14.1.11.1 Deep Metric Learning

Chapter Contents (Back)
Metric Learning. Deep Learning.
See also Deep Learning, Deep Nets, DNN.

Liong, V.E., Lu, J., Tan, Y.P., Zhou, J.,
Deep Coupled Metric Learning for Cross-Modal Matching,
MultMed(19), No. 6, June 2017, pp. 1234-1244.
IEEE DOI 1705
Correlation, Kernel, Learning systems, Machine learning, Measurement, Neural networks, Semantics, Coupled learning, cross-modal matching, deep model, metric learning, multimedia retrieval BibRef

Lu, J.W.[Ji-Wen], Hu, J.L.[Jun-Lin], Zhou, J.,
Deep Metric Learning for Visual Understanding: An Overview of Recent Advances,
SPMag(34), No. 6, November 2017, pp. 76-84.
IEEE DOI 1712
Survey, Metric Learning. Euclidean distance, Extraterrestrial measurements, Face recognition, Image classification, Learning systems, Visualization
See also Deep Transfer Metric Learning. BibRef

Gong, Z., Zhong, P., Yu, Y., Hu, W.,
Diversity-Promoting Deep Structural Metric Learning for Remote Sensing Scene Classification,
GeoRS(56), No. 1, January 2018, pp. 371-390.
IEEE DOI 1801
Feature extraction, Machine learning, Measurement, Redundancy, Remote sensing, Training, Convolutional neural network (CNN), scene classification BibRef

Ren, C.X.[Chuan-Xian], Li, J.Z.[Ju-Zheng], Ge, P.F.[Peng-Fei], Xu, X.L.[Xiao-Lin],
Deep metric learning via subtype fuzzy clustering,
PR(90), 2019, pp. 210-219.
Elsevier DOI 1903
Metric learning, Deep networks, Triplet loss, Fuzzy clustering, Online sampling BibRef

Duan, Y., Lu, J., Feng, J., Zhou, J.,
Deep Localized Metric Learning,
CirSysVideo(28), No. 10, October 2018, pp. 2644-2656.
IEEE DOI 1811
Measurement, Visualization, Learning systems, Face recognition, Training, Neural networks, Face, Deep metric learning, visual recognition BibRef

Zhe, X.F.[Xue-Fei], Chen, S.F.[Shi-Feng], Yan, H.[Hong],
Directional statistics-based deep metric learning for image classification and retrieval,
PR(93), 2019, pp. 113-123.
Elsevier DOI 1906
Deep distance metric learning, Directional statistics, Image retrieval, Image similarity learning BibRef

Zheng, Y., Fan, J., Zhang, J., Gao, X.,
Exploiting Related and Unrelated Tasks for Hierarchical Metric Learning and Image Classification,
IP(29), No. 1, 2020, pp. 883-896.
IEEE DOI 1910
Task analysis, Visualization, Measurement, Training, Correlation, Semantics, Deep learning, Hierarchical metric learning, visual tree BibRef

Duan, Y., Lu, J., Zheng, W., Zhou, J.,
Deep Adversarial Metric Learning,
IP(29), 2020, pp. 2037-2051.
IEEE DOI 2001
Measurement, Training, Microstrip, Generators, Learning systems, Visualization, Task analysis, Metric learning, deep learning, multi-metric BibRef

Yun, M.S.[Min-Sub], Nam, W.J.[Woo-Jeoung], Lee, S.W.[Seong-Whan],
Coarse-to-Fine Deep Metric Learning for Remote Sensing Image Retrieval,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link 2001
BibRef

Zhao, H.W.[Hong-Wei], Yuan, L.[Lin], Zhao, H.Y.[Hao-Yu],
Similarity Retention Loss (SRL) Based on Deep Metric Learning for Remote Sensing Image Retrieval,
IJGI(9), No. 2, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Li, Y., Yao, T., Pan, Y., Chao, H., Mei, T.,
Deep Metric Learning With Density Adaptivity,
MultMed(22), No. 5, May 2020, pp. 1285-1297.
IEEE DOI 2005
Measurement, Training, Neural networks, Task analysis, Testing, Image retrieval, Adaptation models, Deep Metric Learning, Image Retrieval BibRef

Yu, J.[Jian], Hu, C.H.[Chang-Hui], Jing, X.Y.[Xiao-Yuan], Feng, Y.J.[Yu-Jian],
Deep metric learning with dynamic margin hard sampling loss for face verification,
SIViP(14), No. 4, June 2020, pp. 791-798.
WWW Link. 2005
BibRef

Feng, Y.J.[Yu-Jian], Wu, F.[Fei], Ji, Y.[Yimu], Jing, X.Y.[Xiao-Yuan], Yu, J.[Jian],
Deep Metric Learning with Triplet-Margin-Center Loss for Sketch Face Recognition,
IEICE(E103-D), No. 11, November 2020, pp. 2394-2397.
WWW Link. 2011
BibRef

Jacob, P.[Pierre], Picard, D.[David], Histace, A.[Aymeric], Klein, E.[Edouard],
DIABLO: Dictionary-based attention block for deep metric learning,
PRL(135), 2020, pp. 99-105.
Elsevier DOI 2006
BibRef
Earlier:
Metric Learning With HORDE: High-Order Regularizer for Deep Embeddings,
ICCV19(6538-6547)
IEEE DOI 2004
BibRef
Earlier:
Efficient Codebook and Factorization for Second Order Representation Learning,
ICIP19(849-853)
IEEE DOI 1910
Deep metric learning, Attention, Dictionary, Representation learning. feature extraction, image representation, image retrieval. learning (artificial intelligence), object recognition, Robustness. deep learning, second-order representation, codebook strategy, metric learning. BibRef

Kang, J.[Jian], Fernández-Beltrán, R.[Rubén], Ye, Z.[Zhen], Tong, X.H.[Xiao-Hua], Ghamisi, P.[Pedram], Plaza, A.[Antonio],
High-Rankness Regularized Semi-Supervised Deep Metric Learning for Remote Sensing Imagery,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Manandhar, D.[Dipu], Bastan, M.[Muhammet], Yap, K.H.[Kim-Hui],
Semantic granularity metric learning for visual search,
JVCIR(72), 2020, pp. 102871.
Elsevier DOI 2010
Deep learnin, Metric learning, Metric loss functions, Semantic similarity, Visual search BibRef

Kim, D.H.[Dae Ha], Song, B.C.[Byung Cheol],
Virtual sample-based deep metric learning using discriminant analysis,
PR(110), 2021, pp. 107643.
Elsevier DOI 2011
Linear discriminant analysis, Deep metric learning, Retrieval task BibRef

Wang, Y.B.[Yue-Bin], Zhang, L.Q.[Li-Qiang], Nie, F.P.[Fei-Ping], Li, X.G.[Xin-Gang], Chen, Z.J.[Zhi-Jun], Wang, F.Q.[Fa-Qiang],
WeGAN: Deep Image Hashing With Weighted Generative Adversarial Networks,
MultMed(22), No. 6, June 2020, pp. 1458-1469.
IEEE DOI 2005
Generative adversarial networks, Deep learning, Uncertainty, Semantics, Task analysis, Linear programming, uncertainties between images and tags BibRef

Cao, Y.[Yun], Wang, Y.B.[Yue-Bin], Peng, J.H.[Jun-Huan], Zhang, L.Q.[Li-Qiang], Xu, L.L.[Lin-Lin], Yan, K.[Kai], Li, L.H.[Li-Hua],
DML-GANR: Deep Metric Learning With Generative Adversarial Network Regularization for High Spatial Resolution Remote Sensing Image Retrieval,
GeoRS(58), No. 12, December 2020, pp. 8888-8904.
IEEE DOI 2012
Small number of samples. Feature extraction, Measurement, Generative adversarial networks, Image retrieval, Generators, Training, deep learning BibRef

Kang, J.[Jian], Fernandez-Beltran, R.[Ruben], Ye, Z.[Zhen], Tong, X.H.[Xiao-Hua], Ghamisi, P.[Pedram], Plaza, A.[Antonio],
Deep Metric Learning Based on Scalable Neighborhood Components for Remote Sensing Scene Characterization,
GeoRS(58), No. 12, December 2020, pp. 8905-8918.
IEEE DOI 2012
Measurement, Semantics, Remote sensing, Feature extraction, Training, Complexity theory, Encoding, Deep learning, remote sensing (RS) scene characterization BibRef

Kang, J.[Jian], Fernandez-Beltran, R.[Ruben], Duan, P.H.[Pu-Hong], Liu, S.C.[Si-Cong], Plaza, A.J.[Antonio J.],
Deep Unsupervised Embedding for Remotely Sensed Images Based on Spatially Augmented Momentum Contrast,
GeoRS(59), No. 3, March 2021, pp. 2598-2610.
IEEE DOI 2103
Measurement, Semantics, Remote sensing, Complexity theory, Feature extraction, Standards, Geography, Deep learning (DL), unsupervised learning BibRef

Dong, Y.[Yanni], Yang, C.[Cong], Zhang, Y.X.[Yu-Xiang],
Deep Metric Learning with Online Hard Mining for Hyperspectral Classification,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Mojoo, J.[Jonathan], Kurita, T.[Takio],
Deep Metric Learning for Multi-Label and Multi-Object Image Retrieval,
IEICE(E104-D), No. 6, June 2021, pp. 873-880.
WWW Link. 2106
BibRef

Zheng, W.Z.[Wen-Zhao], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
Hardness-Aware Deep Metric Learning,
PAMI(43), No. 9, September 2021, pp. 3214-3228.
IEEE DOI 2108
BibRef
Earlier: Add A2: Chen, Z.D.[Zhao-Dong], CVPR19(72-81).
IEEE DOI 2002
Measurement, Training, Training data, Learning systems, Data mining, Geometry, Interpolation, Metric learning, deep learning, hardness-aware learning BibRef

Filax, M.[Marco], Ortmeier, F.[Frank],
On the Influence of Viewpoint Change for Metric Learning,
MVA21(1-4)
DOI Link 2109
Measurement, Visualization, Protocols, Databases, Lighting BibRef

Oi, H.[Hajime], Kawakami, R.[Rei], Nacmura, T.[Takeshi],
Analysis of Evaluation Metrics with the Distance between Positive Pairs and Negative Pairs in Deep Metric Learning,
MVA21(1-5)
DOI Link 2109
Measurement, Deep learning, Histograms, Focusing BibRef

Cheng, Q.M.[Qi-Min], Gan, D.Q.[De-Qiao], Fu, P.[Peng], Huang, H.Y.[Hai-Yan], Zhou, Y.Z.[Yu-Zhuo],
A Novel Ensemble Architecture of Residual Attention-Based Deep Metric Learning for Remote Sensing Image Retrieval,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Liang, C.H.[Chang-Hui], Zhao, W.L.[Wan-Lei], Chen, R.Q.[Run-Qing],
Dynamic sampling for deep metric learning,
PRL(150), 2021, pp. 49-56.
Elsevier DOI 2109
Deep metric learning, Training sample mining, Fashion search BibRef

Kang, J.[Jian], Fernandez-Beltran, R.[Ruben], Duan, P.[Puhong], Kang, X.D.[Xu-Dong], Plaza, A.J.[Antonio J.],
Robust Normalized Softmax Loss for Deep Metric Learning-Based Characterization of Remote Sensing Images With Label Noise,
GeoRS(59), No. 10, October 2021, pp. 8798-8811.
IEEE DOI 2109
Measurement, Semantics, Annotations, Feature extraction, Prototypes, Noise measurement, Visualization, Deep metric learning, remote sensing (RS) BibRef

Huang, K.K.[Ke-Kun], Ren, C.X.[Chuan-Xian], Liu, H.[Hui], Lai, Z.R.[Zhao-Rong], Yu, Y.F.[Yu-Feng], Dai, D.Q.[Dao-Qing],
Hyperspectral image classification via discriminative convolutional neural network with an improved triplet loss,
PR(112), 2021, pp. 107744.
Elsevier DOI 2102
Hyper-spectral image classification, Convolutional neural network, Triplet loss, Metric learning BibRef

Milbich, T.[Timo], Roth, K.[Karsten], Brattoli, B.[Biagio], Ommer, B.[Björn],
Sharing Matters for Generalization in Deep Metric Learning,
PAMI(44), No. 1, January 2022, pp. 416-427.
IEEE DOI 2112
Training, Measurement, Task analysis, Standards, Training data, Image color analysis, Encoding, Deep metric learning, deep learning BibRef

Kim, D.H.[Dae Ha], Song, B.C.[Byung Cheol],
Deep Metric Learning With Manifold Class Variability Analysis,
MultMed(24), 2022, pp. 3533-3544.
IEEE DOI 2207
Measurement, Manifolds, Task analysis, Tools, Probability distribution, Neural networks, linear discriminant analysis BibRef

Wang, Y.F.[Yi-Fan], Liu, P.P.[Ping-Ping], Lang, Y.J.[Yi-Jun], Zhou, Q.Z.[Qiu-Zhan], Shan, X.[Xue],
Learnable dynamic margin in deep metric learning,
PR(132), 2022, pp. 108961.
Elsevier DOI 2209
Deep metric learning, Proxy-based loss, Adaptive margin, Image retrieval, Fine-grained images BibRef

Sanakoyeu, A.[Artsiom], Ma, P.C.[Ping-Chuan], Tschernezki, V.[Vadim], Ommer, B.[Björn],
Improving Deep Metric Learning by Divide and Conquer,
PAMI(44), No. 11, November 2022, pp. 8306-8320.
IEEE DOI 2210
Measurement, Training, Training data, Visualization, Prototypes, Learning systems, Image retrieval, Deep metric learning, deep learning BibRef

Xu, X.[Xinyi], Wang, Z.Y.[Zheng-Yang], Deng, C.[Cheng], Yuan, H.[Hao], Ji, S.W.[Shui-Wang],
Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping,
PAMI(45), No. 1, January 2023, pp. 1189-1200.
IEEE DOI 2212
Measurement, Training, Semantics, Testing, Task analysis, Convolutional neural networks, Tensors, Deep metric learning, invariance BibRef

Yan, J.[Jiexi], Luo, L.[Lei], Deng, C.[Cheng], Huang, H.[Heng],
Adaptive Hierarchical Similarity Metric Learning With Noisy Labels,
IP(32), 2023, pp. 1245-1256.
IEEE DOI 2302
Noise measurement, Measurement, Adaptation models, Geometry, Training, Robustness, Task analysis, Deep metric learning, contrastive augmentation BibRef

Li, X.X.[Xiao-Xu], Yang, X.C.[Xiao-Chen], Ma, Z.Y.[Zhan-Yu], Xue, J.H.[Jing-Hao],
Deep metric learning for few-shot image classification: A Review of recent developments,
PR(138), 2023, pp. 109381.
Elsevier DOI 2303
Few-shot learning, Metric learning, Image classification, Deep neural networks BibRef

Li, P.D.[Pan-Deng], Xie, H.T.[Hong-Tao], Jiang, Y.[Yan], Ge, J.N.[Jian-Nan], Zhang, Y.D.[Yong-Dong],
Neighborhood-Adaptive Multi-Cluster Ranking for Deep Metric Learning,
CirSysVideo(33), No. 4, April 2023, pp. 1952-1965.
IEEE DOI 2304
Training, Measurement, Uncertainty, Manifolds, Indexing, Task analysis, Probabilistic logic, Neighborhood-adaptive, self-supervised learning BibRef

Kan, S.C.[Shi-Chao], He, Z.Q.[Zhi-Quan], Cen, Y.G.[Yi-Gang], Li, Y.[Yang], Mladenovic, V.[Vladimir], He, Z.H.[Zhi-Hai],
Contrastive Bayesian Analysis for Deep Metric Learning,
PAMI(45), No. 6, June 2023, pp. 7220-7238.
IEEE DOI 2305
Measurement, Bayes methods, Training, Semantics, Information science, Analytical models, Task analysis, Bayesian analysis, similarity and distance learning BibRef

Zheng, W.Z.[Wen-Zhao], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
Deep Metric Learning With Adaptively Composite Dynamic Constraints,
PAMI(45), No. 7, July 2023, pp. 8265-8283.
IEEE DOI 2306
Measurement, Training, Generators, Adaptation models, Task analysis, Learning systems, Vehicle dynamics, Metric learning, deep learning, dynamic constraints BibRef

Boutaleb, Y.[Yasser], Soladie, C.[Catherine], Duong, N.D.[Nam-Duong], Kacete, A.[Amine], Royan, J.[Jérôme], Seguier, R.[Renaud],
MES-Loss: Mutually equidistant separation metric learning loss function,
PRL(172), 2023, pp. 58-64.
Elsevier DOI 2309
Metric learning, Deep clustering, Image-retrieval BibRef

Wang, Z.[Zheng], Gao, Z.W.[Zhen-Wei], Wang, G.Q.[Guo-Qing], Yang, Y.[Yang], Shen, H.T.[Heng Tao],
Visual Embedding Augmentation in Fourier Domain for Deep Metric Learning,
CirSysVideo(33), No. 10, October 2023, pp. 5538-5548.
IEEE DOI 2310
BibRef

Saeki, S.[Shozo], Kawahara, M.[Minoru], Aman, H.[Hirohisa],
Multi proxy anchor family loss for several types of gradients,
CVIU(229), 2023, pp. 103654.
Elsevier DOI 2303
Metric learning, Deep metric learning, Data mining, Image retrieval, Feature extraction BibRef

Wang, J.[Jian], Li, X.Y.[Xin-Yue], Zhang, Z.C.[Zhi-Chao], Song, W.[Wei], Guo, W.Q.[Wei-Qi],
Ranked Similarity Weighting and Top-nk Sampling in Deep Metric Learning,
MultMed(25), 2023, pp. 7726-7735.
IEEE DOI 2312
BibRef

Fu, Z.R.[Zhe-Ren], Mao, Z.D.[Zhen-Dong], Hu, B.[Bo], Liu, A.A.[An-An], Zhang, Y.D.[Yong-Dong],
Intra-Class Adaptive Augmentation With Neighbor Correction for Deep Metric Learning,
MultMed(25), 2023, pp. 7758-7771.
IEEE DOI 2312
BibRef


Yan, J.[Jiexi], Yin, Z.H.[Zhi-Hui], Yang, E.[Erkun], Yang, Y.H.[Yan-Hua], Huang, H.[Heng],
Learning with Diversity: Self-Expanded Equalization for Better Generalized Deep Metric Learning,
ICCV23(19308-19317)
IEEE DOI 2401
BibRef

Yang, B.[Bailin], Sun, H.Q.[Hao-Qiang], Li, F.W.B.[Frederick W. B.], Chen, Z.[Zheng], Cai, J.[Jianlu], Song, C.[Chao],
HSE: Hybrid Species Embedding for Deep Metric Learning,
ICCV23(11013-11023)
IEEE DOI 2401
BibRef

Kotovenko, D.[Dmytro], Ma, P.C.[Ping-Chuan], Milbich, T.[Timo], Ommer, B.[Björn],
Cross-Image-Attention for Conditional Embeddings in Deep Metric Learning,
CVPR23(11070-11081)
IEEE DOI 2309
BibRef

Zhuang, F.[Furen], Moulin, P.[Pierre],
Deep Semi-Supervised Metric Learning with Mixed Label Propagation,
CVPR23(3429-3438)
IEEE DOI 2309
BibRef

Wang, C.[Chengkun], Zheng, W.Z.[Wen-Zhao], Li, J.L.[Jun-Long], Zhou, J.[Jie], Lu, J.W.[Ji-Wen],
Deep Factorized Metric Learning,
CVPR23(7672-7682)
IEEE DOI 2309
BibRef

Hunt, R.[Roberta], Pedersen, K.S.[Kim Steenstrup],
Rove-tree-11: The Not-so-wild Rover a Hierarchically Structured Image Dataset for Deep Metric Learning Research,
ACCV22(V:425-441).
Springer DOI 2307
BibRef

Suma, P.[Pavel], Tolias, G.[Giorgos],
Large-to-small Image Resolution Asymmetry in Deep Metric Learning,
WACV23(1451-1460)
IEEE DOI 2302
Measurement, Knowledge engineering, Image resolution, Databases, Image retrieval, Estimation BibRef

Kobs, K.[Konstantin], Steininger, M.[Michael], Hotho, A.[Andreas],
InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images,
WACV23(1063-1072)
IEEE DOI 2302
Measurement, Training, Dimensionality reduction, Natural languages, Image retrieval, Training data, Image representation, visual reasoning. BibRef

Liu, L.Z.[Li-Zhao], Huang, S.X.[Shang-Xin], Zhuang, Z.W.[Zhuang-Wei], Yang, R.[Ran], Tan, M.K.[Ming-Kui], Wang, Y.[Yaowei],
DAS: Densely-Anchored Sampling for Deep Metric Learning,
ECCV22(XXVI:399-417).
Springer DOI 2211
BibRef

Lim, J.[Jongin], Yun, S.[Sangdoo], Park, S.[Seulki], Choi, J.Y.[Jin Young],
Hypergraph-Induced Semantic Tuplet Loss for Deep Metric Learning,
CVPR22(212-222)
IEEE DOI 2210
Measurement, Representation learning, Visualization, Computational modeling, Semantics, Neural networks, Transfer/low-shot/long-tail learning BibRef

Phan, N.[Nguyen], Tran, S.[Sen], Huy, T.D.[Ta Duc], Duong, S.T.M.[Soan T. M.], Nguyen, C.D.T.[Chanh D. Tr.], Bui, T.[Trung], Truong, S.Q.H.[Steven Q.H.],
Adaptive Proxy Anchor Loss for Deep Metric Learning,
ICIP22(1781-1785)
IEEE DOI 2211
Measurement, Training, Learning systems, Neural networks, Image retrieval, Sampling methods, Robustness, adaptive margin BibRef

Buris, L.H.[Luiz H.], Pedronette, D.C.G.[Daniel C. G.], Papa, J.P.[Joao P.], Almeida, J.[Jurandy], Carneiro, G.[Gustavo], Faria, F.A.[Fabio A.],
Mixup-Based Deep Metric Learning Approaches for Incomplete Supervision,
ICIP22(2581-2585)
IEEE DOI 2211
Training, Sensitivity, Semisupervised learning, Agriculture, Security, Task analysis, mixup, deep metric learning, deep learning, incomplete supervision BibRef

Jacob, P.[Pierre], Picard, D.[David], Histace, A.[Aymeric],
Improving Deep Metric Learning with Virtual Classes and Examples Mining,
ICIP22(2696-2700)
IEEE DOI 2211
Training, Measurement, Manifolds, Prototypes, Generators, image retrieval, metric learning, example mining, virtual classes, example generation BibRef

Gonzalez-Zapata, J.[Jorge], Reyes-Amezcua, I.[Iván], Flores-Araiza, D.[Daniel], Mendez-Ruiz, M.[Mauricio], Ochoa-Ruiz, G.[Gilberto], Mendez-Vazquez, A.[Andres],
Guided Deep Metric Learning,
LXCV22(1480-1488)
IEEE DOI 2210
Measurement, Manifolds, Training, Analytical models, Adaptation models, Visualization, Computer architecture BibRef

Roth, K.[Karsten], Vinyals, O.[Oriol], Akata, Z.[Zeynep],
Integrating Language Guidance into Vision-based Deep Metric Learning,
CVPR22(16156-16168)
IEEE DOI 2210
Training, Learning systems, Visualization, Semantics, Benchmark testing, Extraterrestrial measurements, BibRef

Zhou, M.[Mo], Patel, V.M.[Vishal M.],
Enhancing Adversarial Robustness for Deep Metric Learning,
CVPR22(15304-15313)
IEEE DOI 2210
Training, Measurement, Computational modeling, Robustness, Pattern recognition, Security, Adversarial attack and defense, retrieval BibRef

Kirchhof, M.[Michael], Roth, K.[Karsten], Akata, Z.[Zeynep], Kasneci, E.[Enkelejda],
A Non-isotropic Probabilistic Take on Proxy-based Deep Metric Learning,
ECCV22(XXVI:435-454).
Springer DOI 2211
BibRef

Roth, K.[Karsten], Vinyals, O.[Oriol], Akata, Z.[Zeynep],
Non-isotropy Regularization for Proxy-based Deep Metric Learning,
CVPR22(7410-7420)
IEEE DOI 2210
Codes, Face recognition, Semantics, Refining, Benchmark testing, Drives, Recognition: detection, categorization, retrieval, Transfer/low-shot/long-tail learning BibRef

Ko, B.[Byungsoo], Gu, G.[Geonmo], Kim, H.G.[Han-Gyu],
Learning with Memory-based Virtual Classes for Deep Metric Learning,
ICCV21(11772-11781)
IEEE DOI 2203
Training, Visualization, Codes, Training data, Benchmark testing, Extraterrestrial measurements, Image and video retrieval, Representation learning BibRef

Zheng, W.Z.[Wen-Zhao], Zhang, B.[Borui], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
Deep Relational Metric Learning,
ICCV21(12045-12054)
IEEE DOI 2203
Measurement, Learning systems, Point cloud compression, Adaptation models, Correlation, Image and video retrieval, Representation learning BibRef

Zhao, W.L.[Wen-Liang], Rao, Y.M.[Yong-Ming], Wang, Z.[Ziyi], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
Towards Interpretable Deep Metric Learning with Structural Matching,
ICCV21(9867-9876)
IEEE DOI 2203
Measurement, Learning systems, Visualization, Computational modeling, Surveillance, Neural networks, BibRef

Dai, M.Y.[Meng-Yu], Hang, H.B.[Hai-Bin],
Manifold Matching via Deep Metric Learning for Generative Modeling,
ICCV21(6567-6577)
IEEE DOI 2203
Measurement, Manifolds, Training, Visualization, Shape, Computational modeling, Supervised learning, Image and video synthesis BibRef

Vasudeva, B.[Bhavya], Deora, P.[Puneesh], Bhattacharya, S.[Saumik], Pal, U.[Umapada], Chanda, S.[Sukalpa],
LoOp: Looking for Optimal Hard Negative Embeddings for Deep Metric Learning,
ICCV21(10614-10623)
IEEE DOI 2203
Measurement, Training, Visualization, Image retrieval, Computational efficiency, Complexity theory, Recognition and classification BibRef

Cen, J.[Jun], Yun, P.[Peng], Cai, J.[Junhao], Wang, M.Y.[Michael Yu], Liu, M.[Ming],
Deep Metric Learning for Open World Semantic Segmentation,
ICCV21(15313-15322)
IEEE DOI 2203
Measurement, Learning systems, Knowledge engineering, Deep learning, Annotations, Semantics, Knowledge based systems, Vision applications and systems BibRef

Ebrahimpour, M.K.[Mohammad K.], Qian, G.[Gang], Beach, A.[Allison],
Multi-Head Deep Metric Learning Using Global and Local Representations,
WACV22(1340-1349)
IEEE DOI 2202
Training, Measurement, Computational modeling, Semantics, Benchmark testing, Data models, Deep Learning Object Detection/Recognition/Categorization BibRef

Zhu, M.[Min], Liu, B.D.[Bao-Di], Liu, W.F.[Wei-Feng], Zhang, K.[Kai], Li, Y.[Ye], Lu, X.P.[Xiao-Ping],
Affine Non-Negative Collaborative Representation for Deep Metric Learning,
ICIP21(774-778)
IEEE DOI 2201
Measurement, Learning systems, Image processing, Collaboration, Benchmark testing, Robustness, Deep metric learning, meta-learning, hard mining BibRef

Kan, S.C.[Shi-Chao], Cen, Y.G.[Yi-Gang], Li, Y.[Yang], Mladenovic, V.[Vladimir], He, Z.H.[Zhi-Hai],
Relative Order Analysis and Optimization for Unsupervised Deep Metric Learning,
CVPR21(13994-14003)
IEEE DOI 2111
Measurement, Training, Deep learning, Error analysis, Image retrieval, Pattern recognition BibRef

Zheng, W.Z.[Wen-Zhao], Wang, C.K.[Cheng-Kun], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
Deep Compositional Metric Learning,
CVPR21(9316-9325)
IEEE DOI 2111
Measurement, Training, Learning systems, Pattern recognition, Relays BibRef

Roig, C.[Carlos], Varas, D.[David], Masuda, I.[Issey], Riveiro, J.C.[Juan Carlos], Bou-Balust, E.[Elisenda],
Generalized Local Attention Pooling for Deep Metric Learning,
ICPR21(9951-9958)
IEEE DOI 2105
Measurement, Dimensionality reduction, Neural networks, Semantics, Memory management, Image representation, Feature extraction BibRef

Ren, L.[Li], Li, K.[Kai], Wang, L.Q.[Li-Qiang], Hua, K.[Kien],
Beyond the Deep Metric Learning: Enhance the Cross-Modal Matching with Adversarial Discriminative Domain Regularization,
ICPR21(10165-10172)
IEEE DOI 2105
Measurement, Location awareness, Visualization, Semantics, Benchmark testing, Information retrieval, Natural language processing BibRef

Li, Y.[Yang], Kan, S.C.[Shi-Chao], He, Z.H.[Zhi-Hai],
Unsupervised Deep Metric Learning with Transformed Attention Consistency and Contrastive Clustering Loss,
ECCV20(XI:141-157).
Springer DOI 2011
BibRef

Qi, Q.[Qi], Yan, Y.[Yan], Wu, Z.X.[Zi-Xuan], Wang, X.Y.[Xiao-Yu], Yang, T.B.[Tian-Bao],
A Simple and Effective Framework for Pairwise Deep Metric Learning,
ECCV20(XXVII:375-391).
Springer DOI 2011
BibRef

Zhu, Y.[Yuke], Bai, Y.[Yan], Wei, Y.C.[Yi-Chen],
Spherical Feature Transform for Deep Metric Learning,
ECCV20(XIX:420-436).
Springer DOI 2011
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Elezi, I.[Ismail], Vascon, S.[Sebastiano], Torcinovich, A.[Alessandro], Pelillo, M.[Marcello], Leal-Taixé, L.[Laura],
The Group Loss for Deep Metric Learning,
ECCV20(VII:277-294).
Springer DOI 2011
BibRef

Milbich, T.[Timo], Roth, K.[Karsten], Bharadhwaj, H.[Homanga], Sinha, S.[Samarth], Bengio, Y.[Yoshua], Ommer, B.[Björn], Cohen, J.P.[Joseph Paul],
Diva: Diverse Visual Feature Aggregation for Deep Metric Learning,
ECCV20(VIII:590-607).
Springer DOI 2011
BibRef

Mohan, D.D., Sankaran, N., Fedorishin, D., Setlur, S., Govindaraju, V.,
Moving in the Right Direction: A Regularization for Deep Metric Learning,
CVPR20(14579-14587)
IEEE DOI 2008
Optimization, Extraterrestrial measurements, Training, Learning systems, Feature extraction, Force BibRef

Kim, S., Kim, D., Cho, M., Kwak, S.,
Proxy Anchor Loss for Deep Metric Learning,
CVPR20(3235-3244)
IEEE DOI 2008
Training, Convergence, Measurement, Complexity theory, Standards, Training data, Reliability BibRef

Zheng, W., Lu, J., Zhou, J.,
Deep Metric Learning via Adaptive Learnable Assessment,
CVPR20(2957-2966)
IEEE DOI 2008
Measurement, Training, Adaptation models, Task analysis, Learning systems, Complexity theory, Market research BibRef

Ko, B., Gu, G.,
Embedding Expansion: Augmentation in Embedding Space for Deep Metric Learning,
CVPR20(7253-7262)
IEEE DOI 2008
Measurement, Training, Image retrieval, Optimization, Semantics, Interpolation BibRef

Chen, G., Zhang, T., Lu, J., Zhou, J.,
Deep Meta Metric Learning,
ICCV19(9546-9555)
IEEE DOI 2004
face recognition, image classification, image sampling, learning (artificial intelligence), set theory, softmax, Face BibRef

Xu, X.[Xinyi], Yang, Y.H.[Yan-Hua], Deng, C.[Cheng], Zheng, F.[Feng],
Deep Asymmetric Metric Learning via Rich Relationship Mining,
CVPR19(4071-4080).
IEEE DOI 2002
BibRef

Wang, X.[Xun], Han, X.T.[Xin-Tong], Huang, W.L.[Wei-Lin], Dong, D.[Dengke], Scott, M.R.[Matthew R.],
Multi-Similarity Loss With General Pair Weighting for Deep Metric Learning,
CVPR19(5017-5025).
IEEE DOI 2002
BibRef

Wang, X.S.[Xin-Shao], Hua, Y.[Yang], Kodirov, E.[Elyor], Robertson, N.M.[Neil M.],
Ranked List Loss for Deep Metric Learning,
PAMI(44), No. 9, September 2022, pp. 5414-5429.
IEEE DOI 2208
Measurement, Training, Shape, Image retrieval, Extraterrestrial measurements, Task analysis, Pattern analysis, information retrieval BibRef
Earlier: Add: Hu, G.S.[Guo-Sheng], Garnier, R.[Romain], CVPR19(5202-5211).
IEEE DOI 2002
BibRef

Suh, Y.M.[Yu-Min], Han, B.H.[Bo-Hyung], Kim, W.S.[Won-Sik], Lee, K.M.[Kyoung Mu],
Stochastic Class-Based Hard Example Mining for Deep Metric Learning,
CVPR19(7244-7252).
IEEE DOI 2002
BibRef

Landrieu, L.[Loic], Boussaha, M.[Mohamed],
Point Cloud Oversegmentation With Graph-Structured Deep Metric Learning,
CVPR19(7432-7441).
IEEE DOI 2002
BibRef

Cakir, F.[Fatih], He, K.[Kun], Xia, X.[Xide], Kulis, B.[Brian], Sclaroff, S.[Stan],
Deep Metric Learning to Rank,
CVPR19(1861-1870).
IEEE DOI 2002
BibRef

Kim, S.Y.[Sung-Yeon], Seo, M.[Minkyo], Laptev, I.[Ivan], Cho, M.[Minsu], Kwak, S.[Suha],
Deep Metric Learning Beyond Binary Supervision,
CVPR19(2283-2292).
IEEE DOI 2002
BibRef

Waltner, G., Opitz, M., Possegger, H., Bischof, H.,
HiBsteR: Hierarchical Boosted Deep Metric Learning for Image Retrieval,
WACV19(599-608)
IEEE DOI 1904
image representation, image retrieval, learning (artificial intelligence), pattern clustering, Standards BibRef

Duan, Y., Zheng, W., Lin, X., Lu, J., Zhou, J.,
Deep Adversarial Metric Learning,
CVPR18(2780-2789)
IEEE DOI 1812
Measurement, Microstrip, Generators, Learning systems, Training, Visualization, Task analysis BibRef

Sun, P.[Peng], Tang, W.Z.[Wen-Zhong], Bai, X.[Xiao],
Learning Deep Embeddings via Margin-Based Discriminate Loss,
SSSPR18(107-115).
Springer DOI 1810
BibRef

Xuan, H.[Hong], Souvenir, R.[Richard], Pless, R.[Robert],
Deep Randomized Ensembles for Metric Learning,
ECCV18(XVI: 751-762).
Springer DOI 1810
BibRef

Kim, W.S.[Won-Sik], Goyal, B.[Bhavya], Chawla, K.[Kunal], Lee, J.M.[Jung-Min], Kwon, K.[Keunjoo],
Attention-Based Ensemble for Deep Metric Learning,
ECCV18(I: 760-777).
Springer DOI 1810
BibRef

Lin, X.D.[Xu-Dong], Duan, Y.Q.[Yue-Qi], Dong, Q.Y.[Qi-Yuan], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
Deep Variational Metric Learning,
ECCV18(XV: 714-729).
Springer DOI 1810
BibRef

Meyer, B.J., Harwood, B., Drummond, T.W.,
Deep Metric Learning and Image Classification with Nearest Neighbour Gaussian Kernels,
ICIP18(151-155)
IEEE DOI 1809
Training, Measurement, Kernel, Convolutional neural networks, Task analysis, Robots, Metric Learning, Deep Learning, Gaussian Kernel BibRef

Li, D., Tang, J., Tian, Y., Ju, X.,
Multi-view deep metric learning for image classification,
ICIP17(4142-4146)
IEEE DOI 1803
Automobiles, Data mining, Feature extraction, Kernel, Measurement, Optimization, Training, Deep learning, Metric learning, Neural network BibRef

Wang, J., Zhou, F., Wen, S., Liu, X., Lin, Y.,
Deep Metric Learning with Angular Loss,
ICCV17(2612-2620)
IEEE DOI 1802
feature extraction, image retrieval, learning (artificial intelligence), optimisation, angular loss, Training data BibRef

Harwood, B.[Ben], Vijay Kumar, B.G., Carneiro, G.[Gustavo], Reid, I.D.[Ian D.], Drummond, T.W.[Tom W.],
Smart Mining for Deep Metric Learning,
ICCV17(2840-2848)
IEEE DOI 1802
convergence of numerical methods, data mining, learning (artificial intelligence), deep metric learning, Training BibRef

Rahman, S.[Saimunur], Koniusz, P.[Piotr], Wang, L.[Lei], Zhou, L.P.[Lu-Ping], Moghadam, P.[Peyman], Sun, C.M.[Chang-Ming],
Learning Partial Correlation based Deep Visual Representation for Image Classification,
CVPR23(6231-6240)
IEEE DOI 2309
BibRef

Engin, M.[Melih], Wang, L.[Lei], Zhou, L.P.[Lu-Ping], Liu, X.W.[Xin-Wang],
DeepKSPD: Learning Kernel-Matrix-Based SPD Representation For Fine-Grained Image Recognition,
ECCV18(II: 629-645).
Springer DOI 1810
BibRef

Zhou, L.P.[Lu-Ping], Wang, L.[Lei], Zhang, J.J.[Jian-Jia], Shi, Y.H.[Ying-Huan], Gao, Y.[Yang],
Revisiting Metric Learning for SPD Matrix Based Visual Representation,
CVPR17(7111-7119)
IEEE DOI 1711
Covariance matrices, Eigenvalues and eigenfunctions, Euclidean distance, Learning systems, Visualization BibRef

Song, H.O., Jegelka, S., Rathod, V., Murphy, K.,
Deep Metric Learning via Facility Location,
CVPR17(2206-2214)
IEEE DOI 1711
Euclidean distance, Feature extraction, Graphics processing units, Mutual information, Training, data BibRef

Song, H.O., Xiang, Y., Jegelka, S.[Stefanie], Savarese, S.[Silvio],
Deep Metric Learning via Lifted Structured Feature Embedding,
CVPR16(4004-4012)
IEEE DOI 1612
Stanford Online Products. Dataset, Products. BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Multi-View Learning, Transfer from Other View .


Last update:Jan 30, 2024 at 20:33:16