Papers › Concealed Object Detection

Concealed Object Detection

20 Feb 2021arXiv:2102.10274archive 2025-07-28

Deng-Ping Fan, Ge-Peng Ji, Ming-Ming Cheng, Ling Shao

We present the first systematic study on concealed object detection (COD), which aims to identify objects that are "perfectly" embedded in their background. The high intrinsic similarities between the concealed objects and their background make COD far more challenging than traditional object detection/segmentation. To better understand this task, we collect a large-scale dataset, called COD10K, which consists of 10,000 images covering concealed objects in diverse real-world scenarios from 78 object categories. Further, we provide rich annotations including object categories, object boundaries, challenging attributes, object-level labels, and instance-level annotations. Our COD10K is the largest COD dataset to date, with the richest annotations, which enables comprehensive concealed object understanding and can even be used to help progress several other vision tasks, such as detection, segmentation, classification, etc. Motivated by how animals hunt in the wild, we also design a simple but strong baseline for COD, termed the Search Identification Network (SINet). Without any bells and whistles, SINet outperforms 12 cutting-edge baselines on all datasets tested, making them robust, general architectures that could serve as catalysts for future research in COD. Finally, we provide some interesting findings and highlight several potential applications and future directions. To spark research in this new field, our code, dataset, and online demo are available on our project page: http://mmcheng.net/cod.

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Syntology Ran 3 of 3 code samples harvested from 1 repository linked to this paper; 0 have no recorded run. Of those that ran: 2 ran · our draft was wrong; 1 ran · fixture could not drive it.

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GewelsJI/SINet-V2 officialpytorch report

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2ran · our draft was wrong
1ran · fixture could not drive it

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cv_random_flip GewelsJI/SINet-V2/utils/data_val.py official repository ran · fixture could not drive it Apache-2.0 (permissive) · 41839b27773cccf7 · report
randomCrop GewelsJI/SINet-V2/utils/data_val.py official repository ran · our draft was wrong Apache-2.0 (permissive) · b8fc70f2a16b23cc · report
randomRotation GewelsJI/SINet-V2/utils/data_val.py official repository ran · our draft was wrong Apache-2.0 (permissive) · 8d40bcc4f2cf3edb · report

Tasks

Camouflaged Object SegmentationDichotomous Image SegmentationObjectObject Detectionobject-detection

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Camouflaged Object Segmentation CAMO SINet-V2 MAE 0.070 #8 of 14 Archive leaderboard report
Camouflaged Object Segmentation CAMO SINet-V2 S-Measure 0.820 #8 of 14 Archive leaderboard report
Camouflaged Object Segmentation CAMO SINet-V2 Weighted F-Measure 0.743 #8 of 14 Archive leaderboard report
Camouflaged Object Segmentation CHAMELEON SINetV2-Res2Net-50 MAE 0.030 #6 of 6 Archive leaderboard report
Camouflaged Object Segmentation CHAMELEON SINetV2-Res2Net-50 S-measure 0.888 #6 of 6 Archive leaderboard report
Camouflaged Object Segmentation CHAMELEON SINetV2-Res2Net-50 weighted F-measure 0.816 #6 of 6 Archive leaderboard report
Camouflaged Object Segmentation COD SINet* MAE 0.051 #8 of 12 Archive leaderboard report
Camouflaged Object Segmentation COD SINet* S-Measure 0.771 #8 of 12 Archive leaderboard report
Camouflaged Object Segmentation COD SINet* Weighted F-Measure 0.551 #8 of 12 Archive leaderboard report
Camouflaged Object Segmentation NC4K SINetV2-Res2Net-50 MAE 0.048 #6 of 6 Archive leaderboard report
Camouflaged Object Segmentation NC4K SINetV2-Res2Net-50 S-measure 0.847 #6 of 6 Archive leaderboard report
Camouflaged Object Segmentation NC4K SINetV2-Res2Net-50 weighted F-measure 0.770 #6 of 6 Archive leaderboard report
Camouflaged Object Segmentation PCOD_1200 SINet-V2 S-Measure 0.882 #9 of 16 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE1 SINetV2 E-measure 0.791 #15 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE1 SINetV2 HCE 274 #15 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE1 SINetV2 MAE 0.094 #15 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE1 SINetV2 S-Measure 0.727 #15 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE1 SINetV2 max F-Measure 0.644 #15 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE1 SINetV2 weighted F-measure 0.558 #15 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE2 SINetV2 E-measure 0.823 #19 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE2 SINetV2 HCE 593 #19 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE2 SINetV2 MAE 0.099 #19 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE2 SINetV2 S-Measure 0.753 #19 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE2 SINetV2 max F-Measure 0.700 #19 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE2 SINetV2 weighted F-measure 0.618 #19 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE3 SINetV2 E-measure 0.849 #18 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE3 SINetV2 HCE 1096 #18 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE3 SINetV2 MAE 0.096 #18 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE3 SINetV2 S-Measure 0.766 #18 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE3 SINetV2 max F-Measure 0.730 #18 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE3 SINetV2 weighted F-measure 0.641 #18 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE4 SINetV2 E-measure 0.824 #21 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE4 SINetV2 HCE 3683 #21 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE4 SINetV2 MAE 0.113 #21 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE4 SINetV2 S-Measure 0.744 #21 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE4 SINetV2 max F-Measure 0.699 #21 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-TE4 SINetV2 weighted F-measure 0.616 #21 of 22 Archive leaderboard report
Dichotomous Image Segmentation DIS-VD SINetV2 E-measure 0.798 #21 of 24 Archive leaderboard report
Dichotomous Image Segmentation DIS-VD SINetV2 HCE 1568 #21 of 24 Archive leaderboard report
Dichotomous Image Segmentation DIS-VD SINetV2 MAE 0.110 #21 of 24 Archive leaderboard report
Dichotomous Image Segmentation DIS-VD SINetV2 S-Measure 0.727 #21 of 24 Archive leaderboard report
Dichotomous Image Segmentation DIS-VD SINetV2 max F-Measure 0.665 #21 of 24 Archive leaderboard report
Dichotomous Image Segmentation DIS-VD SINetV2 weighted F-measure 0.584 #21 of 24 Archive leaderboard report

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