# Image Classification on ImageNet 50,000 generated samples 256x256 (test)

Source: [Image Classification on ImageNet 50,000 generated samples 256x256 (test)](<https://www.sota2.com/research/sota/image-classification-on-imagenet-50-000-generated-samples-256x256-test>)

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

Data updated: 2026-05-26T10:49:06.433Z

Evaluation of Image Classification performance on the test split of a specific dataset variant composed of 50,000 generated 256x256 samples derived from ImageNet, reporting Top-1 and Top-5 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 | Image Classification |
| Dataset (including any stated split) | ImageNet 50,000 generated samples 256x256 (test) |
| Metric | Top-1 Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 3 of 3 |
| 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

- [Top-1 Accuracy](<https://www.sota2.com/research/sota/image-classification-on-imagenet-50-000-generated-samples-256x256-test.md?metric=Top-1%20Accuracy>): Higher is better; unit: PERCENT.

- [Top-5 Accuracy](<https://www.sota2.com/research/sota/image-classification-on-imagenet-50-000-generated-samples-256x256-test.md?metric=Top-5%20Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Top-1 Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| SFM | 87.13 | Not recorded | 6a152962dbd7150506f7e2eb |
| I-CFM Proj | 79.53 | Not recorded | 6a152962dbd7150506f7e2eb |
| I-CFM | 61.83 | Not recorded | 6a152962dbd7150506f7e2eb |

### SFM

Top-1 Accuracy: 87.13. Result ID: 6a1579d6fbc373592c0da657.

[Reporting paper](<https://www.sota2.com/research/paper/6a152962dbd7150506f7e2eb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/6a152962dbd7150506f7e2eb.md>)

Recorded evaluation configuration: {"Dynamics":"Fully geometry-aware generative dynamics","Sample Count":"50,000"}. This record does not assert independent reproduction.

### I-CFM Proj

Top-1 Accuracy: 79.53. Result ID: 6a1579d6fbc373592c0da656.

[Reporting paper](<https://www.sota2.com/research/paper/6a152962dbd7150506f7e2eb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/6a152962dbd7150506f7e2eb.md>)

Recorded evaluation configuration: {"Dynamics":"Incorporating hyperspherical projection","Sample Count":"50,000"}. This record does not assert independent reproduction.

### I-CFM

Top-1 Accuracy: 61.83. Result ID: 6a1579d6fbc373592c0da655.

[Reporting paper](<https://www.sota2.com/research/paper/6a152962dbd7150506f7e2eb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6e7b1e209131cea4028c.md>)

Recorded evaluation configuration: {"Dynamics":"Euclidean flow matching","Sample Count":"50,000"}. This record does not assert independent reproduction.

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