# Object Detection on Outdoor RGB-D dataset

Source: [Object Detection on Outdoor RGB-D dataset](<https://www.sota2.com/research/sota/object-detection-on-outdoor-rgb-d-dataset>)

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

Data updated: 2026-03-09T06:39:12.574Z

Evaluation of Object Detection performance on the Outdoor RGB-D dataset, reporting mean Average Precision (mAP) and category-specific performance metrics for Vehicle, Human, and Animal classes.

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) | Outdoor RGB-D dataset |
| Metric | mAP |
| 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

- [mAP](<https://www.sota2.com/research/sota/object-detection-on-outdoor-rgb-d-dataset.md?metric=mAP>): Higher is better; unit: PERCENT.

- [AP (Vehicle)](<https://www.sota2.com/research/sota/object-detection-on-outdoor-rgb-d-dataset.md?metric=AP%20(Vehicle)>): Higher is better; unit: PERCENT.

- [AP (Human)](<https://www.sota2.com/research/sota/object-detection-on-outdoor-rgb-d-dataset.md?metric=AP%20(Human)>): Higher is better; unit: PERCENT.

- [AP (Animal)](<https://www.sota2.com/research/sota/object-detection-on-outdoor-rgb-d-dataset.md?metric=AP%20(Animal)>): Higher is better; unit: PERCENT.

## Recorded results

| Method | mAP | Result date | Report paper |
| --- | --- | --- | --- |
| depth-aware hyper-involution | 80.2 | Not recorded | 68fa70be1e209131cea4d049 |
| FETNet | 78.4 | Not recorded | 68fa70be1e209131cea4d049 |

### depth-aware hyper-involution

mAP: 80.2. Result ID: 69ae693e6dbb7075b955d2a4.

[Reporting paper](<https://www.sota2.com/research/paper/68fa70be1e209131cea4d049.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa70be1e209131cea4d049.md>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### FETNet

mAP: 78.4. Result ID: 69ae693e6dbb7075b955d2a3.

[Reporting paper](<https://www.sota2.com/research/paper/68fa70be1e209131cea4d049.md>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

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