FCIS is a fully convolutional end-to-end solution for instance segmentation, which won the first place in COCO segmentation challenge 2016. FCIS is initially described in a CVPR 2017 spotlight paper.

This is the official PyTorch implementation of the paper RetSeg3D: Retention-based 3D Semantic Segmentation for Autonomous Driving, by Gopi Krishna Erabati and Helder Araujo. G. K. Erabati and H.

Image segmentation is crucial for various Computer Vision tasks, aiding in image classification and object detection. Segmentation techniques can be categorised into semantic, instance, and panoptic ...

Various pre-trained deep learning models for the segmentation of bioimages have been made available as developer-to-end-user solutions. They are optimized for ease of use and usually require neither ...