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
Zhao, W.L.[Wen-Liang],
Rao, Y.M.[Yong-Ming],
Zhou, J.[Jie],
Lu, J.W.[Ji-Wen],
DIML: Deep Interpretable Metric Learning via Structural Matching,
PAMI(46), No. 4, April 2024, pp. 2518-2532.
IEEE DOI
2403
Measurement, Transformers, Learning systems, Visualization,
Computer architecture, Task analysis, Computational modeling,
visual recognition
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
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
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
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Yun, P.[Peng],
Cai, J.H.[Jun-Hao],
Wang, M.Y.[Michael Yu],
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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
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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
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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
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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
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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
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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
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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
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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
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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
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CVPR19(5017-5025).
IEEE DOI
2002
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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
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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
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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
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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
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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
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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 .