We evaluate the STEGO algorithm on the CocoStuff, Cityscapes, and Potsdam semantic segmentation datasets. Because these methods see no labels, we use a Hungarian matching algorithm to find the best mapping betw
The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate both supervised classification and unsupervised clustering methods to present more understandable and accurate diagnostic results. The method entails several steps wi...
Self-supervised Augmentation Consistency for Adapting Semantic Segmentation (CVPR 2021) semantic-segmentationunsupervised-domain-adaptationcvpr-2021 UpdatedNov 9, 2021 Python xmed-lab/GenericSSL Star94 NeurIPS 2023: Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation ...
The study of object representations in computer vision has primarily focused on developing representations that are useful for image classification, object detection, or semantic segmentation as downstream tasks. In this work we aim to learn object representations that are useful for control and reinforce...