3AM: Segment Anything with Geometric Consistency in Videos

arXiv — cs.CVWednesday, January 14, 2026 at 5:00:00 AM
  • The introduction of 3AM enhances video object segmentation by integrating 3D-aware features from MUSt3R into the existing SAM2 model, allowing for geometry-consistent recognition without the need for camera poses or extensive preprocessing. This innovation aims to improve performance in scenarios with significant viewpoint changes.
  • This development is significant as it addresses a critical limitation in current video segmentation methods, enabling more reliable object recognition in dynamic environments, which is essential for applications in various fields such as robotics and augmented reality.
  • The advancement of 3AM reflects a broader trend in AI towards improving model robustness and adaptability, particularly in complex visual tasks. This is echoed in recent enhancements to SAM2, such as SAM2S for surgical videos and V^2-SAM for cross-view correspondence, indicating a concerted effort to refine segmentation technologies across diverse domains.
— via World Pulse Now AI Editorial System

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