Ood Benchmarks
Out-of-distribution generalization benchmarks for image recognition models
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Robustness | 728 | 2 years ago | 3 | October 06, 2018 | 3 | apache-2.0 | Python | |||
| Corruption and Perturbation Robustness (ICLR 2019) | ||||||||||
| Fastervit | 539 | 3 months ago | 19 | September 01, 2023 | 5 | other | Python | |||
| [ICLR 2024] Official PyTorch implementation of FasterViT: Fast Vision Transformers with Hierarchical Attention | ||||||||||
| Fishnet | 511 | 5 years ago | Python | |||||||
| Implementation code of the paper: FishNet: A Versatile Backbone for Image, Region, and Pixel Level Prediction, NeurIPS 2018 | ||||||||||
| Keras Unet Collection | 428 |  | 4 | a year ago | 32 | January 10, 2022 | 28 | mit | Python | |
| The Tensorflow, Keras implementation of U-net, V-net, U-net++, UNET 3+, Attention U-net, R2U-net, ResUnet-a, U^2-Net, TransUNET, and Swin-UNET with optional ImageNet-trained backbones. | ||||||||||
| Gcvit | 399 | 4 months ago | 1 | other | Python | |||||
| [ICML 2023] Official PyTorch implementation of Global Context Vision Transformers | ||||||||||
| Fan | 389 | 2 years ago | 4 | other | Python | |||||
| Official PyTorch implementation of Fully Attentional Networks | ||||||||||
| Dfanet | 175 | 4 years ago | 30 | Python | ||||||
| reimpliment of DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation | ||||||||||
| Bonnetal | 167 | 4 years ago | 10 | mit | Python | |||||
| Bonnet and then some! Deep Learning Framework for various Image Recognition Tasks. Photogrammetry and Robotics Lab, University of Bonn | ||||||||||
| Moganet | 100 | 4 months ago | apache-2.0 | Jupyter Notebook | ||||||
| [ICLR 2024] MogaNet: Efficient Multi-order Gated Aggregation Network | ||||||||||
| Negative Margin.few Shot | 99 | 3 years ago | other | Python | ||||||
| PyTorch implementation of “Negative Margin Matters: Understanding Margin in Few-shot Classification” | ||||||||||
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