Shulou(Shulou.com)11/24 Report--

CTOnews.com July 31 news, Ali's Dama House recently launched an AI framework called HQTrack in cooperation with Dalian University of Technology. The framework is mainly composed of video multi-target splitter (VMOS) and mask optimizer (MR), which aims to "achieve high-quality tracking of any target in video".

The research team said that HQTrack is based on open source frameworks DeAOT and HQ-SAM, and has made some improvements to achieve the possibility of "dividing goals in video."

▲ image source HQTrack GitHub page, the research team uses Intern-T as a feature extractor to improve the framework's ability to distinguish different types of objects, and adds a gated propagation module (GPM), so that the framework can perceive more small objects in a complex environment and generate high-quality real-time target masks.

It is reported that in the VOTS2023 competition, HQTrack won the second place with a quality score of 0.615. The research team said that the AI framework can be used in areas such as face recognition, intelligent driving, surveillance and tracking, and is expected to hit the ground in future commercial applications.

The GitHub page of ▲ source HQTrack. The project is now available in GitHub. Interested friends can visit it here. CTOnews.com transcribes the core functions of HQTrack below:

1. Multi-target tracking: HQTrack can track multiple target objects at the same time, which is suitable for target tracking tasks in complex scenes.

two。 Target segmentation: HQTrack can accurately segment the target objects in the video and generate high-quality target masks, which can be used for target recognition and analysis.

3. High quality output: HQTrack tracking results with high quality and high accuracy, can meet the needs of a variety of application scenarios.

4. Easy to use: HQTrack provides a concise interface and guide for users to easily use and integrate the tool.

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