Publication | Open Access
Segment and Track Anything
79
Citations
0
References
2023
Year
EngineeringField RoboticsDrone TechnologyHuman-object InteractionImage AnalysisData ScienceVirtual RealityVideo Content AnalysisObject TrackingRobot LearningHuman MotionProject PageComputational GeometryHealth SciencesMachine VisionMoving Object TrackingComputer ScienceVideo UnderstandingTrack AnythingComputer VisionVideo AnalysisEye TrackingExtended RealityRoboticsTracking System
SAM-Track can be used across an array of fields, ranging from drone technology, autonomous driving, medical imaging, augmented reality, to biological analysis. This report presents a framework called Segment And Track Anything (SAMTrack) that allows users to precisely and effectively segment and track any object in a video. SAM-Track fuses the Segment Anything Model with the DeAOT tracking model and Grounding‑DINO, and offers multimodal interaction (click, stroke, text) to select multiple objects for tracking. We have demonstrated the remarkable capabilities of SAM-Track on DAVIS‑2016 Val (92.0%), DAVIS‑2017 Test (79.2%) and its practicability in diverse applications. The project page is available at: https://github.com/z-x-yang/Segment-and-Track-Anything.
This report presents a framework called Segment And Track Anything (SAMTrack) that allows users to precisely and effectively segment and track any object in a video. Additionally, SAM-Track employs multimodal interaction methods that enable users to select multiple objects in videos for tracking, corresponding to their specific requirements. These interaction methods comprise click, stroke, and text, each possessing unique benefits and capable of being employed in combination. As a result, SAM-Track can be used across an array of fields, ranging from drone technology, autonomous driving, medical imaging, augmented reality, to biological analysis. SAM-Track amalgamates Segment Anything Model (SAM), an interactive key-frame segmentation model, with our proposed AOT-based tracking model (DeAOT), which secured 1st place in four tracks of the VOT 2022 challenge, to facilitate object tracking in video. In addition, SAM-Track incorporates Grounding-DINO, which enables the framework to support text-based interaction. We have demonstrated the remarkable capabilities of SAM-Track on DAVIS-2016 Val (92.0%), DAVIS-2017 Test (79.2%)and its practicability in diverse applications. The project page is available at: https://github.com/z-x-yang/Segment-and-Track-Anything.