# Fine-grained Image Classification on Aircraft

Source: [Fine-grained Image Classification on Aircraft](<https://www.sota2.com/research/sota/fine-grained-image-classification-on-aircraft>)

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

Data updated: 2026-06-02T13:41:37.861Z

Evaluation of Fine-grained Image Classification performance on the Aircraft dataset, reporting Base, Novel, and Harmonic Mean 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 | Fine-grained Image Classification |
| Dataset (including any stated split) | Aircraft |
| Metric | Base Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 7 of 7 |
| 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

- [Base Accuracy](<https://www.sota2.com/research/sota/fine-grained-image-classification-on-aircraft.md?metric=Base%20Accuracy>): Higher is better; unit: PERCENT.

- [Novel Accuracy](<https://www.sota2.com/research/sota/fine-grained-image-classification-on-aircraft.md?metric=Novel%20Accuracy>): Higher is better; unit: PERCENT.

- [Harmonic Mean Accuracy](<https://www.sota2.com/research/sota/fine-grained-image-classification-on-aircraft.md?metric=Harmonic%20Mean%20Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Base Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| ToolFG | 74.4 | Not recorded | 6a1e6454dbd7150506f859f6 |
| ViRFT | 66.9 | Not recorded | 6a1e6454dbd7150506f859f6 |
| DiVE-k | 65.5 | Not recorded | 6a1e6454dbd7150506f859f6 |
| Fine-R1 | 61.2 | Not recorded | 6a1e6454dbd7150506f859f6 |
| Qwen2.5-VL-7B | 50.3 | Not recorded | 6a1e6454dbd7150506f859f6 |
| PromptSRC | 44.9 | Not recorded | 6a1e6454dbd7150506f859f6 |
| MaPLe | 39 | Not recorded | 6a1e6454dbd7150506f859f6 |

### ToolFG

Base Accuracy: 74.4. Result ID: 6a1edd74fbc373592c1b0923.

[Reporting paper](<https://www.sota2.com/research/paper/6a1e6454dbd7150506f859f6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/6a1e6454dbd7150506f859f6.md>)

Recorded evaluation configuration: {"Zero-shot":"true","Training":"mixed-dataset training"}. This record does not assert independent reproduction.

### ViRFT

Base Accuracy: 66.9. Result ID: 6a1edd74fbc373592c1b0920.

[Reporting paper](<https://www.sota2.com/research/paper/6a1e6454dbd7150506f859f6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa77381e209131cea71c39.md>)

Recorded evaluation configuration: {"Zero-shot":"true","Training":"mixed-dataset training"}. This record does not assert independent reproduction.

### DiVE-k

Base Accuracy: 65.5. Result ID: 6a1edd74fbc373592c1b0921.

[Reporting paper](<https://www.sota2.com/research/paper/6a1e6454dbd7150506f859f6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/69253806d6b0dd334292f3a4.md>)

Recorded evaluation configuration: {"Zero-shot":"true","Training":"mixed-dataset training"}. This record does not assert independent reproduction.

### Fine-R1

Base Accuracy: 61.2. Result ID: 6a1edd74fbc373592c1b0922.

[Reporting paper](<https://www.sota2.com/research/paper/6a1e6454dbd7150506f859f6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/698abb81c97a0b3e3b5ddf45.md>)

Recorded evaluation configuration: {"Zero-shot":"true","Training":"mixed-dataset training"}. This record does not assert independent reproduction.

### Qwen2.5-VL-7B

Base Accuracy: 50.3. Result ID: 6a1edd74fbc373592c1b091d.

[Reporting paper](<https://www.sota2.com/research/paper/6a1e6454dbd7150506f859f6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa773a1e209131cea71d3c.md>)

Recorded evaluation configuration: {"Zero-shot":"true","Training":"mixed-dataset training"}. This record does not assert independent reproduction.

### PromptSRC

Base Accuracy: 44.9. Result ID: 6a1edd74fbc373592c1b091f.

[Reporting paper](<https://www.sota2.com/research/paper/6a1e6454dbd7150506f859f6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa705e1e209131cea4aa58.md>)

Recorded evaluation configuration: {"Zero-shot":"true","Training":"mixed-dataset training"}. This record does not assert independent reproduction.

### MaPLe

Base Accuracy: 39. Result ID: 6a1edd74fbc373592c1b091e.

[Reporting paper](<https://www.sota2.com/research/paper/6a1e6454dbd7150506f859f6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6ef21e209131cea4311c.md>)

[Implementation](<https://github.com/muzairkhattak/multimodal-prompt-learning>)

Recorded evaluation configuration: {"Zero-shot":"true","Training":"mixed-dataset training"}. This record does not assert independent reproduction.

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