👏 Survey of Deep Metric Learning

Traditionally, they have defined metrics in a variety of ways, including pairwise distance, similarity, and probability distribution.

💡 I hope many researchers will be able to do good research thanks to this repository.

🔔 Updated frequently.

Pairwise cost methods
Distribution or other variant methods
Probabilistic methods
Boost-like methods
Unsupervised methods
Applications
Related works
- Neurips
- ICLR
- ICML
- ECCV
- ICIP
- Others
Study materials
Challenges

1️⃣ Pairwise cost methods

Dimensionality Reduction by Learning an Invariant Mapping (Contrastive) (CVPR 2006) [Paper][Caffe][Tensorflow][Keras][Pytorch1][Pytorch2]
From Point to Set: Extend the Learning of Distance Metrics (ICCV 2013) [Paper]
FaceNet: A Unified Embedding for Face Recognition and Clustering (Triplet) (CVPR 2015) [Paper][Tensorflow][Pytorch]
Deep Metric Learning via Lifted Structured Feature Embedding (LSSS) (CVPR 2016) [Paper][Chainer][Caffe][Pytorch1][Pytorch2][Tensorflow]
Improved Deep Metric Learning with Multi-class N-pair Loss Objective (N-pair) (NIPS 2016) [Paper][Pytorch][Chainer]
Beyond triplet loss: a deep quadruplet network for person re-identification (Quadruplet) (CVPR 2017) [Paper]
Deep Metric Learning via Facility Location (CVPR 2017) [Paper][Tensorflow]
No Fuss Distance Metric Learning using Proxies (Proxy NCA) (ICCV 2017) [Paper][Pytorch1][Pytorch2][Chainer]
Sampling Matters in Deep Embedding Learning (Margin) (ICCV 2017) [Paper][Pytorch][TensorFlow][MXNet]
Deep Metric Learning with Angular Loss (Angular) (CVPR 2017) [Paper][Tensorflow][Chainer]
Deep Metric Learning by Online Soft Mining and Class-Aware Attention (AAAI 2019) [Paper]
Deep Metric Learning Beyond Binary Supervision (Log_ratio) (CVPR 2019) [Paper][Pytorch]
A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning (CVPR 2019) [Paper]
Ranked List Loss for Deep Metric Learning (RLL) (CVPR 2019) [Paper][Matlab]
Deep Metric Learning to Rank (FastAP) (CVPR 2019) [Paper][Matlab]
SoftTriple Loss: Deep Metric Learning Without Triplet Sampling (Soft-Trip) (ICCV 2019) [Paper][Tensorflow]
Curvilinear Distance Metric Learning (CDML) (Neurips 2019) [Paper]
Proxy Anchor Loss for Deep Metric Learning (Proxy-Anchor) (CVPR 2020) [Paper] [Pytorch]
Embedding Expansion: Augmentation in Embedding Space for Deep Metric Learning (EE) (CVPR 2020) [Paper] [Mxnet]
ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis (Proxy++) (ECCV 2020) [Paper][PyTorch]
Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies (ProxyGML) (NeurIPS 2020) [Paper][PyTorch]
Deep Metric Learning with Spherical Embedding (NeurIPS 2020) [Paper]

2️⃣ Distribution or other variant methods

Image Set Classification Using Holistic Multiple Order Statistics Features and Localized Multi-Kernel Metric Learning (ICCV 2013) [Paper]
Deep Metric Learning for Practical Person Re-Identification (Binomial deviance) (ICPR 2014) [Paper][Tensorflow][Pytorch]
Learning Deep Embeddings with Histogram Loss (Histogram) (NIPS 2016) [Paper][Tensorflow][Pytorch][Caffe]
Learning Deep Disentangled Embeddings With the F-Statistic Loss (F-stat) (NIPS 2018) [Paper][Tensorflow]
Deep Metric Learning via Subtype Fuzzy Clustering (SCDM) (PR 2020) [Paper]
Deep Asymmetric Metric Learning via Rich Relationship Mining (DAML) (CVPR 2019) [Paper]
Hardness-Aware Deep Metric Learning (HDML) (CVPR 2019) [Paper][Tensorflow]
Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning (DSML) (CVPR 2019) [Paper]
Multi-similarity Loss with General Pair Weighting for Deep Metric Learning (MSLoss) (CVPR 2019) [Paper][Pytorch]
Deep Meta Metric Learning (DMML) (ICCV 2019) [Paper][Pytorch]
Symmetrical Synthesis for Deep Metric Learning (Symm) (AAAI 2020) [Paper] [Tensorflow]
Optimizing Rank-based Metrics with Blackbox Differentiation (RaMBO) (CVPR 2020) [Paper]
Cross-Batch Memory for Embedding Learning (CVPR 2020) [Paper] [Pytorch]
Distance Metric Learning with Joint Representation Diversification (JRD) (ICML 2020) [Paper][Pytorch]
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning (ICML 2020) [Paper][PyTorch]
PADS: Policy-Adapted Sampling for Visual Similarity Learning (PADS) (CVPR 2020) [Paper][PyTorch]
A Metric Learning Reality Check (ECCV 2020) [Paper][Pytorch]
Virtual sample-based deep metric learning using discriminant analysis (PR 2020) [Paper]
Provably Robust Metric Learning (NeurIPS 2020) [Paper]

3️⃣ Probabilistic methods

Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning (NIPS 2012) [Paper]
Information-theoretic Semi-supervised Metric Learning via Entropy Regularization (ICML 2014) [Paper]
Learning Deep Disentangled Embeddings With the F-Statistic Loss (F-stat) (NIPS 2018) [Paper][Tensorflow]

4️⃣ Boost-like methods

BIER-Boosting Independent Embeddings Robustly (ICCV 2017) [Paper][Tensorflow]
Hard-Aware Deeply Cascaded Embedding (ICCV 2017) [Paper][Caffe]
Learning Spread-out Local Feature Descriptors (ICCV 2017) [Paper]
Deep Adversarial Metric Learning (CVPR 2018) [Paper][Chainer]
Deep Randomized Ensembles for Metric Learning (ECCV 2018) [Paper][Pytorch]
Attention-based Ensemble for Deep Metric Learning (ECCV 2018) [Paper]
Deep Metric Learning with Hierarchical Triplet Loss (ECCV 2018) [Paper]
Hybrid-Attention based Decoupled Metric Learning for Zero-Shot Image Retrieval (CVPR 2019) [Paper] [Caffe]
Divide and Conquer the Embedding Space for Metric Learning (CVPR 2019) [Paper] [Pytorch]
Stochastic Class-based Hard Example Mining for Deep Metric Learning (CVPR 2019) [Paper]
Deep Metric Learning with Tuplet Margin Loss (ICCV 2019) [Paper]
Metric Learning with HORDE: High-Order Regularizer for Deep Embeddings (ICCV 2019) [Paper][Keras]
MIC: Mining Interclass Characteristics for Improved Metric Learning (ICCV 2019) [Paper][Pytorch]
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning (DIVA) (ECCV 2020) [Paper] [PyTorch]
The Group Loss for Deep Metric Learning (GroupLoss) (ECCV 2020) [Paper][PyTorch]

5️⃣ Unsupervised methods

Unsupervised Embedding Learning via Invariant and Spreading Instance Feature (CVPR 2019) [Paper][Pytorch]
Unsupervised Deep Metric Learning with Transformed Attention Consistency and Contrastive Clustering Loss (ECCV 2020) [Paper]

6️⃣ Applications

Re-identification

Person Re-Identification using Kernel-based Metric Learning Methods (ECCV 2014) [Paper][Matlab]
Similarity Learning on an Explicit Polynomial Kernel Feature Map for Person Re-Identification (CVPR 2015) [Paper]
Learning to rank in person re-identification with metric ensembles (CVPR 2015) [Paper]
Person Re-identification by Local Maximal Occurrence Representation and Metric Learning (CVPR 2015) [Paper][Matlab]
Learning a Discriminative Null Space for Person Re-identification (CVPR 2016) [Paper][Matlab]
Similarity Learning with Spatial Constraints for Person Re-identification (CVPR 2016) [Paper][Matlab]
Consistent-Aware Deep Learning for Person Re-identification in a Camera Network (CVPR 2016) [Paper]
Re-ranking Person Re-identification with k-reciprocal Encoding (CVPR 2017) [Paper][Caffe]
Scalable Person Re-identification on Supervised Smoothed Manifold (CVPR 2017) [Paper]
One-Shot Metric Learning for Person Re-identification (CVPR 2017) [Paper]
Point to Set Similarity Based Deep Feature Learning for Person Re-identification (CVPR 2017) [Paper]
Consistent-Aware Deep Learning for Person Re-identification in a Camera Network (CVPR 2017) [Paper]
Cross-view Asymmetric Metric Learning for Unsupervised Person Re-identification (ICCV 2017) [Paper][Matlab]
Efficient Online Local Metric Adaptation via Negative Samples for Person Re-Identification (ICCV 2017) [Paper]
Mask-guided Contrastive Attention Model for Person Re-Identification (CVPR 2018) [Paper][Caffe]
Efficient and Deep Person Re-Identification using Multi-Level Similarity (CVPR 2018) [Paper]
Group Consistent Similarity Learning via Deep CRF for Person Re-Identification (CVPR 2018) [Paper][Pytorch]
Perceive Where to Focus: Learning Visibility-aware Part-level Features for Partial Person Re-identification (CVPR 2019) [Paper]
Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification (CVPR 2019) [paper] [Pytorch]
Learning to Reduce Dual-level Discrepancy for Infrared-Visible Person Re-identification (CVPR2019) [Paper]
Densely Semantically Aligned Person Re-Identification (CVPR 2019) [Paper]
Generalizable Person Re-identification by Domain-Invariant Mapping Network (CVPR 2019) [Paper]
Re-ranking via Metric Fusion for Object Retrieval and Person Re-identification (CVPR 2019) [Paper]
Weakly Supervised Person Re-Identification (CVPR 2019) [Paper]
Towards Rich Feature Discovery with Class Activation Maps Augmentation for Person Re-Identification (CVPR 2019) [Paper]
Joint Discriminative and Generative Learning for Person Re-identification (CVPR 2019) [Paper]
Unsupervised Person Re-identification by Soft Multilabel Learning (CVPR 2019) [Paper] [Pytorch]
Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification (CVPR 2019) [Paper]
Attribute-Driven Feature Disentangling and Temporal Aggregation for Video Person Re-Identification (CVPR 2019) [Paper]
AANet: Attribute Attention Network for Person Re-Identifications (CVPR 2019) [Paper]
VRSTC: Occlusion-Free Video Person Re-Identification (CVPR 2019) [paper]
Adaptive Transfer Network for Cross-Domain Person Re-Identification (CVPR 2019) [Paper]
Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training (CVPR 2019) [Paper]
Interaction-and-Aggregation Network for Person Re-identification (CVPR 2019) [Paper]
Vehicle Re-identification with Viewpoint-aware Metric Learning (ICCV 2019) [Paper]
Distilled Person Re-identification: Towards a More Scalable System (CVPR 2019) [Paper]
Unsupervised Person Re-Identification via Multi-Label Classification (CVPR 2020) [Paper]
Style Normalization and Restitution for Generalizable Person Re-identification (CVPR 2020) [Paper]
Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification (CVPR 2020) [Paper][PyTorch]
The Dilemma of TriHard Loss and an Element-Weighted TriHard Loss for Person Re-Identification (NeurIPS 2020) [Paper][PyTorch]

Face verification

Discriminative Deep Metric Learning for Face Verification in the Wild (CVPR 2014) [Paper]
Fantope Regularization in Metric Learning (CVPR 2014) [Paper]
Deep Transfer Metric Learning (CVPR 2015) [Paper]
BioMetricNet: deep unconstrained face verification through learning of metrics regularized onto Gaussian distributions (ECCV 2020) [Paper]

Face recognition

Large Scale Metric Learning from Equivalence Constraints (CVPR 2012) [Paper]
Fusing Robust Face Region Descriptors via Multiple Metric Learning for Face Recognition in the Wild (CVPR 2013) [Paper]
Similarity Metric Learning for Face Recognition (ICCV 2013) [Paper]
Projection Metric Learning on Grassmann Manifold with Application to Video based Face Recognition (CVPR 2015) [Paper]

Segmentation

Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning (CVPR 2019) [Paper]
3D Instance Segmentation via Multi-Task Metric Learning (ICCV 2019) [Paper]

Image registration

Metric Learning for Image Registration (CVPR 2019) [Paper]

Few (zero)-shot approach

RepMet: Representative-based metric learning for classification and few-shot object detection (CVPR 2019) [Paper] [Pytorch]
Revisiting Metric Learning for Few-Shot Image Classification (arXiv 2019) [Paper]
Model-Agnostic Metric for Zero-Shot Learning (WACV 2020) [Paper]

3D reconstruction

Learning Embedding of 3D models with Quadric Loss (BMVC 2019) [Paper][Pytorch]

Action localization

Weakly Supervised Temporal Action Localization Using Deep Metric Learning (WACV2020) [Paper][Pytorch]

Adversarial attack

Metric Learning for Adversarial Robustness (Neurips 2019) [Paper][Tensorflow]

Text documentation

Fast(er) Reconstruction of Shredded Text Documents via Self-Supervised Deep Asymmetric Metric Learning (CVPR 2020) [Paper][Code]

Pill identification

ePillID Dataset: A Low-Shot Fine-Grained Benchmark for Pill Identification (CVPR 2020) [Paper][Code]

7️⃣ Related works

Neurips

Distance Metric Learning for Large Margin Nearest Neighbor Classification (Neurips 2005) [Paper][Journal][Python]
First approach of local metric learning
Metric Learning by Collapsing Classes (Neurips 2005) [Paper]
Online Metric Learning and Fast Similarity Search (Neurips 2008) [Paper]
Sparse Metric Learning via Smooth Optimization (Neurips 2009) [Paper]
Metric Learning with Multiple Kernels (Neurips 2011) [Paper]
Hamming Distance Metric Learning (Neurips 2012) [Paper][Matlab]
Parametric Local Metric Learning for Nearest Neighbor Classification (Neurips 2012) [Paper]

A representative approach of local metric learning

Non-linear Metric Learning (Neurips 2012) [Paper]
Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning (Neurips 2012) [Paper]
- They deal with probabilistic model based on EM algorithm
Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning (Neurips 2012) [Paper]
Similarity Component Analysis (Neurips 2013) [Paper]
Discriminative Metric Learning by Neighborhood Gerrymandering (Neurips 2014) [Paper]
Log-Hilbert-Schmidt metric between positive definite operators on Hilbert spaces (Neurips 2014) [Paper]
Metric Learning for Temporal Sequence Alignment (Neurips 2014) [paper]
Sample complexity of learning Mahalanobis distance metrics (Neurips 2015) [Paper]
Regressive Virtual Metric Learning (Neurips 2015) [Paper]
What Makes Objects Similar: A Unified Multi-Metric Learning Approach (Neurips 2016) [Paper]
Improved Error Bounds for Tree Representations of Metric Spaces (Neurips 2016) [Paper]
What Makes Objects Similar: A Unified Multi-Metric Learning Approach (Neurips 2016) [Paper]
Learning Low-Dimensional Metrics (Neurips 2017) [Paper]
Generative Local Metric Learning for Kernel Regression (Neurips 2017) [Paper]
Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams (Neurips 2018) [Paper][Matlab]
Bilevel Distance Metric Learning for Robust Image Recognition (Neurips 2018) [Paper]
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning (Neurips 2018) [Paper][Tensorflow]
Fast Low-rank Metric Learning for Large-scale and High-dimensional Data (Neurips 2019) [Paper][Matlab]
Metric Learning for Adversarial Robustness (Neurips 2019) [Paper][Tensorflow]
Region-specific Diffeomorphic Metric Mapping (Neurips 2019) [Paper][Pytorch]
Fast Low-rank Metric Learning for Large-scale and High-dimensional Data (FLRML) (Neurips 2019) [Paper][Matlab]
Contrastive Learning with Adversarial Examples (NeurIPS 2020) [Paper]
Simultaneous Preference and Metric Learning from Paired Comparisons (NeurIPS 2020) [Paper][MatLab]
Multi-task Batch Reinforcement Learning with Metric Learning (NeurIPS 2020) [Paper]

ICLR

Deep Metric Learning Using Triplet Network (ICLR 2015 workshop) [Paper][Keras][Torch]
Metric Learning with Adaptive Density Discrimination (Magnet loss) (ICLR 2016) [Paper][Pytorch1][Pytorch2][Tensorflow]
Semi-supervised Deep Learning by Metric Embedding (ICLRW 2017) [Paper][Torch(Lua)]
Learning Wasserstein Embedding (ICLR 2018) [Paper][Keras]
Smoothing the Geometry of Probabilistic Box Embeddings (ICLR 2019) [Paper][Tensorflow]
- New type of embedding method
Unsupervised Domain Adaptation for Distance Metric Learning (ICLR 2019) [Paper]
ROTATE: Knowledge Graph Embedding bt Relational Rotation in Complex Space (ICLR 2019) [Paper][Pytorch]
- Define relationship by using rotation in vector space
Conditional Network Embeddings (ICLR 2019) [Paper][Matlab]
- Add additional information with respect to given structural properties

ICML

Gromov-Wasserstein Learning for Graph Matching and Node Embedding (ICML 2019) [Paper][Pytorch]
- Propose novel framework btw. relation graph and embedding space
Hyperbolic Disk Embeddings for Directed Acyclic Graphs (ICML 2019) [Paper][Luigi]
- Propose embedding framework on quasi-metric space

ECCV

A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses (ECCV 2020) [Paper][PyTorch]

ICIP

Quadruplet Selection Methods for Deep Embedding Learning (ICIP 2019) [Paper]

Others

Cross-Batch Memory for Embedding Learning (ArXiv 2020) [Paper]
Calibrated neighborhood aware confidence measure for deep metric learning (ArXiv 2020) [Paper]
Diversified Mutual Learning for Deep Metric Learning (ArXiv 2020) [Link]
Deep Metric Learning Based on Rank-sensitive Optimization of Top-k Precision (CIKM 2020) [Paper]

8️⃣ Study materials

Tutorial

Metric learning tutorial (ICML 2010) [Video]
Metric Learning and Manifolds: Preserving the Intrinsic Geometry (MS research 2016) [VIdeo]
Visual Search (Image Retrieval) and Metric Learning (CVPR 2018) [Video]

Lecture

Topology and Manifold (International Winter School on Gravity and Light 2015) [Video]
Metric learning lecture (Waterloo University) [Video]
Understanding of Mahalanobis distance [Video]
Metric Learning by Caltech (2018) [Video]

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