# Object Detection on Road Damage Dataset (Public Leaderboard) Source: [Object Detection on Road Damage Dataset (Public Leaderboard)]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:52:05.437Z Evaluation of Object Detection performance on the Road Damage Dataset (Public Leaderboard), measured using Mean F1 Score. A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. | Scope | Recorded value | | --- | --- | | Task | Object Detection | | Dataset (including any stated split) | Road Damage Dataset (Public Leaderboard) | | Metric | Mean F1 Score | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 1 of 1 | | Coverage | All results currently returned for this benchmark | Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol. ## Metrics - [Mean F1 Score](): Higher is better; unit: PERCENT. ## Recorded results | Method | Mean F1 Score | Result date | Report paper | | --- | --- | --- | --- | | Mask R-CNN | 52.8 | Not recorded | 68fa65171e209131cea0830d | ### Mask R-CNN Mean F1 Score: 52.8. Result ID: 698c9c520b614d12cff1f118. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Backbone":"ResNet-101","IoU Threshold":"50%","Framework":"Tensorflow","Input Resolution":"512x512"}. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.