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SAM2Matting introduces a tracker-to-matting framework that enhances foundational trackers like SAM2 with region-proposal bridges and matting heads, achieving state-of-the-art video matting performance even when trained only on images, with strong generalization across diverse scenarios.
AuralSAM2 integrates audio into SAM2 via an AuralFuser module that generates sparse and dense prompts from audio-visual features, enhancing cross-modal segmentation while maintaining interactive efficiency.