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A Benchmark for Vehicle Attribute Classification in Cross-Domain Surveillance Scenarios

arXiv · AI, language, vision and robotics · article · Sep 1, 2026 · UTC

Vehicle attribute analysis is a key component of Intelligent Transportation Systems (ITS), supporting applications such as vehicle identification, traffic monitoring, and forensic investigation. However, models trained under controlled conditions often degrade in real surveillance scenarios due to changes in viewpoint, occlusion, illumination, and sensor characteristics. This paper introduces Unconstrained Vehicle Identification Benchmark (UVIB), a benchmark for evaluating three operational vehicle-analysis tasks: front/rear orientation, occlusion-related suitability for Vehicle Make and Model

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Evidence & attribution

First collected: 2026-09-21T06:01:56.170Z. This is not the publication date.