Library contents

Datasets

Name	Reference Papers
CUB	The caltech-ucsd birds-200-2011 dataset
Cars196	3D Object Representations for Fine-Grained Categorization
INaturalist2018	The iNaturalist Species Classification and Detection Dataset
StanfordOnlineProducts	Deep Metric Learning via Lifted Structured Feature Embedding

Distances

Name	Reference Papers
CosineSimilarity
DotProductSimilarity
LpDistance
SNRDistance	Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning

Losses

Name	Reference Papers
AngularLoss	Deep Metric Learning with Angular Loss
ArcFaceLoss	ArcFace: Additive Angular Margin Loss for Deep Face Recognition
CircleLoss	Circle Loss: A Unified Perspective of Pair Similarity Optimization
ContrastiveLoss	Dimensionality Reduction by Learning an Invariant Mapping
CosFaceLoss	- CosFace: Large Margin Cosine Loss for Deep Face Recognition - Additive Margin Softmax for Face Verification
DynamicSoftMarginLoss	Learning Local Descriptors With a CDF-Based Dynamic Soft Margin
FastAPLoss	Deep Metric Learning to Rank
GeneralizedLiftedStructureLoss	In Defense of the Triplet Loss for Person Re-Identification
HistogramLoss	Learning Deep Embeddings with Histogram Loss
InstanceLoss	Dual-Path Convolutional Image-Text Embeddings with Instance Loss
IntraPairVarianceLoss	Deep Metric Learning with Tuplet Margin Loss
LargeMarginSoftmaxLoss	Large-Margin Softmax Loss for Convolutional Neural Networks
LiftedStructreLoss	Deep Metric Learning via Lifted Structured Feature Embedding
ManifoldLoss	Ensemble Deep Manifold Similarity Learning using Hard Proxies
MarginLoss	Sampling Matters in Deep Embedding Learning
MultiSimilarityLoss	Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning
NCALoss	Neighbourhood Components Analysis
NormalizedSoftmaxLoss	- NormFace: L2 Hypersphere Embedding for Face Verification - Classification is a Strong Baseline for DeepMetric Learning
NPairsLoss	Improved Deep Metric Learning with Multi-class N-pair Loss Objective
NTXentLoss	- Representation Learning with Contrastive Predictive Coding - Momentum Contrast for Unsupervised Visual Representation Learning - A Simple Framework for Contrastive Learning of Visual Representations
P2SGradLoss	P2SGrad: Refined Gradients for Optimizing Deep Face Models
PNPLoss	Rethinking the Optimization of Average Precision: Only Penalizing Negative Instances before Positive Ones is Enough
ProxyAnchorLoss	Proxy Anchor Loss for Deep Metric Learning
ProxyNCALoss	No Fuss Distance Metric Learning using Proxies
RankedListLoss	Ranked List Loss for Deep Metric Learning
SignalToNoiseRatioContrastiveLoss	Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning
SmoothAPLoss	Smooth-AP: Smoothing the Path Towards Large-Scale Image Retrieval
SoftTripleLoss	SoftTriple Loss: Deep Metric Learning Without Triplet Sampling
SphereFaceLoss	SphereFace: Deep Hypersphere Embedding for Face Recognition
SubCenterArcFaceLoss	Sub-center ArcFace: Boosting Face Recognition by Large-scale Noisy Web Faces
SupConLoss	Supervised Contrastive Learning
ThresholdConsistentMarginLoss	Threshold-Consistent Margin Loss for Open-World Deep Metric Learning
TripletMarginLoss	Distance Metric Learning for Large Margin Nearest Neighbor Classification
TupletMarginLoss	Deep Metric Learning with Tuplet Margin Loss
VICRegLoss	VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning

Miners

Name	Reference Papers
AngularMiner
BatchEasyHardMiner	Improved Embeddings with Easy Positive Triplet Mining
BatchHardMiner	In Defense of the Triplet Loss for Person Re-Identification
DistanceWeightedMiner	Sampling Matters in Deep Embedding Learning
EmbeddingsAlreadyPackagedAsTriplets
HDCMiner	Hard-Aware Deeply Cascaded Embedding
MultiSimilarityMiner	Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning
PairMarginMiner
TripletMarginMiner	FaceNet: A Unified Embedding for Face Recognition and Clustering
UniformHistogramMiner

Reducers

Name	Reference Papers
AvgNonZeroReducer
ClassWeightedReducer
DivisorReducer
DoNothingReducer
MeanReducer
PerAnchorReducer
ThresholdReducer

Regularizers

Name	Reference Papers
CenterInvariantRegularizer	Deep Face Recognition with Center Invariant Loss
LpRegularizer
RegularFaceRegularizer	RegularFace: Deep Face Recognition via Exclusive Regularization
SparseCentersRegularizer	SoftTriple Loss: Deep Metric Learning Without Triplet Sampling
ZeroMeanRegularizer	Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning

Samplers

Name	Reference Papers
MPerClassSampler
HierarchicalSampler	Deep Metric Learning to Rank
TuplesToWeightsSampler
FixedSetOfTriplets

Trainers

Name	Reference Papers
MetricLossOnly
TrainWithClassifier
CascadedEmbeddings	Hard-Aware Deeply Cascaded Embedding
DeepAdversarialMetricLearning	Deep Adversarial Metric Learning
TwoStreamMetricLoss

Testers

Name	Reference Papers
GlobalEmbeddingSpaceTester
WithSameParentLabelTester
GlobalTwoStreamEmbeddingSpaceTester

Utils

Name	Reference Papers
AccuracyCalculator
HookContainer
InferenceModel
TorchInitWrapper
DistributedLossWrapper
DistributedMinerWrapper

Base Classes, Mixins, and Wrappers

Name	Reference Papers
CrossBatchMemory	Cross-Batch Memory for Embedding Learning
GenericPairLoss
MultipleLosses
MultipleReducers
EmbeddingRegularizerMixin
WeightMixin
WeightRegularizerMixin
BaseDistance
BaseMetricLossFunction
BaseMiner
BaseReducer
BaseRegularizer
BaseTrainer
BaseTester

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