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✨3AM: Segment Anything with Geometric Consistency in Videos
📝 Summary:
3AM enhances video object segmentation by integrating 3D-aware features from MUSt3R into SAM2. This improves viewpoint consistency and geometric recognition using only RGB input at inference, significantly outperforming prior methods on challenging datasets.
🔹 Publication Date: Published on Jan 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.08831
• PDF: https://arxiv.org/pdf/2601.08831
• Project Page: https://jayisaking.github.io/3AM-Page/
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For more data science resources:
✓ https://t.iss.one/DataScienceT
#VideoSegmentation #ComputerVision #DeepLearning #GeometricAI #AI
📝 Summary:
3AM enhances video object segmentation by integrating 3D-aware features from MUSt3R into SAM2. This improves viewpoint consistency and geometric recognition using only RGB input at inference, significantly outperforming prior methods on challenging datasets.
🔹 Publication Date: Published on Jan 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.08831
• PDF: https://arxiv.org/pdf/2601.08831
• Project Page: https://jayisaking.github.io/3AM-Page/
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#VideoSegmentation #ComputerVision #DeepLearning #GeometricAI #AI