ETH Zurich and HKUST Researchers Propose HQ-SAM: A High-Quality Zero-Shot Segmentation Model By Introducing Negligible Overhead To The Original SAM

Accurate segmentation of multiple objects is essential for various scene understanding applications, such as image/video processing, robotic perception, and AR/VR. The Segment Anything Model (SAM) was recently released, a basic vision model for broad image segmentation. It was trained using billion-scale mask labels. SAM can segment various objects, components, and visual structures in multiple contexts […]

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