MSFFNet: Multistage Feature Fusion With Metadata Injection for Vehicle Reidentification

Vehicle reidentification (Re-ID, the task of finding images of the same vehicle across different camera views) systems often require expensive computation or manual labeling. This paper presents MSFFNet, a lightweight AI model that uses multistage feature fusion (combining information from different layers of a neural network) and metadata injection (adding contextual information like camera location) to identify vehicles efficiently while maintaining high accuracy.