self-supervised
dino
self-supervised | dino | |
---|---|---|
2 | 7 | |
129 | 6,549 | |
3.1% | 1.1% | |
0.0 | 0.0 | |
about 2 years ago | 7 months ago | |
Python | Python | |
- | Apache License 2.0 |
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self-supervised
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[P] solo-learn: a library of self-supervised methods for visual representation learning
W-MSE
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[R] ICLR rejected the submission only for missing large-scale ImageNet experiments
https://github.com/htdt/self-supervised it includes our method, byol and contrastive. I tried to keep the code nice and clean.
dino
- Batch-wise processing or image-by-image processing? (DINO V1)
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[P] Image search with localization and open-vocabulary reranking.
I also implemented one based on the self attention maps from the DINO trained ViT’s. This worked pretty well when the attention maps were combined with some traditional computer vision to get bounding boxes. It seemed an ok compromise between domain specialization and location specificity. I did not try any saliency or gradient based methods as i was not sure on generalization and speed respectively. I know LAVIS has an implementation of grad cam and it seems to work well in the plug'n'play vqa.
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Unsupervised semantic segmentation
You will probably need an unwieldy amount of data and compute to reproduce it, so your best option would be to use the pretrained models available on github.
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[D] Why Transformers are taking over the Compute Vision world: Self-Supervised Vision Transformers with DINO explained in 7 minutes!
[Full Explanation Post] [Arxiv] [Project Page]
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A major part of real-world AI has to be solved to make unsupervised, generalized full self-driving work, as the entire road system is designed for biological neural nets with optical imagers
Except he is actually talking about the new DINO model created by facebook that was released on friday. Which is a new approach to image transformers for unsupervised segmentation. Here's its github.
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[D] Paper Explained - DINO: Emerging Properties in Self-Supervised Vision Transformers (Full Video Analysis)
Code: https://github.com/facebookresearch/dino
- [R] DINO and PAWS: Advancing the state of the art in computer vision with self-supervised Transformers
What are some alternatives?
Unsupervised-Classification - SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
simsiam-cifar10 - Code to train the SimSiam model on cifar10 using PyTorch
PASS - The PASS dataset: pretrained models and how to get the data
pytorch-metric-learning - The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
Revisiting-Contrastive-SSL - Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]
lightly - A python library for self-supervised learning on images.
Unsupervised-Semantic-Segmentation - Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals. [ICCV 2021]
Transformer-SSL - This is an official implementation for "Self-Supervised Learning with Swin Transformers".
PaddleHelix - Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
unsupervised-depth-completion-visual-inertial-odometry - Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)
transferlearning - Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
solo-learn - solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning