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RGB-D Salient Object Detection Dataset (RGB-D SOD)

RGB-D Salient Object Detection (RGB-D SOD) aims to detect and segment objects that visually attract the most human interest from a pair of color and depth images.

Train

  • COME-8K [8025 samples]

Dev

  • COME-E [4600 samples]

Test

  • Coming soon

How to use

from datasets import load_dataset

dataset = load_dataset(
    "RGBD-SOD/rgbdsod_datasets", "v1", split="train", cache_dir="data"
)
print(dataset[0])

BibTeX entry and citation info

@inproceedings{zhang2021rgb,
  title={RGB-D saliency detection via cascaded mutual information minimization},
  author={Zhang, Jing and Fan, Deng-Ping and Dai, Yuchao and Yu, Xin and Zhong, Yiran and Barnes, Nick and Shao, Ling},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={4338--4347},
  year={2021}
}
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Models trained or fine-tuned on RGBD-SOD/rgbdsod_datasets