The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider removing the loading script and relying on automated data support (you can use convert_to_parquet from the datasets library). If this is not possible, please open a discussion for direct help.

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}
}
Downloads last month
58

Models trained or fine-tuned on RGBD-SOD/rgbdsod_datasets