Unsupervised Semantic Segmentation
Models that learn to segment each image (i.e. cluster the pixels into their ground truth classes) without seeing the ground truth labels.
( Image credit: SegSort: Segmentation by Discriminative Sorting of Segments )
Leaderboards
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Greatest papers with code
Invariant Information Clustering for Unsupervised Image Classification and Segmentation
arXiv 2019
• xu-ji/IIC
• 
The method is not specialised to computer vision and operates on any paired dataset samples; in our experiments we use random transforms to obtain a pair from each image.
SEMI-SUPERVISED IMAGE CLASSIFICATION UNSUPERVISED IMAGE CLASSIFICATION UNSUPERVISED SEMANTIC SEGMENTATION
SegSort: Segmentation by Discriminative Sorting of Segments
ICCV 2019
• jyhjinghwang/segsort
• 
As a result, we present the SegSort, as a first attempt using deep learning for unsupervised semantic segmentation, achieving $76\%$ performance of its supervised counterpart.
SOTA for Unsupervised Semantic Segmentation on PASCAL VOC 2012 val (using extra training data)
Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation
This paper focuses on the unsupervised domain adaptation of transferring the knowledge from the source domain to the target domain in the context of semantic segmentation.
UNSUPERVISED DOMAIN ADAPTATION UNSUPERVISED SEMANTIC SEGMENTATION