Datasets › Polarized Film Removal Dataset

Polarized Film Removal Dataset

Introduced by Jiaqi Tang et al. in Learning to Remove Wrinkled Transparent Film with Polarized Prior30 Apr 2024 archive 2025-07-28

The current industrial pipeline includes 315 dynamic industrial scenarios, which can be categorized into three types: QR codes, text, and products. To enhance the diversity, we have different films with diverse material properties, coverage areas, film thicknesses, and levels of wrinkling. The film exhibits significant variability across each scenario. On the other hand, to ensure the stability of the industrial imaging pipeline, we maintained a consistent intensity level for the industrial light source and fixed the distance between the camera and the object flow. This helps to minimize the influence of errors external to the industrial system.

Benchmarks archive 2025-07-28

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Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

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Tasks archive 2025-07-28

License archive 2025-07-28

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Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • Polarized Film Removal Dataset

1 variant name, as the archive lists them.

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