InsPLAD (Inspection Power Line Asset Dataset)
Introduced by Silva et al. in InsPLAD: A Dataset and Benchmark for Power Line Asset Inspection in UAV Images
InsPLAD is a Dataset for Power Line Asset Inspection containing 10,607 high-resolution Unmanned Aerial Vehicles colour images. It contains 17 unique power line assets captured from real-world operating power lines. Some of those assets (five, to be precise) are also annotated regarding their conditions. They present the following defects: corrosion (4 of them), broken/missing cap (1 of them), and bird's nest presence (1 of them).
Three image-level computer vision tasks covered by InsPLAD:
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Object detection, evaluated through the AP metric
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Defect classification, evaluated through Balanced Accuracy
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Anomaly detection, evaluated through the AUROC metric
Benchmarks
| Trend | Task | Dataset Variant | Best Model | Paper | Code |
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InsPLAD
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AttentDifferNet
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Papers
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