Camouflaged Object Segmentation

Camouflaged object segmentation (COS) or Camouflaged object detection (COD), which was originally promoted by T.-N. Le et al. (2017), aims to identify objects that conceal their texture into the surrounding environment. The high intrinsic similarities between the target object and the background make COS/COD far more challenging than the traditional object segmentation task. Also, refer to the online benchmarks on CAMO dataset, COD dataset, and online demo.

<span style="color:grey; opacity: 0.6">( Image source: Anabranch Network for Camouflaged Object Segmentation )</span>