mhamilton723/STEGO

Unsupervised Semantic Segmentation by Distilling Feature Correspondences

Jupyter NotebookPythoncomputer-visiondeep-learningpytorchunsupervised-learningsemantic-segmentationiclr2022
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STEGO: Unsupervised Semantic Segmentation by Distilling Feature Correspondences Project Page | Paper | Video | ICLR 2022 Mark Hamilton, Zhoutong Zhang, Bharath Hariharan, Noah Snavely, William T. Freeman This is the official implementation of the paper "Unsupervised Semantic Segmentation by Distilling Feature Correspondences". Contents Install Evaluation Training Bringing your own data Understanding STEGO Unsupervised Semantic Segmentation Deep features connect objects across images The STEGO...
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