Depth-Aware Pothole Detection Using YOLO and RT-DETR at the Edge
Pothole detection and its severity measurement is still an important challenges in urban infrastructure management, where late maintenance directly contributes to vehicle damage, road accidents, and escalating repair costs. Existing automated approaches depend on 2D RGB images and cannot measure physical depth of potholes. In this paper, we present a depthaware pothole detection framework and then compare five architectures: YOLOv8n, YOLOv8nSeg, YOLOv9t, RTDETRL, and RTDETRX for RGB-D sensor fusion-based detection and automated depth measurement. A custom offline augmentation pipeline is used here to simulate adverse road monitoring conditions. All models are trained on the PothRGBD datas...
| Authors | Md Monjurul Ahsan Prodhan, Md Nour Hossain |
|---|---|
| Primary category | cs.CV |
| Published | 27 August 2026 |
| Last updated at source | 27 August 2026 |
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