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--- |
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size_categories: |
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- 100B<n<1T |
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--- |
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# Spectro-polarimetric Dataset |
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We provide a spectro-polarimetric dataset. This dataset consists of full-Stokes images for both hyperspectral and trichromatic scenes. Hyperspectral dataset has 311 scenes and trichromatic dataset has 2022 scenes. |
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For more details, see our paper on [<u>**Spectral and Polarization Vision: Spectro-polarimetric Real-world Dataset**</u>](https://arxiv.org/abs/2311.17396). |
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## 📦 Contents |
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- [**File Hierarchy** ](#💾-file-hierarchy) |
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- [**Trichromatic Data Overview** ](#📷-trichromatic-data-overview) |
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- [**Hyperspectral Data Overview** ](#📷-hyperspectral-data-overview) |
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- [**Labeling Information** ](#🗂️-labeling-information) |
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- [**Citation** ](#📜-citation) |
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- [**Contact** ](#📫-contact) |
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## 💾 File Hierarchy |
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- ### **📂 trichromatic/**: Trichromatic polarimetric dataset |
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- **📂 original/**: Data processed from captured raw files |
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- **📄 0000.npy ~** |
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- **📂 denoised/**: Data processed from denoised raw files |
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- **📄 0000.npy ~** |
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- **📂 mask/**: Masks for the scenes |
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- **📄 0000.png ~** |
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- **📄 labeling_trichromatic.csv**: Labeling each scene |
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- ### **📂 hyperspectral/**: Hyperspectral polarimetric dataset |
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- **📂 original/**: Data processed from captured raw files |
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- **📄 0000.npy ~** |
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- **📂 denoised/**: Data processed from denoised raw files |
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- **📄 0000.npy ~** |
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- **📂 mask/**: Mask fors the scenes |
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- **📄 0000.png ~** |
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- **📄 labeling_hyperspectral.csv**: Labeling each scene |
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- ### **📄 README.md** |
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## 📷 Trichromatic Data Overview |
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+ **original & denoised:** |
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- Format: Stokes numpy files `(1900, 2100, 4, 3)` |
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- Dimensions: |
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- **R:** Spatial dimension |
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- **C:** Spatial dimension |
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- **s:** Stokes axis (*s0, s1, s2, s3*) |
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- **c:** Spectral axis (R G B) |
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+ **mask:** |
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- Binary mask images `(1900, 2100)` |
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- Dimensions: |
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- **R:** Spatial dimension |
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- **C:** Spatial dimension |
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## 📷 Hyperspectral Data Overview |
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+ **original & denoised:** |
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- Format: Stokes numpy files `(512, 612, 4, 21)` |
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- Dimensions: |
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- **R:** Spatial dimension |
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- **C:** Spatial dimension |
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- **s:** Stokes axis (*s0, s1, s2, s3*) |
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- **c:** Spectral axis (`450nm ~ 650nm` at `10nm` intervals) |
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+ **mask:** |
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- Binary mask images `(512, 612)` |
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- Dimensions: |
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- **R:** Spatial dimension |
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- **C:** Spatial dimension |
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## 🗂️ Labeling Information |
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- **SceneNum:** Indices of scenes (`0 ~ 310` for hyperspectral, `0 ~ 2021` for trichromatic) |
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- **Content:** Type of content (scene, object) |
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- **Timezone:** Scene environment (indoor, day, night) |
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- **Illumination:** Illumination condition (white, yellow, sunny, cloudy) |
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## 📜 Citation |
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```bibtex |
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@InProceedings{Jeon_2024_CVPR, |
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author = {Jeon, Yujin and Choi, Eunsue and Kim, Youngchan and Moon, Yunseong and Omer, Khalid and Heide, Felix and Baek, Seung-Hwan}, |
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title = {Spectral and Polarization Vision: Spectro-polarimetric Real-world Dataset}, |
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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 = {22098-22108} |
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} |
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``` |
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## 📫 Contact |
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If you have any questions, please contact |
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+ Yujin Jeon: [email protected] |
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+ Eunsue Choi: [email protected] |
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+ Seung-hwan Baek: [email protected] |
