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

Paper recorded by Signals 4 on 2026-09-01 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-01 on arXiv · recorded by Signals 4 on 2026-09-02

Category: cs.CV · 计算机视觉 · first seen 2026-09-02

Abstract

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 Unco

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#178 most recent of 237 cs.CV papers we have recorded · ↑ newer: UI-VISA: U-Net Initialized Vascular Image Segmentation Architecture · ↓ older: SpatialGuard: Harness-Guided Verifiable Spatial Reasoning for Text-to-
Cite this page: A Benchmark for Vehicle Attribute Classification in Cross-Domain Surveillance Scenarios: the #178 most recent of 237 cs.CV papers we have recorded (as of 2026-09-01). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/a-benchmark-for-vehicle-attribute-classification-in-cross-domain-surveillance-sc.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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