xuebinqin/U-2-Net
The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."
This project helps you automatically remove backgrounds and isolate the main subject in images or videos, also known as 'salient object detection.' You input an image or video, and it outputs a version where the primary object is clearly separated from its background, often with the background removed entirely or replaced. This is designed for graphic designers, content creators, marketers, or anyone needing to quickly extract subjects from visual media for editing or composition.
9,672 stars. No commits in the last 6 months.
Use this if you need to quickly and accurately separate a foreground object from its background in images or videos for tasks like product photography, portrait editing, or creating visual effects.
Not ideal if you require extremely fine-grained, pixel-perfect segmentation for highly complex or ambiguous scenes where manual masking and detailed editing are indispensable.
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Language
Python
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Apache-2.0
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Last pushed
Jun 26, 2024
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