twke18/HSG
Unsupervised Hierarchical Semantic Segmentation with Multiview Cosegmentation and Clustering Transformers
This project helps computer vision researchers and practitioners automatically identify distinct objects and regions within images without requiring pre-labeled examples. It takes raw image data and outputs hierarchical segmentations, meaning it can group pixels into fine-grained details or broader categories, offering a flexible understanding of an image's content. This is for professionals working with image analysis, visual data interpretation, or autonomous systems.
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Use this if you need to segment images into meaningful, multi-level groupings (from fine details to broad categories) without the time-consuming and expensive process of manually labeling thousands of images.
Not ideal if your segmentation task requires precise, pre-defined object classes that are consistent across all images, as this method discovers groupings rather than recognizing specific categories.
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74
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6
Language
Python
License
MIT
Category
Last pushed
Apr 02, 2024
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