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awesome-self-supervised-vision

Awesome Self-Supervised Vision Learning
https://github.com/fawazsammani/awesome-self-supervised-vision

Last synced: about 21 hours ago
JSON representation

  • Papers

    • t-ReX - vision/improving-the-generalization-of-supervised-models/)
    • DeepCluster
    • [pdf
    • MoBY - SSL)
    • ReSim - Xiao/ReSim)
    • CLSA - research-lab/CLSA)
    • [pdf
    • RELICv2
    • CaCo - research-lab/caco)
    • DnC
    • SimCLR - research/simclr) [[code]](https://github.com/leftthomas/SimCLR) [[code]](https://github.com/ae-foster/pytorch-simclr) [[code]](https://github.com/sthalles/SimCLR) [[code]](https://github.com/AndrewAtanov/simclr-pytorch) [[code]](https://github.com/tonylins/simclr-converter) [[video]](https://www.youtube.com/watch?v=a7-qwwAFs_s&t=215s) [[video]](https://www.youtube.com/watch?v=YZgeWsuyRH8&ab_channel=AIBites)
    • SimCLRv2 - research/simclr) [[code]](https://github.com/Separius/SimCLRv2-Pytorch) [[video]](https://www.youtube.com/watch?v=2lkUNDZld-4&ab_channel=YannicKilcher)
    • BYOL - BYOL) [[code]](https://github.com/lucidrains/byol-pytorch) [[video]](https://www.youtube.com/watch?v=YPfUiOMYOEE&t=1813s&ab_channel=YannicKilcher)
    • BYOL does not work
    • BYOL works!
    • DeepCluster
    • DeeperCluster
    • SWAV - YangFu)
    • SimSiam
    • MoCo - notebook/colab/moco_cifar10_demo.ipynb)
    • MoCo v2
    • MoCo v3 - v3)
    • DINO - code]](https://www.youtube.com/watch?v=hNf6RNHKnE4&t=19s&ab_channel=TheAIEpiphany) [[video-code]](https://www.youtube.com/watch?v=psmMEWKk4Uk&t=1082s&ab_channel=mildlyoverfitted)
    • TWIST
    • EsViT
    • iBOT
    • SiT - Ahmed/SiT)
    • Asym-Siam - siam)
    • DetCon - pytorch) [[video]](https://www.youtube.com/watch?v=oPfu_Ec5u60&t=1225s&ab_channel=TheAIEpiphany)
    • MoBY - SSL)
    • CARE
    • ContrastiveCrop
    • SDMP
    • ImageGPT - gpt) [[code]](https://github.com/karpathy/minGPT) [[code]](https://github.com/teddykoker/image-gpt) [[website]](https://openai.com/blog/image-gpt/) [[video]](https://www.youtube.com/watch?v=YBlNQK0Ao6g&ab_channel=YannicKilcher)
    • ReSSL
    • DCL - Contrastive-Learning)
    • LEWEL
    • MSF
    • SWAG
    • ISD
    • Self-Label - label)
    • InfoCL - Wang/InfoCL)
    • DenseCL
    • FlatNCE - Chen/FlatCLR)
    • ARB
    • SelfPatch
    • EMAN - research/exponential-moving-average-normalization)
    • MPL - pytorch)
    • RINCE
    • CoKe
    • ReSim - Xiao/ReSim)
    • CAST
    • LoGo - SSL)
    • CsMl
    • SetSim
    • UniVIP
    • Dual Temperature - temperature)
    • DATA - vision/GAIA-ssl)
    • SaGe
    • MST
    • IP-IRM - CN/IP-IRM)
    • SSL-HSIC
    • JigClu - research/JigsawClustering)
    • SelfAugment
    • ProtoNCE
    • OBoW
    • SEERv1
    • SEERv2
    • CLSA - research-lab/CLSA)
    • VICReg
    • VQ-VAE - vq-vae) [[code]](https://github.com/lucidrains/vector-quantize-pytorch) [[code]](https://github.com/karpathy/deep-vector-quantization) [[code]](https://github.com/openai/DALL-E) [[code]](https://github.com/ritheshkumar95/pytorch-vqvae) [[code]](https://github.com/nadavbh12/VQ-VAE) [[code]](https://github.com/nakosung/VQ-VAE) [[code]](https://juliusruseckas.github.io/ml/vq-vae.html) [[code]](https://github.com/AntixK/PyTorch-VAE/blob/master/models/vq_vae.py) [[colab]](https://colab.research.google.com/github/zalandoresearch/pytorch-vq-vae/blob/master/vq-vae.ipynb) [[video]](https://www.youtube.com/watch?v=VZFVUrYcig0&ab_channel=TheAIEpiphany) [[blog]](https://ml.berkeley.edu/blog/posts/vq-vae/)
    • VQ-VAE-2 - vae-2-pytorch) [[code]](https://github.com/vvvm23/vqvae-2) [[code]](https://github.com/lucidrains/vector-quantize-pytorch)
    • VQ-GAN - transformers) [[code]](https://github.com/dome272/VQGAN-pytorch) [[website]](https://compvis.github.io/taming-transformers/) [[video]](https://www.youtube.com/watch?v=j2PXES-liuc&t=2s&ab_channel=TheAIEpiphany) [[video]](https://www.youtube.com/watch?v=wcqLFDXaDO8&ab_channel=Outlier) [[video]](https://www.youtube.com/watch?v=-wDSDtIAyWQ&ab_channel=GradientDude) [[video code]](https://www.youtube.com/watch?v=_Br5WRwUz_U&ab_channel=Outlier) [[blog]](https://ljvmiranda921.github.io/notebook/2021/08/08/clip-vqgan/) [[ViT-VQGAN]](https://arxiv.org/pdf/2110.04627.pdf)
    • CycleGAN - CycleGAN-and-pix2pix) [[code]](https://github.com/eriklindernoren/PyTorch-GAN/tree/master/implementations/cyclegan) [[code]](https://github.com/leftthomas/CycleGAN) [[code]](https://nn.labml.ai/gan/cycle_gan/index.html)
    • Restormer
    • MC-SSL0.0
    • t-ReX - vision/improving-the-generalization-of-supervised-models/)
    • HCSC - team/HCSC)
    • BatchFormer
    • Mugs - sg/mugs)
    • LIFT - Madison-Lee-Lab/LanguageInterfacedFineTuning)
    • VICReg
    • VICRegL
    • Propagate Yourself
    • SDCLR - Group/SDCLR)
    • I-JEPA - lecun-ai-model-i-jepa/)
    • CorInfoMax
    • All4One
    • SimDis
    • MOKD
    • SiameseIM - Image-Modeling)
    • MixedAE
    • CIM - Image-Modeling)
    • VD
    • [pdf
    • [pdf
    • [pdf - supervised-relational-reasoning)
    • [pdf
    • [pdf
    • [pdf
    • [pdf
    • [pdf
    • [pdf - vision/mochi/)
    • [pdf - Learning-with-Non-Semantic-Negatives)
    • [pdf
    • [pdf
    • [pdf
    • SiT - Ahmed/SiT)
    • MST
    • MC-SSL0.0
    • BYOL works!
    • DeeperCluster
    • DINOv2 - v2-computer-vision-self-supervised-learning/) [[demo]](https://dinov2.metademolab.com/) [[hf notebook]](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/DINOv2)
    • TWIST
    • Asym-Siam - siam)
    • CARE
    • ContrastiveCrop
    • ReSSL
    • DCL - Contrastive-Learning)
    • LEWEL
    • FlatNCE - Chen/FlatCLR)
    • SelfPatch
    • EMAN - research/exponential-moving-average-normalization)
    • MPL - pytorch)
    • RINCE
    • CoKe
    • CsMl
    • SetSim
    • UniVIP
    • DATA - vision/GAIA-ssl)
    • SaGe
    • SSL-HSIC
    • ProtoNCE
    • OBoW
    • SEERv1
    • VQ-VAE - vq-vae) [[code]](https://github.com/lucidrains/vector-quantize-pytorch) [[code]](https://github.com/karpathy/deep-vector-quantization) [[code]](https://github.com/openai/DALL-E) [[code]](https://github.com/ritheshkumar95/pytorch-vqvae) [[code]](https://github.com/nadavbh12/VQ-VAE) [[code]](https://github.com/nakosung/VQ-VAE) [[code]](https://juliusruseckas.github.io/ml/vq-vae.html) [[code]](https://github.com/AntixK/PyTorch-VAE/blob/master/models/vq_vae.py) [[colab]](https://colab.research.google.com/github/zalandoresearch/pytorch-vq-vae/blob/master/vq-vae.ipynb) [[video]](https://www.youtube.com/watch?v=VZFVUrYcig0&ab_channel=TheAIEpiphany) [[blog]](https://ml.berkeley.edu/blog/posts/vq-vae/)
    • Restormer
    • RELICv2
    • DnC
    • VICReg
    • I-JEPA - lecun-ai-model-i-jepa/)
    • CorInfoMax
    • All4One
    • MOKD
    • SiameseIM - Image-Modeling)
    • CIM - Image-Modeling)
    • [pdf
    • [pdf
    • [pdf
    • [pdf
    • [pdf - Learning-with-Non-Semantic-Negatives)
    • [pdf
    • [pdf
    • IP-IRM - CN/IP-IRM)
    • BatchFormer
    • CaCo - research-lab/caco)
    • VICRegL
    • [pdf - research/compressive-visual-representations)
    • [pdf - research/compressive-visual-representations)
    • VQ-VAE-2 - vae-2-pytorch) [[code]](https://github.com/vvvm23/vqvae-2) [[code]](https://github.com/lucidrains/vector-quantize-pytorch)
    • JigClu - research/JigsawClustering)
    • DINOv2 - v2-computer-vision-self-supervised-learning/) [[demo]](https://dinov2.metademolab.com/) [[hf notebook]](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/DINOv2)
    • SWAG
    • SelfAugment
    • [pdf - supervised-relational-reasoning)
    • LIFT - Madison-Lee-Lab/LanguageInterfacedFineTuning)
    • InfoCL - Wang/InfoCL)
    • HCSC - team/HCSC)
    • SimCLR - research/simclr) [[code]](https://github.com/leftthomas/SimCLR) [[code]](https://github.com/ae-foster/pytorch-simclr) [[code]](https://github.com/sthalles/SimCLR) [[code]](https://github.com/AndrewAtanov/simclr-pytorch) [[code]](https://github.com/tonylins/simclr-converter) [[video]](https://www.youtube.com/watch?v=a7-qwwAFs_s&t=215s) [[video]](https://www.youtube.com/watch?v=YZgeWsuyRH8&ab_channel=AIBites)
    • SimCLRv2 - research/simclr) [[code]](https://github.com/Separius/SimCLRv2-Pytorch) [[video]](https://www.youtube.com/watch?v=2lkUNDZld-4&ab_channel=YannicKilcher)
    • BYOL - BYOL) [[code]](https://github.com/lucidrains/byol-pytorch) [[video]](https://www.youtube.com/watch?v=YPfUiOMYOEE&t=1813s&ab_channel=YannicKilcher)
    • SWAV - YangFu)
    • SimSiam
    • Barlow Twins
    • MoCo - notebook/colab/moco_cifar10_demo.ipynb)
    • MoCo v2
    • MoCo v3 - v3)
    • DINO - code]](https://www.youtube.com/watch?v=hNf6RNHKnE4&t=19s&ab_channel=TheAIEpiphany) [[video-code]](https://www.youtube.com/watch?v=psmMEWKk4Uk&t=1082s&ab_channel=mildlyoverfitted)
    • EsViT
    • iBOT
    • DetCon - pytorch) [[video]](https://www.youtube.com/watch?v=oPfu_Ec5u60&t=1225s&ab_channel=TheAIEpiphany)
    • Self-Label - label)
    • DenseCL
    • CAST
    • VICReg
    • Propagate Yourself
    • SDCLR - Group/SDCLR)
    • SimDis
    • [pdf
    • [pdf - vision/mochi/)
    • LoGo - SSL)
    • MixedAE

  • Masked Image Pretraining

    • BEiT
    • BEiT v2
    • ConvNeXt v2 - V2)
    • SparK - tian/SparK)
    • MaskFeat
    • SimMIM - pretraining)
    • GMML - Ahmed/GMML)
    • MAE - pretraining) [[code]](https://github.com/pengzhiliang/MAE-pytorch) [[code]](https://github.com/FlyEgle/MAE-pytorch) [[hf notebook]](https://github.com/NielsRogge/Transformers-Tutorials/blob/master/ViTMAE/ViT_MAE_visualization_demo.ipynb)
    • MaskFeat
    • SimMIM - pretraining)
    • Awesome Masked Autoencoders
    • BEiT
    • ConvNeXt v2 - V2)
    • SparK - tian/SparK)
    • GMML - Ahmed/GMML)
    • MAE - pretraining) [[code]](https://github.com/pengzhiliang/MAE-pytorch) [[code]](https://github.com/FlyEgle/MAE-pytorch) [[hf notebook]](https://github.com/NielsRogge/Transformers-Tutorials/blob/master/ViTMAE/ViT_MAE_visualization_demo.ipynb)
    • BEiT v2

  • Unsupervised Segmentation With/Using Self-Supervised Models

    • TransCAM
    • GroupViT
    • LOST
    • MaskContrast - Semantic-Segmentation)
    • MaskDistill
    • Leopart
    • TokenCut - psi.fr/Papers/TokenCut2022/)
    • [pdf - spectral-segmentation) [[demo]](https://huggingface.co/spaces/lukemelas/deep-spectral-segmentation) [[website]](https://lukemelas.github.io/deep-spectral-segmentation/)
    • GroupViT
    • TokenCut - psi.fr/Papers/TokenCut2022/)
    • TransCAM
    • LOST
    • MaskContrast - Semantic-Segmentation)
    • MaskDistill
    • [pdf - spectral-segmentation) [[demo]](https://huggingface.co/spaces/lukemelas/deep-spectral-segmentation) [[website]](https://lukemelas.github.io/deep-spectral-segmentation/)

  • Review Papers

  • Some Nice Resources

    • Stanford CS231n slides
    • OpenAI NeurIPS Tutorial
    • Amit Chaudhary
    • AI Summer
    • [Self-Supervised Representation Learning - 05-31-contrastive/) [[Semi-Supervised Learning]](https://lilianweng.github.io/posts/2021-12-05-semi-supervised/) [[Active Learning]](https://lilianweng.github.io/posts/2022-02-20-active-learning/) [[Data Generation]](https://lilianweng.github.io/posts/2022-04-15-data-gen/)
    • [Yuandong Tian's work
    • [blog - transport-a-hidden-gem-that-empowers-todays-machine-learning-2609bbf67e59) [[blog]](https://leimao.github.io/blog/Hungarian-Matching-Algorithm/) [[blog]](https://brilliant.org/wiki/hungarian-matching/) [[blog]](https://www.topcoder.com/thrive/articles/Assignment%20Problem%20and%20Hungarian%20Algorithm) [[blog]](https://medium.com/@riya.tendulkar/the-assignment-problem-using-hungarian-algorithm-4f105729af18)
    • [pdf - softmax-pytorch) [[blog and code]](https://neptune.ai/blog/gumbel-softmax-loss-function-guide-how-to-implement-it-in-pytorch) [[blog]](https://sassafras13.github.io/GumbelSoftmax/) [[blog]](https://towardsdatascience.com/synthetic-data-with-gumbel-softmax-activations-49e990168565) [[gumbel-softmax vae]](https://github.com/YongfeiYan/Gumbel_Softmax_VAE)
    • [pdf - softmax-pytorch) [[blog and code]](https://neptune.ai/blog/gumbel-softmax-loss-function-guide-how-to-implement-it-in-pytorch) [[blog]](https://sassafras13.github.io/GumbelSoftmax/) [[blog]](https://towardsdatascience.com/synthetic-data-with-gumbel-softmax-activations-49e990168565) [[gumbel-softmax vae]](https://github.com/YongfeiYan/Gumbel_Softmax_VAE)
    • Stanford CS231n slides

  • Libraries

  • Other Awesomes

Programming Languages
Python 5 Jupyter Notebook 1
Categories
Papers 192 Masked Image Pretraining 17 Unsupervised Segmentation With/Using Self-Supervised Models 15 Some Nice Resources 10 Review Papers 10 Libraries 6 Other Awesomes 3
Sub Categories
Keywords
self-supervised-learning 6 pytorch 4 mae 3 deep-learning 3 machine-learning 2 contrastive-learning 2 computer-vision 2 unsupervised-learning 2 simsiam 2 simclr 2 self-supervised 2 moco 2 beit 2 pixel-cnn 1 normalizing-flows 1 comparison 1 beta-vae 1 reproducibility 1 benchmarking 1 vicreg 1 vibcreg 1 transformer-models 1 swav 1 ressl 1 pytorch-lightning 1 nvidia-dali 1 nnclr 1 masked-input-prediction 1 dino 1 deepcluster 1 byol 1 barlow-twins 1 embeddings 1 contributions-welcome 1 masked-image-modeling 1 masked-autoencoder 1 minilm 1 mllm 1 multimodal 1 nlp 1 pre-trained-model 1 textdiffuser 1 trocr 1 unilm 1 xlm-e 1 natural-language-processing 1 reinforcement-learning 1 robotics 1 awesome 1 cvpr2020 1