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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.
By dynamically adjusting contrastive learning temperatures based on data density, MM-TS achieves state-of-the-art results on multimodal long-tail datasets.
