NVlabs/GroupViT
Official PyTorch implementation of GroupViT: Semantic Segmentation Emerges from Text Supervision, CVPR 2022.
This project helps computer vision researchers and practitioners automatically identify and group semantically related regions within an image, purely from text descriptions, without needing manually drawn outlines. You provide an image and a text description, and the system outputs an image with distinct regions highlighted and categorized based on the text. It's ideal for those working on advanced image understanding problems.
783 stars. No commits in the last 6 months.
Use this if you need to segment images based on conceptual understanding derived from text, rather than relying on pixel-level mask annotations or pre-defined categories.
Not ideal if you require highly precise, pixel-perfect segmentation masks for every object, or if you don't have access to textual descriptions for your image data.
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Python
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Last pushed
May 10, 2022
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