STN PLAD: A Dataset for Multi-Size Power Line Assets Detection in High-Resolution UAV Images

  • André Luiz Buarque Vieira-e-Silva UFPE
  • Heitor de Castro Feliz UFPE
  • Thiago de Menezes Chaves UFPE
  • Francisco Paulo Magalhães Simões UFPE / UFRPE
  • Veronica Teichrieb UFPE
  • Michel Mozinho dos Santos In Forma Software
  • Hemir da Cunha Santiago In Forma Software
  • Virginia Adélia Cordeiro Sgotti In Forma Software
  • Henrique Baptista Duffles Teixeira Lott Neto Sistema de Transmissão Nordeste


Many power line companies are using UAVs to perform their inspection processes instead of putting their workers at risk by making them climb high voltage power line towers, for instance. A crucial task for the inspection is to detect and classify assets in the power transmission lines. However, public data related to power line assets are scarce, preventing a faster evolution of this area. This work proposes the STN Power Line Assets Dataset, containing high-resolution and real-world images of multiple high-voltage power line components. It has 2,409 annotated objects divided into five classes: transmission tower, insulator, spacer, tower plate, and Stockbridge damper, which vary in size (resolution), orientation, illumination, angulation, and background. This work also presents an evaluation with popular deep object detection methods and MS-PAD, a new pipeline for detecting power line assets in hi-res UAV images. The latter outperforms the other methods achieving 89.2% mAP, showing considerable room for improvement. The STN PLAD dataset is publicly available at

Palavras-chave: Power transmission lines, Image resolution, Poles and towers, Pipelines, Lighting, Object detection, Inspection
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VIEIRA-E-SILVA, André Luiz Buarque et al. STN PLAD: A Dataset for Multi-Size Power Line Assets Detection in High-Resolution UAV Images. In: CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), 34. , 2021, Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 .