- [D] How to integrate ViT into U-Net using this library? https://github.com/lucidrains/vit-pytorch#vision-transformer-for-small-datasets 3 comments machinelearning
Linking pages
- GitHub - cmhungsteve/Awesome-Transformer-Attention: An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites https://github.com/cmhungsteve/Awesome-Transformer-Attention 13 comments
- GitHub - sushant097/30-Days-GANs-Paper-Reading: 30 Days GANs Paper Reading https://github.com/sushant097/30-Days-GANs-Paper-Reading 7 comments
- Vision Transformers in PyTorch. When convolutions stopped being a… | by Ta-Ying Cheng | Towards Data Science https://taying-cheng.medium.com/vision-transformers-in-pytorch-43d13cb7ec7a 3 comments
- GitHub - thuanz123/enhancing-transformers: An unofficial implementation of both ViT-VQGAN and RQ-VAE in Pytorch https://github.com/thuanz123/enhancing-transformers 3 comments
- GitHub - roboflow/notebooks: Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM. https://github.com/roboflow/notebooks 1 comment
- GitHub - aqibsaeed/Sensor-Transformer: Transformer Network for Time-Series, Sensor and Wearable Data https://github.com/aqibsaeed/Sensor-Transformer 0 comments
- GitHub - ml-tooling/best-of-ml-python: 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly. https://github.com/ml-tooling/best-of-ml-python 0 comments
- GitHub - xxxnell/how-do-vits-work: (ICLR 2022 Spotlight) Official PyTorch implementation of "How Do Vision Transformers Work?" https://github.com/xxxnell/how-do-vits-work 0 comments
- Papers with Code 2021 : A Year in Review | by elvis | PapersWithCode | Medium https://medium.com/paperswithcode/papers-with-code-2021-a-year-in-review-de75d5a77b8b 0 comments
Linked pages
- Transformers from scratch | peterbloem.nl http://peterbloem.nl/blog/transformers 40 comments
- GitHub - lucidrains/x-transformers: A simple but complete full-attention transformer with a set of promising experimental features from various papers https://github.com/lucidrains/x-transformers 40 comments
- The Illustrated Transformer – Jay Alammar – Visualizing machine learning one concept at a time. https://jalammar.github.io/illustrated-transformer/ 36 comments
- [2103.14030] Swin Transformer: Hierarchical Vision Transformer using Shifted Windows https://arxiv.org/abs/2103.14030 20 comments
- [2111.06377] Masked Autoencoders Are Scalable Vision Learners https://arxiv.org/abs/2111.06377 5 comments
- [2103.15691] ViViT: A Video Vision Transformer https://arxiv.org/abs/2103.15691 4 comments
- The Annotated Transformer https://nlp.seas.harvard.edu/2018/04/03/attention.html 3 comments
- [2105.12723] Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual Understanding https://arxiv.org/abs/2105.12723 3 comments
- [2104.14294] Emerging Properties in Self-Supervised Vision Transformers https://arxiv.org/abs/2104.14294 3 comments
- [2102.03902] Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention https://arxiv.org/abs/2102.03902 2 comments
- GitHub - rwightman/pytorch-image-models: PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more https://github.com/rwightman/pytorch-image-models 2 comments
- [2103.17239] Going deeper with Image Transformers https://arxiv.org/abs/2103.17239 1 comment
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