| --- |
| license: mit |
| task_categories: |
| - image-classification |
| language: |
| - en |
| tags: |
| - Multi-Scale |
| - ImageNet |
| - Equivariance |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| | Global Scaling | Local Scaling | |
| |----------------|---------------| |
| | <img src="https://raw.githubusercontent.com/ashiq24/local-scale-equivariance/refs/heads/gh-pages/assets/bird_1_gscale.gif" width="450"/> | <img src="https://raw.githubusercontent.com/ashiq24/local-scale-equivariance/refs/heads/gh-pages/assets/bird_1.gif" width="450"/> | |
|
|
| # Multi-Scale_ImageNet |
| The dataset contains multi-scale ImageNet from **Local Scale Equivariance with Latent Deep Equilibrium Canonicalizer**. |
| |
| The dataset generating pipeline is provided here: https://github.com/ashiq24/local-scale-equivariance/tree/main/datagen_ImNet |
|
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| ## Pipeline Overview |
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| If you use this dataset, please consider citing |
|
|
| ``` |
| @inproceedings{rahman2025local, |
| title={Local Scale Equivariance with Latent Deep Equilibrium Canonicalizer}, |
| author={Rahman, Md Ashiqur and Yang, Chiao-An and Cheng, Michael N. and Lim, Jun Hao and Jiang, Jeremiah and Lim, Teck-Yian and Yeh, Raymond A.}, |
| booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, |
| year={2025} |
| } |
| ``` |
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