| --- |
| license: cc-by-nc-4.0 |
| pretty_name: DAVIS-S |
| task_categories: |
| - image-segmentation |
| tags: |
| - saliency |
| - salient-object-detection |
| - segmentation |
| - high-resolution |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: data/test-* |
| --- |
| |
| # DAVIS-S |
|
|
| DAVIS-S is a high-resolution salient object detection (SOD) evaluation set, |
| released alongside the **HRSOD** (High-Resolution Salient Object Detection) |
| paper. It is a saliency-annotated subset of the **DAVIS** video object |
| segmentation dataset, curated to benchmark high-resolution salient object |
| detection methods. Images are full-HD (1920x1080) with pixel-accurate |
| binary ground-truth saliency masks. |
|
|
| ## Dataset structure |
|
|
| - **Split:** `test` (single evaluation set), 92 image/mask pairs. |
| - **Columns:** |
| - `image`: the RGB source image (`datasets.Image`). |
| - `mask`: the grayscale ground-truth saliency mask (`datasets.Image`). |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("nobg/DAVIS-S", split="test") |
| ex = ds[0] |
| ex["image"] # PIL.Image, RGB, 1920x1080 |
| ex["mask"] # PIL.Image, L (grayscale) saliency mask |
| ``` |
|
|
| ## Source & credits |
|
|
| - **DAVIS dataset** — the underlying images originate from the DAVIS |
| (Densely Annotated VIdeo Segmentation) benchmark. |
| - **HRSOD authors** — the high-resolution saliency subset and ground-truth |
| masks were released as part of the HRSOD project |
| ([yi94code/HRSOD](https://github.com/yi94code/HRSOD)). |
|
|
| Please cite the DAVIS and HRSOD works if you use this dataset. |
|
|
| ## License |
|
|
| Released under **CC BY-NC 4.0** (non-commercial research use), consistent |
| with the DAVIS dataset licensing. |
|
|
