DeepCut: Unsupervised Segmentation using Graph Neural Networks Clustering

Understand

Image segmentation is a fundamental task in computer vision.

• Data annotation for training supervised methods can be labor-intensive, motivating unsupervised methods.
• Current approaches often rely on extracting deep features from pre-trained networks to construct a graph, and classical clustering methods like k-means and normalized-cuts are then applied as a post-processing step.
• However, this approach reduces the high-dimensional information encoded in the features to pair-wise scalar affinities.