervised pretraining
Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, and Laurens Van Der Maaten · 2018
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Efficient parametrization of multi-domain deep neural networks
Sylvestre-Alvise Rebuffi, Hakan Bilen, and Andrea Vedaldi · 2018
Cited alongside, same era.
The inaturalist species classification and detection dataset
Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alex Shepard, Hartwig Adam, Pietro Perona, and Serge Belongie · 2018
Cited alongside, same era.
Deep cosine metric learning for person re-identification
Nicolai Wojke and Alex Bewley · 2018
Cited alongside, same era.
Retrieving and classifying affective images via deep metric learning
Jufeng Yang, Dongyu She, Yu-Kun Lai, and Ming-Hsuan Yang · 2018
Cited alongside, same era.
Parameter-efficient transfer learning for nlp
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly · 2019
Cited alongside, same era.
Improving diversity of image captioning through variational autoencoders and adversarial learning
Robust and decomposable average precision for image retrieval
Elias Ramzi, Nicolas Thome, Clément Rambour, Nicolas Audebert, and Xavier Bitot · 2021
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Beyond the deep metric learning: enhance the cross-modal matching with adversarial discriminative domain regularization
Li Ren, Kai Li, LiQiang Wang, and Kien Hua · 2021
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Imagenet-21k pretraining for the masses
Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, and Lihi Zelnik-Manor · 2021
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Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2021
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Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models
Elad Ben Zaken, Shauli Ravfogel, and Yoav Goldberg · 2021
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Li Ren, Guo-Jun Qi, and Kien Hua · 2019
Cited alongside, same era.
Multi-similarity loss with general pair weighting for deep metric learning
Xun Wang, Xintong Han, Weilin Huang, Dengke Dong, and Matthew R Scott · 2019
Cited alongside, same era.
Smooth-ap: Smoothing the path towards large-scale image retrieval
Andrew Brown, Weidi Xie, Vicky Kalogeiton, and Andrew Zisserman · 2020
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Cited alongside, same era.
Self-supervising fine-grained region similarities for large-scale image localization
Yixiao Ge, Haibo Wang, Feng Zhu, Rui Zhao, and Hongsheng Li · 2020
Cited alongside, same era.
Proxy anchor loss for deep metric learning
Sungyeon Kim, Dongwon Kim, Minsu Cho, and Suha Kwak · 2020
Cited alongside, same era.
M-adda: Unsupervised domain adaptation with deep metric learning
Issam H Laradji and Reza Babanezhad · 2020
Cited alongside, same era.
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Hyperbolic vision transformers: Combining improvements in metric learning
Aleksandr Ermolov, Leyla Mirvakhabova, Valentin Khrulkov, Nicu Sebe, and Ivan Oseledets · 2022
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
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Visual prompt tuning
Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge Belongie, Bharath Hariharan, and Ser-Nam Lim · 2022
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Maple: Multi-modal prompt learning
Muhammad Uzair Khattak, Hanoona Rasheed, Muhammad Maaz, Salman Khan, and Fahad Shahbaz Khan · 2022
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Recall@ k surrogate loss with large batches and similarity mixup
Yash Patel, Giorgos Tolias, and Jiří Matas · 2022
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Non-isotropy regularization for proxy-based deep metric learning
Karsten Roth, Oriol Vinyals, and Zeynep Akata · 2022
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It takes two to tango: Mixup for deep metric learning
Shashanka Venkataramanan, Bill Psomas, Yannis Avrithis, Ewa Kijak, Laurent Amsaleg, and Konstantinos Karantzalos · 2022
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Hierarchical proxy-based loss for deep metric learning
Zhibo Yang, Muhammet Bastan, Xinliang Zhu, Douglas Gray, and Dimitris Samaras · 2022
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Pcl: Proxy-based contrastive learning for domain generalization
Xufeng Yao, Yang Bai, Xinyun Zhang, Yuechen Zhang, Qi Sun, Ran Chen, Ruiyu Li, and Bei Yu · 2022
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Attributable visual similarity learning
Borui Zhang, Wenzhao Zheng, Jie Zhou, and Jiwen Lu · 2022
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Compositional prompt tuning with motion cues for open-vocabulary video relation detection
Kaifeng Gao, Long Chen, Hanwang Zhang, Jun Xiao, and Qianru Sun · 2023
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Hier: Metric learning beyond class labels via hierarchical regularization
Sungyeon Kim, Boseung Jeong, and Suha Kwak · 2023
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Cross-image-attention for conditional embeddings in deep metric learning
Dmytro Kotovenko, Pingchuan Ma, Timo Milbich, and Björn Ommer · 2023
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Deep factorized metric learning
Chengkun Wang, Wenzhao Zheng, Junlong Li, Jie Zhou, and Jiwen Lu · 2023
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Aim: Adapting image models for efficient video action recognition
Taojiannan Yang, Yi Zhu, Yusheng Xie, Aston Zhang, Chen Chen, and Mu Li · 2023
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Towards improved proxy-based deep metric learning via data-augmented domain adaptation
Li Ren, Chen Chen, Liqiang Wang, and Kien Hua · 2024
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