Datasets › DIS5K
DIS5K (Dichotomous Image Segmentation (DIS) Dataset)
To build the highly accurate Dichotomous Image Segmentation dataset (DIS5K), we first manually collected over 12,000 images from Flickr1 based on our pre-designed keywords. Then, we obtained 5,470 images of 22 groups and 225 categories from the 12,000 images according to the structural complexities of the objects. Each image is then manually labeled with pixel-wise accuracy using GIMP. The labeled targets in DIS5K mainly focus on the “objects of the images defined by the pre-designed keywords (categories)” regardless of their characteristics e.g., salient, common, camouflaged, meticulous, etc. The average per-image labeling time is ∼30 minutes and some images cost up to 10 hours.
Benchmarks archive 2025-07-28
All 5 leaderboards 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 | ||||
|---|---|---|---|---|---|---|
| Dichotomous Image Segmentation | DIS-VD | BEN_Base max F-Measure 0.923 | BEN: Using Confidence-Guided Matting for Dichotomous... | PramaLLC/BEN | 24 | Compare |
| Dichotomous Image Segmentation | DIS-TE1 | PDFNet max F-Measure 0.890 | Patch-Depth Fusion: Dichotomous Image Segmentation via... | tennine2077/pdfnet | 22 | Compare |
| Dichotomous Image Segmentation | DIS-TE2 | PDFNet max F-Measure 0.921 | Patch-Depth Fusion: Dichotomous Image Segmentation via... | tennine2077/pdfnet | 22 | Compare |
| Dichotomous Image Segmentation | DIS-TE3 | PDFNet max F-Measure 0.936 | Patch-Depth Fusion: Dichotomous Image Segmentation via... | tennine2077/pdfnet | 22 | Compare |
| Dichotomous Image Segmentation | DIS-TE4 | MVANet max F-Measure 0.912 | Multi-view Aggregation Network for Dichotomous Image Segmentation | qianyu-dlut/mvanet | 22 | Compare |
Papers archive 2025-07-28
22 shown of 22 papers 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 39. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- DIS5K
- DIS-VD
- DIS-TE1
- DIS-TE2
- DIS-TE3
- DIS-TE4
6 variant names, as the archive lists them.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections