SAMOSA adapts SAM 2 for complex visual object tracking by integrating explicit nonlinear motion prediction, semantic cues for failure recovery, and geometric constraints for stability, outperforming prior SAM 2-based and supervised methods on benchmarks including anti-UAV datasets.
Evidential detection and tracking collaboration: New problem, benchmark and algorithm for robust anti-uav system
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Introduces UAVDB dataset for UAV detection/segmentation via PIC point-to-box conversion and SAM2 masks, with YOLO baselines showing PIC+SAM2 outperforms prior annotation methods on IoU.
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Segment Anything with Motion, Geometry, and Semantic Adaptation for Complex Nonlinear Visual Object Tracking
SAMOSA adapts SAM 2 for complex visual object tracking by integrating explicit nonlinear motion prediction, semantic cues for failure recovery, and geometric constraints for stability, outperforming prior SAM 2-based and supervised methods on benchmarks including anti-UAV datasets.
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UAVDB: Point-Guided Masks for UAV Detection and Segmentation
Introduces UAVDB dataset for UAV detection/segmentation via PIC point-to-box conversion and SAM2 masks, with YOLO baselines showing PIC+SAM2 outperforms prior annotation methods on IoU.