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CAMO

Camouflaged Object

CAMO

Camouflaged Object (CAMO) dataset specifically designed for the task of camouflaged object segmentation. We focus on two categories, i.e., naturally camouflaged objects and artificially camouflaged objects, which usually correspond to animals and humans in the real world, respectively. Camouflaged object images consists of 1250 images (1000 images for the training set and 250 images for the testing set). Non-camouflaged object images are collected from the MS-COCO dataset (1000 images for the training set and 250 images for the testing set). CAMO has objectness mask ground-truth.

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Anabranch Network for Camouflaged Object Segmentation
https://www.cornell.edu
Task
Semantic Segmentation
Annotation Types
Semantic Segmentation
1250
Items
2
Classes
1250
Labels
Models using this dataset
Last updated on 
January 20, 2022
Licensed under 
Unknown
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