Deep Metallic Surface Defect Detection: The New Benchmark and Detection Network

Metallic surface defect detection is an essential and necessary process to control the qualities of industrial products. However, due to the limited data scale and defect categories, existing defect datasets are generally unavailable for the deployment of the detection model. To address this problem, we contribute a new dataset called GC10-DET for large-scale metallic surface defect detection. The GC10-DET dataset has great challenges on defect categories, image number, and data scale. Besides, traditional detection approaches are poor in both efficiency and accuracy for the complex real-world environment. Thus, we also propose a novel end-to-end defect detection network (EDDN) based on the Single Shot…

• NN
  National Natural Science Foundation of China

  Award: No.61905175, 51775377, 61971307
• FY
  Fok Ying Tung Education Foundation

  Award: 171055
• NS
  National Science and Technology Major Project

  Award: 2017-V-0009
• SK
  State Key Laboratory for Underwater Information and Control

  Award: 6142218081811