SiamFC++: Towards Robust and Accurate Visual Tracking
Implementation of a series of basic algorithms which is useful for video understanding, including Single Object Tracking (SOT), Video Object Segmentation ...
video image-segmentation pytorch computer-vision
Objectives & Highlights

In this work, we address the task of semi-supervised video object segmentation(VOS) and explore how to make efficient use of video property to tackle the challenge of semi-supervision. We propose a novel pipeline called State-Aware Tracker(SAT), which can produce accurate segmentation results with real-time speed. For higher efficiency, SAT takes advantage of the inter-frame consistency and deals with each target object as a tracklet. For more stable and robust performance over video sequences, SAT gets awareness for each state and makes self-adaptation via two feedback loops. One loop assists SAT in generating more stable tracklets.

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