Datasets:

nobg
/

DUTS

license: cc-by-nc-4.0
pretty_name: DUTS
task_categories:
  - image-segmentation
tags:
  - saliency-detection
  - salient-object-detection
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*

DUTS

DUTS is a large-scale saliency detection (salient object detection) dataset. It contains a training set, DUTS-TR (10,553 images), and a test set, DUTS-TE (5,019 images). Each image is paired with a binary ground-truth saliency mask.

Splits

Split	Source	Rows
train	DUTS-TR	10,553
test	DUTS-TE	5,019

Columns

image: the RGB input image (datasets.Image).
mask: the ground-truth saliency mask (datasets.Image, single channel).

Image and mask are matched by filename stem.

License

Released for academic / research use. No explicit SPDX license is provided by the authors; this mirror is published under cc-by-nc-4.0. See https://saliencydetection.net/duts/ for the original terms.

Credits

Source: https://saliencydetection.net/duts/

Paper: Lijun Wang, Huchuan Lu, Yifan Wang, Mengyang Feng, Dong Wang, Baocai Yin, Xiang Ruan. Learning to Detect Salient Objects with Image-level Supervision. CVPR 2017.