# Semantic Segmentation on NWPU Traffic Source: [Semantic Segmentation on NWPU Traffic]() Collection index: [llms.txt]() Data updated: 2026-07-07T09:51:21.699Z Evaluation of Semantic Segmentation performance on the NWPU Traffic dataset, reporting class-specific metrics, mIoU, Overall Accuracy (OA), and 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 | Semantic Segmentation | | Dataset (including any stated split) | NWPU Traffic | | Metric | Background Accuracy | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 8 of 8 | | 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 - [Background Accuracy](): Higher is better; unit: PERCENT. - [Airplane Accuracy](): Higher is better; unit: PERCENT. - [Car Accuracy](): Higher is better; unit: PERCENT. - [Ship Accuracy](): Higher is better; unit: PERCENT. - [Train Accuracy](): Higher is better; unit: PERCENT. - [mIoU](): Higher is better; unit: PERCENT. - [Overall Accuracy (OA)](): Higher is better; unit: PERCENT. - [F1-score](): Higher is better; unit: PERCENT. ## Recorded results | Method | Background Accuracy | Result date | Report paper | | --- | --- | --- | --- | | CSPNet | 98.73 | Not recorded | 6a4c882885dba69fef8b29de | | Deeplabv3+ | 98.66 | Not recorded | 6a4c882885dba69fef8b29de | | CMLFormer | 98.64 | Not recorded | 6a4c882885dba69fef8b29de | | GCBNet | 98.48 | Not recorded | 6a4c882885dba69fef8b29de | | FSEL | 98.47 | Not recorded | 6a4c882885dba69fef8b29de | | Scaleformer | 98.22 | Not recorded | 6a4c882885dba69fef8b29de | | UNetFormer | 97.98 | Not recorded | 6a4c882885dba69fef8b29de | | ABCNet | 97.86 | Not recorded | 6a4c882885dba69fef8b29de | ### CSPNet Background Accuracy: 98.73. Result ID: 6a4ccc0260b88bb339c9f09c. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### Deeplabv3+ Background Accuracy: 98.66. Result ID: 6a4ccc0260b88bb339c9f095. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### CMLFormer Background Accuracy: 98.64. Result ID: 6a4ccc0260b88bb339c9f09a. [Reporting paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### GCBNet Background Accuracy: 98.48. Result ID: 6a4ccc0260b88bb339c9f098. [Reporting paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### FSEL Background Accuracy: 98.47. Result ID: 6a4ccc0260b88bb339c9f09b. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### Scaleformer Background Accuracy: 98.22. Result ID: 6a4ccc0260b88bb339c9f099. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### UNetFormer Background Accuracy: 97.98. Result ID: 6a4ccc0260b88bb339c9f097. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### ABCNet Background Accuracy: 97.86. Result ID: 6a4ccc0260b88bb339c9f096. [Reporting paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.