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awesome-self-supervised-vision
Awesome Self-Supervised Vision Learning
https://github.com/fawazsammani/awesome-self-supervised-vision
Last synced: 5 days ago
JSON representation
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Papers
- t-ReX - vision/improving-the-generalization-of-supervised-models/)
- DeepCluster
- MoBY - SSL)
- ReSim - Xiao/ReSim)
- CLSA - research-lab/CLSA)
- 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 - supervised-relational-reasoning)
- [pdf - vision/mochi/)
- [pdf - Learning-with-Non-Semantic-Negatives)
- 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
- SEERv1
- Restormer
- RELICv2
- DnC
- VICReg
- I-JEPA - lecun-ai-model-i-jepa/)
- CorInfoMax
- All4One
- MOKD
- SiameseIM - Image-Modeling)
- CIM - Image-Modeling)
- [pdf - Learning-with-Non-Semantic-Negatives)
- IP-IRM - CN/IP-IRM)
- BatchFormer
- CaCo - research-lab/caco)
- VICRegL
- [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)
- [pdf - research/compressive-visual-representations)
- 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)
- 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)
- 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 - 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
- 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/)
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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
Categories
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