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Max Planck Institute for Informatics, Saarland Informatics Campus 2 University of Technology Nuremberg
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SAM, designed for instance segmentation, can be surprisingly effective for semantic segmentation with weak supervision when adapted with techniques like skeleton-based prompting and iterative pseudo-label refinement.
Semantic scene understanding can be injected into novel view synthesis to generate more plausible and consistent images, especially under long-range camera motion, improving FID scores by up to 15%.
