AdCo
solo-learn
| AdCo | solo-learn | |
|---|---|---|
| 2 | 3 | |
| 161 | 1,358 | |
| 0.0% | - | |
| 0.9 | 5.9 | |
| about 1 year ago | 9 days ago | |
| Python | Python | |
| MIT License | MIT License |
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AdCo
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[D] Negative examples are still useful in self-supervised learning even after the BYOL, and they are directly trainable end-to-end with a backbone.
The paper showed that with only 8196 negatives, the AdCo can achieve better performance than the SOTA self-supervised methods (MoCo V2, SimCLR, AdCo and SWAV) with fewer epochs, thus making the AdCo a very efficient self-supervised learning algorithm to pretrain a backbone. The source code has been released at https://github.com/maple-research-lab/AdCo.
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[R] AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries
The source code is available at https://github.com/maple-research-lab/AdCo/. The paper will be presented at CVPR 2021.
solo-learn
- [D]Use SimCLR as pretraining for image segmentation
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[D] State-of-the-Art for Self-Supervised (Pre-)Training of CNN architectures (e.g. ResNet)?
Hello, I lost a bit of touch to the current SOTA of self-supervised pretraining of CNNs, in particular ResNet. I found this repository https://github.com/vturrisi/solo-learn that has many methods implemented but I'm not really sure where to start. My goal is to pretrain a ResNet backbone on a decently large amount of image data that comes from a certain domain and after that fine-tune it for different downstream tasks (classification, segmentation, object detection) on a subset of the data I have labels for.
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[P] Solo-learn 1.0.3: new methods, support for transformer architectures, better evaluation, improved docs, and additional results.
Hi Reddit, the solo-learn team is back again with interesting news about its SSL library.
What are some alternatives?
Unsupervised-Classification - SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
dino - PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
lightning-transformers - Flexible components pairing 🤗 Transformers with :zap: Pytorch Lightning
contrastive-reconstruction - Tensorflow-keras implementation for Contrastive Reconstruction (ConRec) : a self-supervised learning algorithm that obtains image representations by jointly optimizing a contrastive and a self-reconstruction loss.
Revisiting-Contrastive-SSL - Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]
Unsupervised-Semantic-Segmentation - Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals. [ICCV 2021]
CEBRA - Learnable latent embeddings for joint behavioral and neural analysis - Official implementation of CEBRA
vectorrvnn - Data Driven method for hierarchical grouping of paths in Vector Graphics.
detrex - detrex is a research platform for DETR-based object detection, segmentation, pose estimation and other visual recognition tasks.
pytorch-forecasting - Time series forecasting with PyTorch
mmselfsup - OpenMMLab Self-Supervised Learning Toolbox and Benchmark