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

arXiv: https://arxiv.org/abs/2108.07944 · HTML: https://mlsanity.com/paper/2108.07944/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 35 references that are in the map.
- First posted on arXiv 18 Aug 2021.

## Builds on (most cited first, 7 of 7)

- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [Feature Pyramid Networks for Object Detection](https://mlsanity.com/paper/1612.03144/) (2016)
- [SSD: Single Shot MultiBox Detector](https://mlsanity.com/paper/1512.02325/) (2015)
- [Deformable Convolutional Networks](https://mlsanity.com/paper/1703.06211/) (2017)
- [TTPLA: An Aerial-Image Dataset for Detection and Segmentation of Transmission Towers and Power Lines](https://mlsanity.com/paper/2010.10032/) (2020)
- [Review of data analysis in vision inspection of power lines with an in-depth discussion of deep learning technology](https://mlsanity.com/paper/2003.09802/) (2020)

## Built on by (most cited first, 6 of 6)

- [InsPLAD: A Dataset and Benchmark for Power Line Asset Inspection in UAV Images](https://mlsanity.com/paper/2311.01619/) (2023)
- [CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset](https://mlsanity.com/paper/2409.20353/) (2024)
- [Deep Learning in Automated Power Line Inspection: A Review](https://mlsanity.com/paper/2502.07826/) (2025)
- [Object detection-based inspection of power line insulators: Incipient fault detection in the low data-regime](https://mlsanity.com/paper/2212.11017/) (2022)
- [GridNet-HD: A High-Resolution Multi-Modal Dataset for LiDAR-Image Fusion on Power Line Infrastructure](https://mlsanity.com/paper/2601.13052/) (2026)
- [EDFNet: Early Fusion of Edge and Depth for Thin-Obstacle Segmentation in UAV Navigation](https://mlsanity.com/paper/2604.09694/) (2026)

## Abstract (arXiv)

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 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, showing considerable room for improvement. The STN PLAD dataset is publicly available at https://github.com/andreluizbvs/PLAD.