Unsupervised-Semantic-Segmentation
solo-learn
| Unsupervised-Semantic-Segmentation | solo-learn | |
|---|---|---|
| 1 | 3 | |
| 386 | 1,357 | |
| - | - | |
| 1.8 | 5.9 | |
| almost 2 years ago | 5 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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Unsupervised-Semantic-Segmentation
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Unsupervised semantic segmentation
Check out these unsupervised masks created in exactly such way in this paper. They are nearly perfect
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?
mmselfsup - OpenMMLab Self-Supervised Learning Toolbox and Benchmark
dino - PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
Unsupervised-Classification - SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
lightning-transformers - Flexible components pairing 🤗 Transformers with :zap: Pytorch Lightning
DA-RetinaNet - Official Detectron2 implementation of DA-RetinaNet of our Image and Vision Computing 2021 work 'An unsupervised domain adaptation scheme for single-stage artwork recognition in cultural sites'
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.
DiffCSE - Code for the NAACL 2022 long paper "DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings"
Revisiting-Contrastive-SSL - Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]
PASS - The PASS dataset: pretrained models and how to get the data
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.