Datasets › RB-Dust
RB-Dust (RB-Dust: Real-world Industrial Dust Dehazing Dataset)
A small-scale real-world dataset containing hazy/dusty industrial images and their clean ground truth counterparts. Designed for evaluating deep learning models for dust removal and image dehazing in industrial environments. Collected and fine-tuned by Moshtaghioun et al., 2025.
Benchmarks archive 2025-07-28
All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Image Dehazing | RB-Dust | EENet PSNR 27.45 | EENet: Frequency-Aware and Spatially Multiscale Network... | amir1373/EENet-Dehazing | 1 | Compare |
Papers archive 2025-07-28
1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 1. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| EENet: Frequency-Aware and Spatially Multiscale Network for Single Image Dehazing | 1 | 1 | 1 Feb 2025 | not harvested |
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- RB-Dust
1 variant name, as the archive lists them.
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