mlsanityData to 14 Oct 2026

TD-RD: A Top-Down Benchmark with Real-Time Framework for Road Damage Detection

arXiv 2501.14302 ↗First posted 24 Jan 2025cs.CVcited by 6

Not on the map. Why?

Abstract (arXiv)

Object detection has witnessed remarkable advancements over the past decade, largely driven by breakthroughs in deep learning and the proliferation of large scale datasets. However, the domain of road damage detection remains relatively under explored, despite its critical significance for applications such as infrastructure maintenance and road safety. This paper addresses this gap by introducing a novel top down benchmark that offers a complementary perspective to existing datasets, specifically tailored for road damage detection. Our proposed Top Down Road Damage Detection Dataset (TDRD) includes three primary categories of road damage cracks, potholes, and patches captured from a top down viewpoint. The dataset consists of 7,088 high resolution images, encompassing 12,882 annotated instances of road damage. Additionally, we present a novel real time object detection framework, TDYOLOV10, designed to handle the unique challenges posed by the TDRD dataset. Comparative studies with state of the art models demonstrate competitive baseline results. By releasing TDRD, we aim to accelerate research in this crucial area. A sample of the dataset will be made publicly available upon the paper's acceptance.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 14 of its 22 references that are in the map. First posted on arXiv 24 Jan 2025.

Builds on

14 of 22 references.

References · 14

  1. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  2. 2022YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectorscited by 982
  3. 2017Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learningcited by 950
  4. 2020A Survey on Visual Transformercited by 654
  5. 2021You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detectioncited by 170
  6. 2018Pyramid Attention Network for Semantic Segmentationcited by 149
  7. 2021Lite-HRNet: A Lightweight High-Resolution Networkcited by 91
  8. 2021PP-PicoDet: A Better Real-Time Object Detector on Mobile Devicescited by 25
  9. 2023FishEye8K: A Benchmark and Dataset for Fisheye Camera Object Detectioncited by 22
  10. 2024HGTDP-DTA: Hybrid Graph-Transformer with Dynamic Prompt for Drug-Target Binding Affinity Predictioncited by 7
  11. 2024Interpretable Data Fusion for Distributed Learning: A Representative Approach via Gradient Matchingcited by 4
  12. 2024Cycle-YOLO: A Efficient and Robust Framework for Pavement Damage Detectioncited by 2
2 more
  1. 2024Features Reconstruction Disentanglement Cloth-Changing Person Re-Identificationcited by 2
  2. 2024Advancing Out-of-Distribution Detection through Data Purification and Dynamic Activation Function Designcited by 1

Built on by

Cited by year

Citing papers per year: 2025: 6.

6 papers.

  1. 2025Prompt-based Adaptation in Large-scale Vision Models: A Surveycited by 21
  2. 2025CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentationcited by 12
  3. 2025CIBR: Cross-modal Information Bottleneck Regularization for Robust CLIP Generalizationcited by 6
  4. 2025PFedDST: Personalized Federated Learning with Decentralized Selection Trainingcited by 4
  5. 2025Self-Supervised Visual Prompting for Cross-Domain Road Damage Detectioncited by 3
  6. 2025E2CB2former: Effecitve and Explainable Transformer for CB2 Receptor Ligand Activity Predictioncited by 0