# Image Classification on Oxford Flowers 102 (Base/Novel/HM Metrics)

Source: [Image Classification on Oxford Flowers 102 (Base/Novel/HM Metrics)](<https://www.sota2.com/research/sota/image-classification-on-oxford-flowers-102-base-novel-hm-metrics>)

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

Data updated: 2026-03-18T09:09:46.481Z

Evaluation of Image Classification performance on the Oxford Flowers 102 dataset, specifically reporting Base, Novel, and Harmonic Mean (HM) metrics, suggesting a few-shot or generalization evaluation setup.

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 | Image Classification |
| Dataset (including any stated split) | Oxford Flowers 102 |
| Metric | Base Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 13 of 13 |
| 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/image-classification-on-oxford-flowers-102-base-novel-hm-metrics.md?metric=Base%20Accuracy>): Higher is better; unit: PERCENT.

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

- [HM Score](<https://www.sota2.com/research/sota/image-classification-on-oxford-flowers-102-base-novel-hm-metrics.md?metric=HM%20Score>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Base Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| HPT | 98.17 | Not recorded | 69ba31930636e5bf4afc08c3 |
| P-SRC | 98.07 | Not recorded | 69ba31930636e5bf4afc08c3 |
| MMA | 97.77 | Not recorded | 69ba31930636e5bf4afc08c3 |
| ProDA | 97.7 | Not recorded | 69ba31930636e5bf4afc08c3 |
| CoOp | 97.6 | Not recorded | 69ba31930636e5bf4afc08c3 |
| LwEIB | 97.53 | Not recorded | 69ba31930636e5bf4afc08c3 |
| HeBA | 97.37 | Not recorded | 69ba31930636e5bf4afc08c3 |
| LASP-V | 97.17 | Not recorded | 69ba31930636e5bf4afc08c3 |
| MaPLe | 95.92 | Not recorded | 69ba31930636e5bf4afc08c3 |
| KgCoOp | 95 | Not recorded | 69ba31930636e5bf4afc08c3 |
| CoOpOp | 94.87 | Not recorded | 69ba31930636e5bf4afc08c3 |
| RPO | 94.13 | Not recorded | 69ba31930636e5bf4afc08c3 |
| CLIP | 72.08 | Not recorded | 69ba31930636e5bf4afc08c3 |

### HPT

Base Accuracy: 98.17. Result ID: 69ba6bbc47f34ce924a48f72.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa71761e209131cea515bb.md>)

[Implementation](<https://github.com/Vill-Lab/2024-AAAI-HPT>)

Recorded evaluation configuration: {"Year":"2024"}. This record does not assert independent reproduction.

### P-SRC

Base Accuracy: 98.07. Result ID: 69ba6bbc47f34ce924a48f71.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

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

Recorded evaluation configuration: {"Year":"2023"}. This record does not assert independent reproduction.

### MMA

Base Accuracy: 97.77. Result ID: 69ba6bbc47f34ce924a48f73.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa74c21e209131cea6392b.md>)

Recorded evaluation configuration: {"Year":"2024"}. This record does not assert independent reproduction.

### ProDA

Base Accuracy: 97.7. Result ID: 69ba6bbc47f34ce924a48f6c.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6c771e209131cea34184.md>)

Recorded evaluation configuration: {"Year":"2022"}. This record does not assert independent reproduction.

### CoOp

Base Accuracy: 97.6. Result ID: 69ba6bbc47f34ce924a48f6a.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6d8b1e209131cea3a814.md>)

[Implementation](<https://github.com/KaiyangZhou/CoOp>)

Recorded evaluation configuration: {"Year":"2022"}. This record does not assert independent reproduction.

### LwEIB

Base Accuracy: 97.53. Result ID: 69ba6bbc47f34ce924a48f74.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

Recorded evaluation configuration: {"Year":"2025"}. This record does not assert independent reproduction.

### HeBA

Base Accuracy: 97.37. Result ID: 69ba6bbc47f34ce924a48f75.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

[Method origin paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

[Implementation](<https://github.com/Jahid12012021/VLM-HeBA>)

Recorded evaluation configuration: {"Year":"Ours"}. This record does not assert independent reproduction.

### LASP-V

Base Accuracy: 97.17. Result ID: 69ba6bbc47f34ce924a48f6f.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6ef11e209131cea43118.md>)

Recorded evaluation configuration: {"Year":"2023"}. This record does not assert independent reproduction.

### MaPLe

Base Accuracy: 95.92. Result ID: 69ba6bbc47f34ce924a48f6e.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

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

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

Recorded evaluation configuration: {"Year":"2023"}. This record does not assert independent reproduction.

### KgCoOp

Base Accuracy: 95. Result ID: 69ba6bbc47f34ce924a48f6d.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6ee91e209131cea42d7a.md>)

Recorded evaluation configuration: {"Year":"2023"}. This record does not assert independent reproduction.

### CoOpOp

Base Accuracy: 94.87. Result ID: 69ba6bbc47f34ce924a48f6b.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

Recorded evaluation configuration: {"Year":"2022"}. This record does not assert independent reproduction.

### RPO

Base Accuracy: 94.13. Result ID: 69ba6bbc47f34ce924a48f70.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa71201e209131cea4f558.md>)

[Implementation](<https://github.com/mlvlab/RPO>)

Recorded evaluation configuration: {"Year":"2023"}. This record does not assert independent reproduction.

### CLIP

Base Accuracy: 72.08. Result ID: 69ba6bbc47f34ce924a48f69.

[Reporting paper](<https://www.sota2.com/research/paper/69ba31930636e5bf4afc08c3.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69581e209131cea21ad0.md>)

[Implementation](<https://github.com/OpenAI/CLIP>)

Recorded evaluation configuration: {"Year":"2021"}. This record does not assert independent reproduction.

Page 1 of 1. This is an index page, not the full collection.
