Segment Anything Model 2 (SAM 2) is a foundational model for visual segmentation in both images and videos. This episode highlights the development of a large video segmentation dataset (SA-V), collected through a data engine involving human annotators and model-assisted annotation. SAM 2 is a transformer-based model equipped with a streaming memory mechanism for real-time video processing, enabling efficient and accurate segmentation across video frames. The SAM 2 paper authors demonstrate the model's superior performance compared to prior approaches in both image and video segmentation tasks, highlighting its ability to "segment anything" in videos through user-provided prompts.

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