| --- |
| license: cc-by-4.0 |
| task_categories: |
| - image-classification |
| language: |
| - en |
| tags: |
| - benchmark |
| - image-classification |
| - out-of-distribution |
| - robustness |
| - sensor-control |
| - light-control |
| - real-photo |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # 📸 ImageNet-ES |
| 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.** |
| [📄 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) |
| <img align="center" src="https://raw.githubusercontent.com/Edw2n/ImageNet-ES/main/supples/ImageNet-ES.jpg" width="800"> |
|
|
| --- |
| ### 🗂️ ImageNet-ES Strucuture |
| ``` |
| ImageNet-ES |
| ├── es-train |
| │ └── tin_no_resize_sample_removed |
| │ # 8K original validation samples of Tiny-ImageNet without references |
| ├── es-val |
| │ ├── auto_exposure # 10K = 1K reference samples * 2 environments * 5 shots |
| │ ├── param_control # 128K = 1K reference samples * 2 environments * 64 shots |
| │ └── sampled_tin_no_resize # reference samples (1K) |
| ├── es-test |
| ├── auto_exposure # 10K = 1K reference samples * 2 environments * 5 shots |
| ├── param_control # 54K = 1K reference samples * 2 environments * 27 shots |
| └── sampled_tin_no_resize2 # reference samples (1K) |
| ``` |
| The main paper and the appendix detail the dataset specifications and present analyses on covariate shifts, robustness evaluations, and qualitative insights. |
|
|
| --- |
| ### 🎛️ ES-Studio |
| 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. |
| <img align="center" src="https://raw.githubusercontent.com/Edw2n/ImageNet-ES/main/supples/Testbed.png" width="800"> |
| <img align="center" src="https://raw.githubusercontent.com/Edw2n/ImageNet-ES/main/supples/Testbed_actual.jpg" width="800"> |
|
|
| --- |
| ### 🖥️ Download from terminal |
| To download the dataset directly from your terminal using **`wget`:** |
| ```bash |
| wget https://huggingface.co/datasets/Edw2n/ImageNet-ES/resolve/main/ImageNet-ES.zip |
| ``` |
|
|
| --- |
| ### 🔍 More Exploration |
| Visit our paper repository: [🔗 ImageNet-ES GitHub Repository](https://github.com/Edw2n/ImageNet-ES) |
|
|
| --- |
| ### 📜 Citation |
| ```bibtex |
| @InProceedings{Baek_2024_CVPR, |
| author = {Baek, Eunsu and Park, Keondo and Kim, Jiyoon and Kim, Hyung-Sin}, |
| title = {Unexplored Faces of Robustness and Out-of-Distribution: Covariate Shifts in Environment and Sensor Domains}, |
| booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, |
| month = {June}, |
| year = {2024}, |
| pages = {22294--22303} |
| } |
| ``` |
