diff --git a/CONTENTS.md b/CONTENTS.md index 8561f7c5..24a48b2f 100644 --- a/CONTENTS.md +++ b/CONTENTS.md @@ -1,4 +1,14 @@ ## Library contents + +### [Datasets](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets) +| Name | Reference Papers | +|---|---| +| [**CUB**](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets/#cub-200-2011) | [The caltech-ucsd birds-200-2011 dataset](https://authors.library.caltech.edu/27452/1/CUB_200_2011.pdf) +| [**Cars196**](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets/#cars196) | 3D Object Representations for Fine-Grained Categorization +| [**INaturalist2018**](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets/#inaturalist2018) | [The iNaturalist Species Classification and Detection Dataset](https://openaccess.thecvf.com/content_cvpr_2018/papers/Van_Horn_The_INaturalist_Species_CVPR_2018_paper.pdf) +| [**StanfordOnlineProducts**](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets/#stanfordonlineproducts) | [Deep Metric Learning via Lifted Structured Feature Embedding](https://cvgl.stanford.edu/papers/song_cvpr16.pdf) + + ### [Distances](https://kevinmusgrave.github.io/pytorch-metric-learning/distances) | Name | Reference Papers | |---|---| @@ -40,6 +50,7 @@ | [**SphereFaceLoss**](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#spherefaceloss) | [SphereFace: Deep Hypersphere Embedding for Face Recognition](https://arxiv.org/pdf/1704.08063.pdf) | [**SubCenterArcFaceLoss**](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#subcenterarcfaceloss) | [Sub-center ArcFace: Boosting Face Recognition by Large-scale Noisy Web Faces](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123560715.pdf) | [**SupConLoss**](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#supconloss) | [Supervised Contrastive Learning](https://arxiv.org/abs/2004.11362) +| [**ThresholdConsistentMarginLoss**](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#thresholdconsistentmarginloss) | [Threshold-Consistent Margin Loss for Open-World Deep Metric Learning](https://arxiv.org/pdf/2307.04047) | [**TripletMarginLoss**](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#tripletmarginloss) | [Distance Metric Learning for Large Margin Nearest Neighbor Classification](https://papers.nips.cc/paper/2795-distance-metric-learning-for-large-margin-nearest-neighbor-classification.pdf) | [**TupletMarginLoss**](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#tupletmarginloss) | [Deep Metric Learning with Tuplet Margin Loss](http://openaccess.thecvf.com/content_ICCV_2019/papers/Yu_Deep_Metric_Learning_With_Tuplet_Margin_Loss_ICCV_2019_paper.pdf) | [**VICRegLoss**](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#vicregloss) | [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning](https://arxiv.org/pdf/2105.04906.pdf) diff --git a/README.md b/README.md index efa91e22..a704340f 100644 --- a/README.md +++ b/README.md @@ -18,15 +18,17 @@ ## News -**July 24**: v2.6.0 -- Changed the `emb` argument of `DistributedLossWrapper.forward` to `embeddings` to be consistent with the rest of the library. -- Added a warning and early-return when `DistributedLossWrapper` is being used in a non-distributed setting. -- Thank you [elisim](https://github.com/elisim). - -**April 1**: v2.5.0 -- Improved `get_all_triplets_indices` so that large batch sizes don't trigger the `INT_MAX` error. -- See the [release notes](https://github.com/KevinMusgrave/pytorch-metric-learning/releases/tag/v2.5.0). -- Thank you [mkmenta](https://github.com/mkmenta). +**December 11**: v2.8.0 +- Added the [Datasets](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets) module for easy downloading of common datasets: + - [CUB200](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets/#cub-200-2011) + - [Cars196](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets/#cars196) + - [INaturalist 2018](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets/#inaturalist2018) + - [Stanford Online Products](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets/#stanfordonlineproducts) +- Thank you [ir2718](https://github.com/ir2718). + +**November 2**: v2.7.0 +- Added [ThresholdConsistentMarginLoss](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#thresholdconsistentmarginloss). +- Thank you [ir2718](https://github.com/ir2718). ## Documentation - [**View the documentation here**](https://kevinmusgrave.github.io/pytorch-metric-learning/) @@ -229,6 +231,7 @@ Thanks to the contributors who made pull requests! |[domenicoMuscill0](https://github.com/domenicoMuscill0)| - [ManifoldLoss](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#manifoldloss)
- [P2SGradLoss](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#p2sgradloss)
- [HistogramLoss](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#histogramloss)
- [DynamicSoftMarginLoss](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#dynamicsoftmarginloss)
- [RankedListLoss](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#rankedlistloss) | |[mlopezantequera](https://github.com/mlopezantequera) | - Made the [testers](https://kevinmusgrave.github.io/pytorch-metric-learning/testers) work on any combination of query and reference sets
- Made [AccuracyCalculator](https://kevinmusgrave.github.io/pytorch-metric-learning/accuracy_calculation/) work with arbitrary label comparisons | |[cwkeam](https://github.com/cwkeam) | - [SelfSupervisedLoss](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#selfsupervisedloss)
- [VICRegLoss](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#vicregloss)
- Added mean reciprocal rank accuracy to [AccuracyCalculator](https://kevinmusgrave.github.io/pytorch-metric-learning/accuracy_calculation/)
- BaseLossWrapper| +| [ir2718](https://github.com/ir2718) | - [ThresholdConsistentMarginLoss](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#thresholdconsistentmarginloss)
- The [Datasets](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets) module | |[marijnl](https://github.com/marijnl)| - [BatchEasyHardMiner](https://kevinmusgrave.github.io/pytorch-metric-learning/miners/#batcheasyhardminer)
- [TwoStreamMetricLoss](https://kevinmusgrave.github.io/pytorch-metric-learning/trainers/#twostreammetricloss)
- [GlobalTwoStreamEmbeddingSpaceTester](https://kevinmusgrave.github.io/pytorch-metric-learning/testers/#globaltwostreamembeddingspacetester)
- [Example using trainers.TwoStreamMetricLoss](https://github.com/KevinMusgrave/pytorch-metric-learning/blob/master/examples/notebooks/TwoStreamMetricLoss.ipynb) | | [chingisooinar](https://github.com/chingisooinar) | [SubCenterArcFaceLoss](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#subcenterarcfaceloss) | | [elias-ramzi](https://github.com/elias-ramzi) | [HierarchicalSampler](https://kevinmusgrave.github.io/pytorch-metric-learning/samplers/#hierarchicalsampler) |