https://github.com/alixunxing/awesome-contrastive-self-supervised-learning
A comprehensive list of awesome contrastive self-supervised learning papers.
https://github.com/alixunxing/awesome-contrastive-self-supervised-learning
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A comprehensive list of awesome contrastive self-supervised learning papers.
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# Awesome CONTRASTIVE LEARNING [](https://github.com/sindresorhus/awesome#readme) > A comprehensive list of awesome contrastive self-supervised learning papers. ## PAPERS #### Surveys and Reviews - [ ] [2020: A Survey on Contrastive Self-Supervised Learning](https://arxiv.org/abs/2011.00362) #### 2022 - [ ] [2022: Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection](https://arxiv.org/abs/2203.12121) - [ ] [2022: Fair Contrastive Learning for Facial Attribute Classification (FSCL)](https://arxiv.org/abs/2203.16209) #### 2021 - [ ] [2021: Learning Transferable Visual Models From Natural Language Supervision (CLIP)](http://proceedings.mlr.press/v139/radford21a) - [ ] [2021: Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images](https://arxiv.org/abs/2103.03423) - [ ] [2021: Robust Contrastive Learning Using Negative Samples with Diminished Semantics](https://arxiv.org/abs/2110.14189) - [ ] [2021: VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning](https://arxiv.org/pdf/2105.04906.pdf) - [ ] [2021: Barlow Twins: Self-Supervised Learning via Redundancy Reduction](https://arxiv.org/pdf/2103.03230.pdf) - [ ] [2021: Poisoning and Backdooring Contrastive Learning](https://arxiv.org/abs/2106.09667) - [ ] [2021: Adversarial Attacks are Reversible with Natural Supervision](https://arxiv.org/abs/2103.14222) - [ ] [2021: Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels](https://arxiv.org/abs/2107.13741v1) - [ ] [2021: Understanding Cognitive Fatigue from fMRI Scans with Self-supervised Learning](https://arxiv.org/abs/2106.15009) - [ ] [2021: A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning ](https://arxiv.org/abs/2104.14558) - [ ] [2021: Contrastive Semi-Supervised Learning for 2D Medical Image Segmentation](https://arxiv.org/abs/2106.06801) - [ ] [2021: Contrastive Learning with Stronger Augmentations](https://arxiv.org/abs/2104.07713v1) - [ ] [2021: Dual Contrastive Learning for Unsupervised Image-to-Image Translation](https://arxiv.org/abs/2104.07689v1) - [ ] [2021: How Well Do Self-Supervised Models Transfer?](https://arxiv.org/abs/2011.13377) - [ ] [2021: Self-supervised Pretraining of Visual Features in the Wild](https://arxiv.org/abs/2103.01988) - [ ] [2021: VideoMoCo: Contrastive Video Representation Learning with Temporally Adversarial Examples](https://arxiv.org/abs/2103.05905v2) - [ ] [2021: Temporal Contrastive Graph for Self-supervised Video Representation Learning](https://arxiv.org/abs/2101.00820) - [ ] [2021: Active Learning by Acquiring Contrastive Examples](https://arxiv.org/abs/2109.03764) - [ ] [2021: Active Contrastive Learning of Audio-Visual Video Representations](https://arxiv.org/abs/2009.09805) #### 2020 - [ ] [2020: Rethinking the Value of Labels for Improving Class-Imbalanced Learning](https://arxiv.org/abs/2006.07529) - [ ] [2020: Online Bag-of-Visual-Words Generation for Unsupervised Representation Learning](https://arxiv.org/abs/2012.11552) - [ ] [2020: Social NCE: Contrastive Learning of Socially-aware Motion Representations](https://arxiv.org/abs/2012.11717) - [ ] [2020: CASTing Your Model: Learning to Localize Improves Self-Supervised Representations](https://arxiv.org/pdf/2012.04630.pdf) - [ ] [2020: Exploring Simple Siamese Representation Learning](https://arxiv.org/abs/2011.10566) - [ ] [2020: FROST: Faster and more Robust One-shot Semi-supervised Training](https://arxiv.org/abs/2011.09471) - [ ] [2020: Hard Negative Mixing for Contrastive Learning](https://arxiv.org/abs/2010.01028) - [ ] [2020: Representation Learning via Invariant Causal Mechanisms](https://arxiv.org/abs/2010.07922) - [ ] [2020: Are all negatives created equal in contrastive instance discrimination?](https://arxiv.org/abs/2010.06682) - [ ] [2020: Bootstrap your own latent: A new approach to self-supervised Learning](https://arxiv.org/abs/2006.07733) - [ ] [2020: Spatiotemporal Contrastive Video Representation Learning](https://arxiv.org/abs/2008.03800) - [ ] [2020: Augmented Skeleton Based Contrastive Action Learning with Momentum LSTM for Unsupervised Action Recognition](https://arxiv.org/abs/2008.00188) - [ ] [2020: Deep Robust Clustering by Contrastive Learning](https://arxiv.org/abs/2008.03030) - [ ] [2020: Contrastive Learning for Unpaired Image-to-Image Translation](https://arxiv.org/abs/2007.15651) - [ ] [2020: Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases](https://arxiv.org/abs/2007.13916) - [ ] [2020: What Should Not Be Contrastive in Contrastive Learning](https://arxiv.org/abs/2008.05659) - [ ] [2020: Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework](https://arxiv.org/abs/2008.02531) - [ ] [2020: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments](https://arxiv.org/abs/2006.09882) - [ ] [2020: Prototypical Contrastive Learning of Unsupervised Representations](https://arxiv.org/abs/2005.04966) - [ ] [2020: GraphCL: Contrastive Self-Supervised Learning of Graph Representations](https://arxiv.org/abs/2007.08025) - [ ] [2020: DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations](https://arxiv.org/abs/2006.03659) - [ ] [2020: Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models](https://arxiv.org/abs/2005.10389) - [ ] [2020: CERT: Contrastive Self-supervised Learning for Language Understanding](https://arxiv.org/abs/2005.12766) - [ ] [2020: Deep Graph Contrastive Representation Learning](https://arxiv.org/abs/2006.04131v1) - [ ] [2020: CLOCS: Contrastive Learning of Cardiac Signals](https://arxiv.org/abs/2005.13249v1) - [ ] [2020: On Mutual Information in Contrastive Learning for Visual Representations](https://arxiv.org/abs/2005.13149v2) - [ ] [2020: What makes for good views for contrastive learning](https://arxiv.org/abs/2005.10243v1) - [ ] [2020: CURL: Contrastive Unsupervised Representations for Reinforcement Learning](https://arxiv.org/abs/2004.04136v2) - [ ] [2020: Supervised Contrastive Learning](https://arxiv.org/abs/2004.11362v1) - [ ] [2020: Clustering based Contrastive Learning for Improving Face Representations](https://arxiv.org/abs/2004.02195v1) - [ ] [2020: A Simple Framework for Contrastive Learning of Visual Representations](https://arxiv.org/pdf/2002.05709.pdf) - [ ] [2020: Improved Baselines with Momentum Contrastive Learning](https://arxiv.org/abs/2003.04297v1) - [ ] [2020: ALICE: Active Learning with Contrastive Natural Language Explanations](https://arxiv.org/abs/2009.10259) #### 2019 - [ ] [2019: Unsupervised Scene Adaptation with Memory Regularization in vivo](https://arxiv.org/abs/1912.11164) - [ ] [2019: Self-labelling via simultaneous clustering and representation learning](https://arxiv.org/abs/1911.05371) - [ ] [2019: Transferable Contrastive Network for Generalized Zero-Shot Learning](https://arxiv.org/abs/1908.05832v1) - [ ] [2019: MoCo: Momentum Contrast for Unsupervised Visual Representation Learning](https://arxiv.org/abs/1911.05722) - [ ] [2019: Self-Supervised Learning of Pretext-Invariant Representations](https://arxiv.org/pdf/1912.01991.pdf) - [ ] [2019: Selfie: Self-supervised Pretraining for Image Embedding](https://arxiv.org/abs/1906.02940) - [ ] [2019: Data-Efficient Image Recognition with Contrastive Predictive Coding](https://arxiv.org/abs/1905.09272) - [ ] [2019: Local Aggregation for Unsupervised Learning of Visual Embeddings](https://arxiv.org/abs/1903.12355) - [ ] [2019: Learning Representations by Maximizing Mutual Information Across Views](https://arxiv.org/abs/1906.00910) - [ ] [2019: Contrastive Multiview Coding](https://arxiv.org/abs/1906.05849) - [ ] [2019: Unsupervised Embedding Learning via Invariant and Spreading Instance Feature](https://arxiv.org/abs/1904.03436) - [ ] [2019: Invariant Information Clustering for Unsupervised Image Classification and Segmentation](https://arxiv.org/abs/1807.06653) - [ ] [2019: A Theoretical Analysis of Contrastive Unsupervised Representation Learning](https://arxiv.org/abs/1902.09229) #### 2018 - [ ] [2018: Learning deep representations by mutual information estimation and maximization](https://arxiv.org/abs/1808.06670) - [ ] [2018: Representation Learning with Contrastive Predictive Coding](https://arxiv.org/abs/1807.03748) - [ ] [2018: Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination](https://arxiv.org/abs/1805.01978) #### 2017 and Older - [ ] [2017: Time-Contrastive Networks: Self-Supervised Learning from Video](https://arxiv.org/abs/1704.06888) - [ ] [2017: Multi-task Self-Supervised Visual Learning](https://arxiv.org/abs/1708.07860) - [ ] [2017: Unsupervised learning of visual representations by solving jigsawpuzzles](https://arxiv.org/abs/1603.09246) - [ ] [2015: Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks](https://arxiv.org/abs/1406.6909) - [ ] [2010: Noise-contrastive estimation: A new estimation principle for unnormalized statistical models](http://proceedings.mlr.press/v9/gutmann10a/gutmann10a.pdf)
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# Awesome CONTRASTIVE LEARNING [](https://github.com/sindresorhus/awesome#readme)
> A comprehensive list of awesome contrastive self-supervised learning papers.
## PAPERS
#### Surveys and Reviews
- [ ] [2020: A Survey on Contrastive Self-Supervised Learning](https://arxiv.org/abs/2011.00362)
#### 2022
- [ ] [2022: Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection](https://arxiv.org/abs/2203.12121)
- [ ] [2022: Fair Contrastive Learning for Facial Attribute Classification (FSCL)](https://arxiv.org/abs/2203.16209)
#### 2021
- [ ] [2021: Learning Transferable Visual Models From Natural Language Supervision (CLIP)](http://proceedings.mlr.press/v139/radford21a)
- [ ] [2021: Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images](https://arxiv.org/abs/2103.03423)
- [ ] [2021: Robust Contrastive Learning Using Negative Samples with Diminished Semantics](https://arxiv.org/abs/2110.14189)
- [ ] [2021: VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning](https://arxiv.org/pdf/2105.04906.pdf)
- [ ] [2021: Barlow Twins: Self-Supervised Learning via Redundancy Reduction](https://arxiv.org/pdf/2103.03230.pdf)
- [ ] [2021: Poisoning and Backdooring Contrastive Learning](https://arxiv.org/abs/2106.09667)
- [ ] [2021: Adversarial Attacks are Reversible with Natural Supervision](https://arxiv.org/abs/2103.14222)
- [ ] [2021: Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels](https://arxiv.org/abs/2107.13741v1)
- [ ] [2021: Understanding Cognitive Fatigue from fMRI Scans with Self-supervised Learning](https://arxiv.org/abs/2106.15009)
- [ ] [2021: A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning
](https://arxiv.org/abs/2104.14558)
- [ ] [2021: Contrastive Semi-Supervised Learning for 2D Medical Image Segmentation](https://arxiv.org/abs/2106.06801)
- [ ] [2021: Contrastive Learning with Stronger Augmentations](https://arxiv.org/abs/2104.07713v1)
- [ ] [2021: Dual Contrastive Learning for Unsupervised Image-to-Image Translation](https://arxiv.org/abs/2104.07689v1)
- [ ] [2021: How Well Do Self-Supervised Models Transfer?](https://arxiv.org/abs/2011.13377)
- [ ] [2021: Self-supervised Pretraining of Visual Features in the Wild](https://arxiv.org/abs/2103.01988)
- [ ] [2021: VideoMoCo: Contrastive Video Representation Learning with Temporally Adversarial Examples](https://arxiv.org/abs/2103.05905v2)
- [ ] [2021: Temporal Contrastive Graph for Self-supervised Video Representation Learning](https://arxiv.org/abs/2101.00820)
- [ ] [2021: Active Learning by Acquiring Contrastive Examples](https://arxiv.org/abs/2109.03764)
- [ ] [2021: Active Contrastive Learning of Audio-Visual Video Representations](https://arxiv.org/abs/2009.09805)
#### 2020
- [ ] [2020: Rethinking the Value of Labels for Improving Class-Imbalanced Learning](https://arxiv.org/abs/2006.07529)
- [ ] [2020: Online Bag-of-Visual-Words Generation for Unsupervised Representation Learning](https://arxiv.org/abs/2012.11552)
- [ ] [2020: Social NCE: Contrastive Learning of Socially-aware Motion Representations](https://arxiv.org/abs/2012.11717)
- [ ] [2020: CASTing Your Model: Learning to Localize Improves Self-Supervised Representations](https://arxiv.org/pdf/2012.04630.pdf)
- [ ] [2020: Exploring Simple Siamese Representation Learning](https://arxiv.org/abs/2011.10566)
- [ ] [2020: FROST: Faster and more Robust One-shot Semi-supervised Training](https://arxiv.org/abs/2011.09471)
- [ ] [2020: Hard Negative Mixing for Contrastive Learning](https://arxiv.org/abs/2010.01028)
- [ ] [2020: Representation Learning via Invariant Causal Mechanisms](https://arxiv.org/abs/2010.07922)
- [ ] [2020: Are all negatives created equal in contrastive instance discrimination?](https://arxiv.org/abs/2010.06682)
- [ ] [2020: Bootstrap your own latent: A new approach to self-supervised Learning](https://arxiv.org/abs/2006.07733)
- [ ] [2020: Spatiotemporal Contrastive Video Representation Learning](https://arxiv.org/abs/2008.03800)
- [ ] [2020: Augmented Skeleton Based Contrastive Action Learning with Momentum LSTM for Unsupervised Action Recognition](https://arxiv.org/abs/2008.00188)
- [ ] [2020: Deep Robust Clustering by Contrastive Learning](https://arxiv.org/abs/2008.03030)
- [ ] [2020: Contrastive Learning for Unpaired Image-to-Image Translation](https://arxiv.org/abs/2007.15651)
- [ ] [2020: Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases](https://arxiv.org/abs/2007.13916)
- [ ] [2020: What Should Not Be Contrastive in Contrastive Learning](https://arxiv.org/abs/2008.05659)
- [ ] [2020: Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework](https://arxiv.org/abs/2008.02531)
- [ ] [2020: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments](https://arxiv.org/abs/2006.09882)
- [ ] [2020: Prototypical Contrastive Learning of Unsupervised Representations](https://arxiv.org/abs/2005.04966)
- [ ] [2020: GraphCL: Contrastive Self-Supervised Learning of Graph Representations](https://arxiv.org/abs/2007.08025)
- [ ] [2020: DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations](https://arxiv.org/abs/2006.03659)
- [ ] [2020: Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models](https://arxiv.org/abs/2005.10389)
- [ ] [2020: CERT: Contrastive Self-supervised Learning for Language Understanding](https://arxiv.org/abs/2005.12766)
- [ ] [2020: Deep Graph Contrastive Representation Learning](https://arxiv.org/abs/2006.04131v1)
- [ ] [2020: CLOCS: Contrastive Learning of Cardiac Signals](https://arxiv.org/abs/2005.13249v1)
- [ ] [2020: On Mutual Information in Contrastive Learning for Visual Representations](https://arxiv.org/abs/2005.13149v2)
- [ ] [2020: What makes for good views for contrastive learning](https://arxiv.org/abs/2005.10243v1)
- [ ] [2020: CURL: Contrastive Unsupervised Representations for Reinforcement Learning](https://arxiv.org/abs/2004.04136v2)
- [ ] [2020: Supervised Contrastive Learning](https://arxiv.org/abs/2004.11362v1)
- [ ] [2020: Clustering based Contrastive Learning for Improving Face Representations](https://arxiv.org/abs/2004.02195v1)
- [ ] [2020: A Simple Framework for Contrastive Learning of Visual Representations](https://arxiv.org/pdf/2002.05709.pdf)
- [ ] [2020: Improved Baselines with Momentum Contrastive Learning](https://arxiv.org/abs/2003.04297v1)
- [ ] [2020: ALICE: Active Learning with Contrastive Natural Language Explanations](https://arxiv.org/abs/2009.10259)
#### 2019
- [ ] [2019: Unsupervised Scene Adaptation with Memory Regularization in vivo](https://arxiv.org/abs/1912.11164)
- [ ] [2019: Self-labelling via simultaneous clustering and representation learning](https://arxiv.org/abs/1911.05371)
- [ ] [2019: Transferable Contrastive Network for Generalized Zero-Shot Learning](https://arxiv.org/abs/1908.05832v1)
- [ ] [2019: MoCo: Momentum Contrast for Unsupervised Visual Representation Learning](https://arxiv.org/abs/1911.05722)
- [ ] [2019: Self-Supervised Learning of Pretext-Invariant Representations](https://arxiv.org/pdf/1912.01991.pdf)
- [ ] [2019: Selfie: Self-supervised Pretraining for Image Embedding](https://arxiv.org/abs/1906.02940)
- [ ] [2019: Data-Efficient Image Recognition with Contrastive Predictive Coding](https://arxiv.org/abs/1905.09272)
- [ ] [2019: Local Aggregation for Unsupervised Learning of Visual Embeddings](https://arxiv.org/abs/1903.12355)
- [ ] [2019: Learning Representations by Maximizing Mutual Information Across Views](https://arxiv.org/abs/1906.00910)
- [ ] [2019: Contrastive Multiview Coding](https://arxiv.org/abs/1906.05849)
- [ ] [2019: Unsupervised Embedding Learning via Invariant and Spreading Instance Feature](https://arxiv.org/abs/1904.03436)
- [ ] [2019: Invariant Information Clustering for Unsupervised Image Classification and Segmentation](https://arxiv.org/abs/1807.06653)
- [ ] [2019: A Theoretical Analysis of Contrastive Unsupervised Representation Learning](https://arxiv.org/abs/1902.09229)
#### 2018
- [ ] [2018: Learning deep representations by mutual information estimation and maximization](https://arxiv.org/abs/1808.06670)
- [ ] [2018: Representation Learning with Contrastive Predictive Coding](https://arxiv.org/abs/1807.03748)
- [ ] [2018: Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination](https://arxiv.org/abs/1805.01978)
#### 2017 and Older
- [ ] [2017: Time-Contrastive Networks: Self-Supervised Learning from Video](https://arxiv.org/abs/1704.06888)
- [ ] [2017: Multi-task Self-Supervised Visual Learning](https://arxiv.org/abs/1708.07860)
- [ ] [2017: Unsupervised learning of visual representations by solving jigsawpuzzles](https://arxiv.org/abs/1603.09246)
- [ ] [2015: Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks](https://arxiv.org/abs/1406.6909)
- [ ] [2010: Noise-contrastive estimation: A new estimation principle for unnormalized statistical models](http://proceedings.mlr.press/v9/gutmann10a/gutmann10a.pdf)