# Object Detection on Real-world scaled vehicle dataset

Source: [Object Detection on Real-world scaled vehicle dataset](<https://www.sota2.com/research/sota/object-detection-on-real-world-scaled-vehicle-dataset>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-02-26T05:23:22.835Z

Evaluation of Object Detection performance on the Real-world scaled vehicle dataset, reporting Average Precision at IoU 0.5 and Confidence scores.

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) | Real-world scaled vehicle dataset |
| Metric | AP@0.5 |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 4 of 4 |
| 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

- [AP@0.5](<https://www.sota2.com/research/sota/object-detection-on-real-world-scaled-vehicle-dataset.md?metric=AP%400.5>): Higher is better; unit: PERCENT.

- [Confidence Score](<https://www.sota2.com/research/sota/object-detection-on-real-world-scaled-vehicle-dataset.md?metric=Confidence%20Score>): Higher is better; unit: PERCENT.

## Recorded results

| Method | AP@0.5 | Result date | Report paper |
| --- | --- | --- | --- |
| YOLOv4 | 96 | Not recorded | 68fa6c121e209131cea31eb6 |
| EffDetD0 | 94 | Not recorded | 68fa6c121e209131cea31eb6 |
| DTA | 61 | Not recorded | 68fa6c121e209131cea31eb6 |
| DTA | 34 | Not recorded | 68fa6c121e209131cea31eb6 |

### YOLOv4

AP@0.5: 96. Result ID: 698ec6edffc3901de0a104c2.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c121e209131cea31eb6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa67721e209131cea16500.md>)

[Implementation](<https://github.com/AlexeyAB/darknet>)

Recorded evaluation configuration: {"Texture":"Normal"}. This record does not assert independent reproduction.

### EffDetD0

AP@0.5: 94. Result ID: 698ec6edffc3901de0a104c0.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c121e209131cea31eb6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa680e1e209131cea19eb9.md>)

[Implementation](<https://github.com/google/automl/tree/master/efficientdet>)

Recorded evaluation configuration: {"Texture":"Normal"}. This record does not assert independent reproduction.

### DTA

AP@0.5: 61. Result ID: 698ec6edffc3901de0a104c3.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c121e209131cea31eb6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6c121e209131cea31eb6.md>)

[Implementation](<https://islab-ai.github.io/dta-cvpr2022/>)

Recorded evaluation configuration: {"Model":"YOLOv4","Texture":"DTA"}. This record does not assert independent reproduction.

### DTA

AP@0.5: 34. Result ID: 698ec6edffc3901de0a104c1.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c121e209131cea31eb6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6c121e209131cea31eb6.md>)

[Implementation](<https://islab-ai.github.io/dta-cvpr2022/>)

Recorded evaluation configuration: {"Model":"EffDetD0","Texture":"DTA"}. This record does not assert independent reproduction.

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