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Library contents

Name Reference Papers
CosineSimilarity
DotProductSimilarity
LpDistance
SNRDistance Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning
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
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
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
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
Name Reference Papers
AvgNonZeroReducer
ClassWeightedReducer
DivisorReducer
DoNothingReducer
MeanReducer
PerAnchorReducer
ThresholdReducer
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
Name Reference Papers
MPerClassSampler
HierarchicalSampler Deep Metric Learning to Rank
TuplesToWeightsSampler
FixedSetOfTriplets
Name Reference Papers
MetricLossOnly
TrainWithClassifier
CascadedEmbeddings Hard-Aware Deeply Cascaded Embedding
DeepAdversarialMetricLearning Deep Adversarial Metric Learning
TwoStreamMetricLoss
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