# 2D Object Detection on KITTI MV3D (val)

Source: [2D Object Detection on KITTI MV3D (val)](<https://www.sota2.com/research/sota/2d-object-detection-on-kitti-mv3d-val>)

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

Data updated: 2026-02-26T05:21:07.069Z

Evaluation of 2D Object Detection performance on the validation split of the KITTI MV3D dataset, reporting 2D Average Precision (AP) for Intersection over Union thresholds of 0.5 and 0.7 across Easy and Moderate difficulty levels.

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 | 2D Object Detection |
| Dataset (including any stated split) | KITTI MV3D (val) |
| Metric | 2D AP @ 0.5 (Easy) |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 2 of 2 |
| 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

- [2D AP @ 0.5 (Easy)](<https://www.sota2.com/research/sota/2d-object-detection-on-kitti-mv3d-val.md?metric=2D%20AP%20%40%200.5%20(Easy)>): Higher is better; unit: PERCENT.

- [2D AP @ 0.7 (Easy)](<https://www.sota2.com/research/sota/2d-object-detection-on-kitti-mv3d-val.md?metric=2D%20AP%20%40%200.7%20(Easy)>): Higher is better; unit: PERCENT.

- [2D AP @ 0.5 (Moderate)](<https://www.sota2.com/research/sota/2d-object-detection-on-kitti-mv3d-val.md?metric=2D%20AP%20%40%200.5%20(Moderate)>): Higher is better; unit: PERCENT.

- [2D AP @ 0.7 (Moderate)](<https://www.sota2.com/research/sota/2d-object-detection-on-kitti-mv3d-val.md?metric=2D%20AP%20%40%200.7%20(Moderate)>): Higher is better; unit: PERCENT.

## Recorded results

| Method | 2D AP @ 0.5 (Easy) | Result date | Report paper |
| --- | --- | --- | --- |
| MonoDIS | 96.7 | Not recorded | 68fa67561e209131cea159c9 |
| MonoDIS | 96.1 | Not recorded | 68fa67561e209131cea159c9 |

### MonoDIS

2D AP @ 0.5 (Easy): 96.7. Result ID: 698d2d938b517eb4331f934d.

[Reporting paper](<https://www.sota2.com/research/paper/68fa67561e209131cea159c9.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa67561e209131cea159c9.md>)

[Implementation](<http://github.com/TRI-ML/sdflabel>)

Recorded evaluation configuration: {"Training Label Source":"Autolabels"}. This record does not assert independent reproduction.

### MonoDIS

2D AP @ 0.5 (Easy): 96.1. Result ID: 698d2d938b517eb4331f934c.

[Reporting paper](<https://www.sota2.com/research/paper/68fa67561e209131cea159c9.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa67561e209131cea159c9.md>)

[Implementation](<http://github.com/TRI-ML/sdflabel>)

Recorded evaluation configuration: {"Training Label Source":"Original Labels"}. This record does not assert independent reproduction.

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