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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.

For more details, see our paper on Spectral and Polarization Vision: Spectro-polarimetric Real-world Dataset.

πŸ“¦ Contents

πŸ’Ύ File Hierarchy

  • πŸ“‚ trichromatic/: Trichromatic polarimetric dataset

    • πŸ“‚ original/: Data processed from captured raw files
      • πŸ“„ 0000.npy ~
    • πŸ“‚ denoised/: Data processed from denoised raw files
      • πŸ“„ 0000.npy ~
    • πŸ“‚ mask/: Masks for the scenes
      • πŸ“„ 0000.png ~
    • πŸ“„ labeling_trichromatic.csv: Labeling each scene
  • πŸ“‚ hyperspectral/: Hyperspectral polarimetric dataset

    • πŸ“‚ original/: Data processed from captured raw files
      • πŸ“„ 0000.npy ~
    • πŸ“‚ denoised/: Data processed from denoised raw files
      • πŸ“„ 0000.npy ~
    • πŸ“‚ mask/: Mask fors the scenes
      • πŸ“„ 0000.png ~
    • πŸ“„ labeling_hyperspectral.csv: Labeling each scene
  • πŸ“„ README.md

πŸ“· Trichromatic Data Overview

  • original & denoised:

    • Format: Stokes numpy files (1900, 2100, 4, 3)
    • Dimensions:
      • R: Spatial dimension
      • C: Spatial dimension
      • s: Stokes axis (s0, s1, s2, s3)
      • c: Spectral axis (R G B)
  • mask:

    • Binary mask images (1900, 2100)
    • Dimensions:
      • R: Spatial dimension
      • C: Spatial dimension

πŸ“· Hyperspectral Data Overview

  • original & denoised:

    • Format: Stokes numpy files (512, 612, 4, 21)
    • Dimensions:
      • R: Spatial dimension
      • C: Spatial dimension
      • s: Stokes axis (s0, s1, s2, s3)
      • c: Spectral axis (450nm ~ 650nm at 10nm intervals)
  • mask:

    • Binary mask images (512, 612)
    • Dimensions:
      • R: Spatial dimension
      • C: Spatial dimension

πŸ—‚οΈ Labeling Information

  • SceneNum: Indices of scenes (0 ~ 310 for hyperspectral, 0 ~ 2021 for trichromatic)
  • Content: Type of content (scene, object)
  • Timezone: Scene environment (indoor, day, night)
  • Illumination: Illumination condition (white, yellow, sunny, cloudy)

πŸ“œ Citation

@misc{jeon2023spectral,
      title={Spectral and Polarization Vision: Spectro-polarimetric Real-world Dataset}, 
      author={Yujin Jeon and Eunsue Choi and Youngchan Kim and Yunseong Moon and Khalid Omer and Felix Heide and Seung-Hwan Baek},
      year={2023},
      eprint={2311.17396},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

πŸ“« Contact

If you have any questions, please contact

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