This AI Paper Introduces the Segment Anything for NeRF in High Quality (SANeRF-HQ) Framework to Achieve High-Quality 3D Segmentation of Any Object in a Given Scene.

Researchers from Hong Kong University of Science and Technology, Carnegie Mellon University, and Dartmouth College developed The SANeRF-HQ (Segment Anything for NeRF in High Quality) method to achieve accurate 3D segmentation in complex scenarios. Prior NeRF-based methods for object segmentation were limited in their accuracy. Still, SANeRF-HQ combines the Segment Anything Model (SAM) and Neural […]

The post This AI Paper Introduces the Segment Anything for NeRF in High Quality (SANeRF-HQ) Framework to Achieve High-Quality 3D Segmentation of Any Object …

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