UDTIRI: An Online Open-Source Intelligent Road Inspection Benchmark Suite

TL;DR

This paper introduces UDTIRI, an open-source benchmark suite for intelligent road inspection, including a new dataset and competition to evaluate deep learning methods for pothole detection under diverse conditions.

Contribution

The paper presents the first online benchmark suite and dataset for intelligent road inspection, enabling systematic evaluation of deep learning models in this emerging field.

Findings

Benchmark includes 1,000 annotated RGB images in diverse conditions

Evaluates state-of-the-art detection and segmentation networks

Aims to accelerate research in urban digital twins and road inspection

Abstract

In the nascent domain of urban digital twins (UDT), the prospects for leveraging cutting-edge deep learning techniques are vast and compelling. Particularly within the specialized area of intelligent road inspection (IRI), a noticeable gap exists, underscored by the current dearth of dedicated research efforts and the lack of large-scale well-annotated datasets. To foster advancements in this burgeoning field, we have launched an online open-source benchmark suite, referred to as UDTIRI. Along with this article, we introduce the road pothole detection task, the first online competition published within this benchmark suite. This task provides a well-annotated dataset, comprising 1,000 RGB images and their pixel/instance-level ground-truth annotations, captured in diverse real-world scenarios under different illumination and weather conditions. Our benchmark provides a systematic and thorough evaluation of state-of-the-art object detection, semantic segmentation, and instance segmentation networks, developed based on either convolutional neural networks or Transformers. We anticipate that our benchmark will serve as a catalyst for the integration of advanced UDT techniques into IRI. By providing algorithms with a more comprehensive understanding of diverse road conditions, we seek to unlock their untapped potential and foster innovation in this critical domain.