| Distance metric learning for large margin nearest neighbor classification |
K. Q. Weinberger, J. et al. |
2006 |
NeurIPS |
PDF |
| FaceNet: A unified embedding for face recognition and clustering |
Schroff, F. et al. |
2015 |
CVPR |
PDF |
| Deepfashion: Powering robust clothes recognition and retrieval with rich annotations |
Liu, Z. et al. |
2016 |
CVPR |
PDF |
| Deep metric learning via lifted structured feature embedding |
Song, H. et al. |
2016 |
CVPR |
PDF |
| Deep Metric Learning via Lifted Structured Feature Embedding |
Song, H. O. et al. |
2016 |
CVPR |
PDF |
| No Fuss Distance Metric Learning Using Proxies |
Movshovitz-Attias, Y. et al. |
2017 |
ICCV |
PDF |
| SphereFace: Deep Hypersphere Embedding for Face Recognition |
Liu, W. et al. |
2017 |
CVPR |
PDF |
| Sampling Matters in Deep Embedding Learning |
Wu, C.-Y. et al. |
2017 |
ICCV |
PDF |
| BIER: Online Gradient Boosting |
Opitz, M. et al. |
2017 |
ICCV |
PDF |
| CosFace: Large Margin Cosine Loss for Deep Face Recognition |
Wang, H. et al. |
2018 |
CVPR |
PDF |
| ArcFace: Additive Angular Margin Loss for Deep Face Recognition |
Deng, J. et al. |
2019 |
CVPR |
PDF |
| Classification is a strong baseline for deep metric learning |
Zhai, A. and Wu, H. |
2019 |
BMVC |
PDF |
| SoftTriple Loss: Deep Metric Learning Without Triplet Sampling |
Qian, Q. et al. |
2019 |
ICCV |
PDF |
| Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning |
Wang, X. et al. |
2019 |
CVPR |
PDF |
| Divide and Conquer the Embedding Space for Metric Learning |
Sanakoyeu, A. et al. |
2019 |
CVPR |
PDF |
| MIC: Mining Interclass Characteristics for Improved Metric Learning |
Roth, K. et al. |
2019 |
ICCV |
PDF |
| Proxy Anchor Loss for Deep Metric Learning |
Kim, S. et al. |
2020 |
CVPR |
PDF |
| Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies |
Zhu, Y. et al. |
2020 |
NeurIPS |
PDF |
| ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis |
Teh, E. W. et al. |
2020 |
ECCV |
PDF |
| A Metric Learning Reality Check |
Musgrave, K. et al. |
2020 |
ECCV |
PDF |
| Revisiting Training Strategies and Generalization Performance in Deep Metric Learning |
Roth, K. et al. |
2020 |
ICML |
PDF |
| Proxy Anchor Loss for Deep Metric Learning |
Kim, S. et al. |
2020 |
CVPR |
PDF |
| The Group Loss for Deep Metric Learning |
Elezi, I. et al. |
2020 |
ECCV 2020 |
PDF |
| PADS: Policy-Adapted Sampling for Visual Similarity Learning |
Roth, K. et al. |
2020 |
CVPR |
PDF |
| Sharing Matters for Generalization in Deep Metric Learning |
Milbich, T. et al. |
2020 |
TPAMI |
PDF |
| DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning |
Milbich, T. et al. |
2020 |
ECCV |
PDF |
| Learning Intra-Batch Connections for Deep Metric Learning |
Seidenschwarz, J. et al. |
2021 |
ICML |
PDF |
| Robust and Decomposable Average Precision for Image Retrieval |
Ramzi, E. et al. |
2021 |
NeurIPS |
PDF |
| Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning |
Milbich, T. et al. |
2021 |
NeuRIPS |
PDF |
| Improving deep metric learning by divide and conquer |
Sanakoyeu, A. et al. |
2021 |
CVPR |
PDF |
| S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning |
Roth, K. et al. |
2021 |
ICML |
PDF |
| The Group Loss++: A deeper look into group loss for deep metric learning |
Elezi, I. et al. |
2022/03 |
PAMI |
PDF |
| Recall@k Surrogate Loss with Large Batches and Similarity Mixup |
Patel, Y. et al. |
2022 |
CVPR |
PDF |
| Hyperbolic Vision Transformers: Combining Improvements in Metric Learning |
Ermolov, A.et al. |
2022 |
CVPR |
PDF |