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--- |
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license: cc-by-4.0 |
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task_categories: |
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- image-classification |
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language: |
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- en |
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tags: |
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- benchmark |
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- image-classification |
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- out-of-distribution |
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- robustness |
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- sensor-control |
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- light-control |
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- real-photo |
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size_categories: |
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- 100K<n<1M |
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--- |
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# 📸 ImageNet-ES |
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Unlike conventional robustness benchmarks that rely on digital perturbations, we directly capture **202k images** by using a real camera in a controllable testbed. **The dataset presents a wide range of covariate shifts caused by variations in light and camera sensor factors.** |
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[📄 Read the paper (CVPR 2024)](https://openaccess.thecvf.com/content/CVPR2024/html/Baek_Unexplored_Faces_of_Robustness_and_Out-of-Distribution_Covariate_Shifts_in_Environment_CVPR_2024_paper.html) |
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<img align="center" src="https://raw.githubusercontent.com/Edw2n/ImageNet-ES/main/supples/ImageNet-ES.jpg" width="800"> |
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--- |
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### 🗂️ ImageNet-ES Strucuture |
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``` |
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ImageNet-ES |
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├── es-train |
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│ └── tin_no_resize_sample_removed |
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│ # 8K original validation samples of Tiny-ImageNet without references |
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├── es-val |
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│ ├── auto_exposure # 10K = 1K reference samples * 2 environments * 5 shots |
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│ ├── param_control # 128K = 1K reference samples * 2 environments * 64 shots |
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│ └── sampled_tin_no_resize # reference samples (1K) |
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├── es-test |
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├── auto_exposure # 10K = 1K reference samples * 2 environments * 5 shots |
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├── param_control # 54K = 1K reference samples * 2 environments * 27 shots |
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└── sampled_tin_no_resize2 # reference samples (1K) |
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``` |
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The main paper and the appendix detail the dataset specifications and present analyses on covariate shifts, robustness evaluations, and qualitative insights. |
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--- |
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### 🎛️ ES-Studio |
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To compensate the missing perturbations in current robustness benchmarks, we construct a new testbed, **ES-Studio** (**E**nvironment and camera **S**ensor perturbation **Studio**). It can control physical light and camera sensor parameters during data collection. |
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<img align="center" src="https://raw.githubusercontent.com/Edw2n/ImageNet-ES/main/supples/Testbed.png" width="800"> |
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<img align="center" src="https://raw.githubusercontent.com/Edw2n/ImageNet-ES/main/supples/Testbed_actual.jpg" width="800"> |
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--- |
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### 🖥️ Download from terminal |
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To download the dataset directly from your terminal using **`wget`:** |
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```bash |
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wget https://huggingface.co/datasets/Edw2n/ImageNet-ES/resolve/main/ImageNet-ES.zip |
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``` |
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--- |
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### 🔍 More Exploration |
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Visit our paper repository: [🔗 ImageNet-ES GitHub Repository](https://github.com/Edw2n/ImageNet-ES) |
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--- |
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### 📜 Citation |
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```bibtex |
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@InProceedings{Baek_2024_CVPR, |
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author = {Baek, Eunsu and Park, Keondo and Kim, Jiyoon and Kim, Hyung-Sin}, |
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title = {Unexplored Faces of Robustness and Out-of-Distribution: Covariate Shifts in Environment and Sensor Domains}, |
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booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, |
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month = {June}, |
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year = {2024}, |
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pages = {22294--22303} |
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} |
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``` |
