SAM 3 outperforms SAM 2 under click prompting for zero-shot 3D medical segmentation across 16 datasets and 54 structures, with fewer failure modes in prompt-frame over-segmentation and prediction retention.
Endonet: a deep architecture for recognition tasks on laparoscopic videos
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SurgMotion outperforms prior methods on 17 surgical video benchmarks by shifting pretraining to latent motion prediction with motion-guided masking, affinity distillation, and diversity regularization on a 15M-sample dataset.
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Comparing SAM 2 and SAM 3 for Zero-Shot Segmentation of 3D Medical Data
SAM 3 outperforms SAM 2 under click prompting for zero-shot 3D medical segmentation across 16 datasets and 54 structures, with fewer failure modes in prompt-frame over-segmentation and prediction retention.
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SurgMotion: A Video-Native Foundation Model for Universal Understanding of Surgical Videos
SurgMotion outperforms prior methods on 17 surgical video benchmarks by shifting pretraining to latent motion prediction with motion-guided masking, affinity distillation, and diversity regularization on a 15M-sample dataset.