# Effect of Annotation Errors on Drone Detection with YOLOv3

arXiv: https://arxiv.org/abs/2004.01059 · HTML: https://mlsanity.com/paper/2004.01059/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Apr 2020.

## Built on by (most cited first, 7 of 7)

- [Identifying Label Errors in Object Detection Datasets by Loss Inspection](https://mlsanity.com/paper/2303.06999/) (2023)
- [Semi-Automatic Annotation For Visual Object Tracking](https://mlsanity.com/paper/2101.06977/) (2021)
- [Strong Baseline: Multi-UAV Tracking via YOLOv12 with BoT-SORT-ReID](https://mlsanity.com/paper/2503.17237/) (2025)
- [Vision-Based Anti Unmanned Aerial Technology: Opportunities and Challenges](https://mlsanity.com/paper/2507.10006/) (2025)
- [Improved Hard Example Mining Approach for Single Shot Object Detectors](https://mlsanity.com/paper/2202.13080/) (2022)
- [Deep Active Learning with Noisy Oracle in Object Detection](https://mlsanity.com/paper/2310.00372/) (2023)
- [DronePose: The identification, segmentation, and orientation detection of drones via neural networks](https://mlsanity.com/paper/2112.05488/) (2021)

## Abstract (arXiv)

Following the recent advances in deep networks, object detection and tracking algorithms with deep learning backbones have been improved significantly; however, this rapid development resulted in the necessity of large amounts of annotated labels. Even if the details of such semi-automatic annotation processes for most of these datasets are not known precisely, especially for the video annotations, some automated labeling processes are usually employed. Unfortunately, such approaches might result with erroneous annotations. In this work, different types of annotation errors for object detection problem are simulated and the performance of a popular state-of-the-art object detector, YOLOv3, with erroneous annotations during training and testing stages is examined. Moreover, some inevitable annotation errors in CVPR-2020 Anti-UAV Challenge dataset is also examined in this manner, while proposing a solution to correct such annotation errors of this valuable data set.