AttriBE: Quantifying Attribute Expressivity in Body Embeddings for Recognition and Identification

ArXi:2604.27218v1 Announce Type: new Person re-identification (ReID) systems that match individuals across images or video frames are essential in many real-world applications. However, existing methods are often influenced by attributes such as gender, pose, and body mass index (BMI), which vary in unconstrained settings and raise concerns related to fairness and generalization.