# Fine-grained Image Classification on Oxford Flowers 102 (test)

Source: [Fine-grained Image Classification on Oxford Flowers 102 (test)](<https://www.sota2.com/research/sota/fine-grained-image-classification-on-oxford-flowers-102-test>)

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

Data updated: 2026-06-02T13:41:37.712Z

Evaluation of Fine-grained Image Classification performance on the test split of the Oxford Flowers 102 dataset, reporting Base, Novel, and Harmonic Mean Accuracy.

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) | Oxford Flowers 102 (test) |
| Metric | Base Accuracy (B) |
| 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 (B)](<https://www.sota2.com/research/sota/fine-grained-image-classification-on-oxford-flowers-102-test.md?metric=Base%20Accuracy%20(B)>): Higher is better; unit: PERCENT.

- [Novel Accuracy (N)](<https://www.sota2.com/research/sota/fine-grained-image-classification-on-oxford-flowers-102-test.md?metric=Novel%20Accuracy%20(N)>): Higher is better; unit: PERCENT.

- [Harmonic Mean (H)](<https://www.sota2.com/research/sota/fine-grained-image-classification-on-oxford-flowers-102-test.md?metric=Harmonic%20Mean%20(H)>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Base Accuracy (B) | Result date | Report paper |
| --- | --- | --- | --- |
| ToolFG | 99.3 | Not recorded | 6a1e6454dbd7150506f859f6 |
| PromptSRC | 98.1 | Not recorded | 6a1e6454dbd7150506f859f6 |
| DiVE-k | 97.4 | Not recorded | 6a1e6454dbd7150506f859f6 |
| Fine-R1 | 96.6 | Not recorded | 6a1e6454dbd7150506f859f6 |
| MaPLe | 95.9 | Not recorded | 6a1e6454dbd7150506f859f6 |
| ViRFT | 89.5 | Not recorded | 6a1e6454dbd7150506f859f6 |
| Qwen2.5-VL-7B | 84.2 | Not recorded | 6a1e6454dbd7150506f859f6 |

### ToolFG

Base Accuracy (B): 99.3. Result ID: 6a1edd74fbc373592c1b08e4.

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

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

Recorded evaluation configuration: {"Training Strategy":"per-dataset training","Evaluation Protocol":"Zero-shot base-to-novel generalization"}. This record does not assert independent reproduction.

### PromptSRC

Base Accuracy (B): 98.1. Result ID: 6a1edd74fbc373592c1b08e0.

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

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

Recorded evaluation configuration: {"Training Strategy":"per-dataset training","Evaluation Protocol":"Zero-shot base-to-novel generalization"}. This record does not assert independent reproduction.

### DiVE-k

Base Accuracy (B): 97.4. Result ID: 6a1edd74fbc373592c1b08e2.

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

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

Recorded evaluation configuration: {"Training Strategy":"per-dataset training","Evaluation Protocol":"Zero-shot base-to-novel generalization"}. This record does not assert independent reproduction.

### Fine-R1

Base Accuracy (B): 96.6. Result ID: 6a1edd74fbc373592c1b08e3.

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

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

Recorded evaluation configuration: {"Training Strategy":"per-dataset training","Evaluation Protocol":"Zero-shot base-to-novel generalization"}. This record does not assert independent reproduction.

### MaPLe

Base Accuracy (B): 95.9. Result ID: 6a1edd74fbc373592c1b08df.

[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: {"Training Strategy":"per-dataset training","Evaluation Protocol":"Zero-shot base-to-novel generalization"}. This record does not assert independent reproduction.

### ViRFT

Base Accuracy (B): 89.5. Result ID: 6a1edd74fbc373592c1b08e1.

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

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

Recorded evaluation configuration: {"Training Strategy":"per-dataset training","Evaluation Protocol":"Zero-shot base-to-novel generalization"}. This record does not assert independent reproduction.

### Qwen2.5-VL-7B

Base Accuracy (B): 84.2. Result ID: 6a1edd74fbc373592c1b08de.

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

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

Recorded evaluation configuration: {"Training Strategy":"per-dataset training","Evaluation Protocol":"Zero-shot base-to-novel generalization"}. This record does not assert independent reproduction.

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