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Object Segmentation

Instance segmentation is a computer vision technique utilized to detect and separate individual objects in an image. Within the realm of warehouse automation, instance segmentation is used to identify and define distinct objects that are stored in containers. The outcomes of instance segmentation can be used to provide information to subsequent robotic processes, such as the identification of objects and generation of grasping strategies. It is an essential factor in achieving high-efficiency robot manipulation as it facilitates more precise and accurate object detection and handling.

We have divided the Object Segmentation dataset into three distinct subsets to showcase the challenge of transferring learned knowledge across tasks. The subsets are as follows:
These labels are provided per-image in the format that is compatible with LabelMe, as well as a train, validation, and test split format that is compatible with MS-COCO format.