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https://github.com/asheeshcric/awesome-contrastive-self-supervised-learning

A comprehensive list of awesome contrastive self-supervised learning papers.
https://github.com/asheeshcric/awesome-contrastive-self-supervised-learning

List: awesome-contrastive-self-supervised-learning

deep-learning hacktoberfest-accepted representation-learning self-supervised-learning transfer-learning unsupervised-learning

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A comprehensive list of awesome contrastive self-supervised learning papers.

Host: GitHub
URL: https://github.com/asheeshcric/awesome-contrastive-self-supervised-learning
Owner: asheeshcric
Created: 2020-06-10T18:20:33.000Z (over 4 years ago)
Default Branch: master
Last Pushed: 2024-05-18T23:20:55.000Z (7 months ago)
Last Synced: 2024-05-19T20:52:42.264Z (7 months ago)
Topics: deep-learning, hacktoberfest-accepted, representation-learning, self-supervised-learning, transfer-learning, unsupervised-learning
Homepage:
Size: 85.9 KB
Stars: 1,146
Watchers: 37
Forks: 123
Open Issues: 0
Metadata Files:
- Readme: README.md

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README

        

# Awesome CONTRASTIVE LEARNING [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](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)

#### 2024

- [ ] [2024: Topic Modeling as Multi-Objective Contrastive Optimization](https://arxiv.org/abs/2402.07577)

- [ ] [2024: Demonstrating and Reducing Shortcuts in Vision-Language Representation Learning](https://arxiv.org/abs/2402.17510) [[Code]](https://github.com/MauritsBleeker/svl-framework)

- [ ] [2024: VoCo: A Simple-yet-Effective Volume Contrastive Learning Framework for 3D Medical Image Analysis](https://arxiv.org/abs/2402.17300) [[Code]](https://github.com/Luffy03/VoCo)

- [ ] [2024: Multi-Grained Contrast for Data-Efficient Unsupervised Representation Learning](https://arxiv.org/abs/2407.02014) [[Code]](https://github.com/visresearch/mgc)

- [ ] [2024: Kdmcse: Knowledge distillation multimodal sentence embeddings with adaptive angular margin contrastive learning](https://arxiv.org/abs/2403.17486) [[Code]](https://github.com/duyngtr16061999/kdmcse)

#### 2023

- [ ] [2023: Improving multimodal sentiment analysis: Supervised angular margin-based contrastive learning for enhanced fusion representation](https://aclanthology.org/2023.findings-emnlp.980/)

- [ ] [2023: Inter-Instance Similarity Modeling for Contrastive Learning](https://arxiv.org/abs/2306.12243) [[Code]](https://github.com/visresearch/patchmix)

- [ ] [2023: Asymmetric Patch Sampling for Contrastive Learning](https://arxiv.org/abs/2306.02854) [[Code]](https://github.com/visresearch/aps)

- [ ] [2023: Randomized Schur Complement Views for Graph Contrastive Learning](https://arxiv.org/abs/2306.04004) [[Code]](https://github.com/kvignesh1420/rlap)

#### 2022

- [ ] [2022: Adaptive Contrastive Learning on Multimodal Transformer for Review Helpfulness Predictions](https://arxiv.org/abs/2211.03524) [[Code]](https://github.com/nguyentthong/adaptive_contrastive_mrhp)

- [ ] [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: Contrastive Learning for Neural Topic Model](https://arxiv.org/abs/2110.12764) [[Code]](https://github.com/nguyentthong/CLNTM)

- [ ] [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)

## Star History