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COD10K (Camouflaged Object Detection 10K)
This dataset contains the COD10K subset for camouflaged object detection, packaged from the SINet repository (DengPingFan/SINet). Each example is a natural image paired with a binary ground-truth object mask.
Contents
Only the COD10K portion of the SINet train/test bundles is included here. The SINet distribution also ships CAMO and CHAMELEON samples; those were excluded:
- train: 3040 COD10K samples (the 1000 CAMO
camourflage_*samples bundled in the SINet TrainDataset were filtered out). - test: 2026 COD10K samples (the CAMO (251) and CHAMELEON (77) test sets bundled in the SINet TestDataset were filtered out).
Features
image: the RGB input image (datasets.Image).mask: the binary ground-truth object segmentation mask (datasets.Image, modeL).
Edge/instance maps that ship with COD10K are not included; only the binary
object mask is provided as mask.
Citation
If you use this dataset, please cite the COD10K paper:
@inproceedings{fan2020camouflaged,
title={Camouflaged Object Detection},
author={Fan, Deng-Ping and Ji, Ge-Peng and Sun, Guolei and Cheng, Ming-Ming and Shen, Jianbing and Shao, Ling},
booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2020}
}
License
Released for academic / research (non-commercial) use, following the terms
of the original COD10K / SINet release. No explicit SPDX license is provided by
the authors; this repository is tagged cc-by-nc-4.0 to reflect the
non-commercial, attribution-based terms. Please refer to the
original repository for authoritative terms.
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