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SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory
SAMURAI enhances the Segment Anything Model 2 for visual object tracking, improving accuracy and robustness in crowded scenes through motion-aware memory selection, achieving significant performance gains without retraining.
https://arxiv.org/abs//2411.11922
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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By Igor Melnyk
5
33 ratings
SAMURAI enhances the Segment Anything Model 2 for visual object tracking, improving accuracy and robustness in crowded scenes through motion-aware memory selection, achieving significant performance gains without retraining.
https://arxiv.org/abs//2411.11922
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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