# Image Classification on ImageNet-R OOD (test)

Source: [Image Classification on ImageNet-R OOD (test)](<https://www.sota2.com/research/sota/image-classification-on-imagenet-r-ood-test>)

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

Data updated: 2026-06-25T08:46:53.464Z

Evaluation of Image Classification performance specifically on the test split of the ImageNet-R Out-of-Distribution (OOD) dataset, reporting Top-1 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-R OOD (test) |
| Metric | Top-1 Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 4 of 4 |
| 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-r-ood-test.md?metric=Top-1%20Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Top-1 Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| SS-CA | 31.89 | Not recorded | 691bfdf36750be83fe5ceb57 |
| Chen et al. | 31.69 | Not recorded | 691bfdf36750be83fe5ceb57 |
| Xiao et al. | 31.65 | Not recorded | 691bfdf36750be83fe5ceb57 |
| Conventional Training | 31.63 | Not recorded | 691bfdf36750be83fe5ceb57 |

### SS-CA

Top-1 Accuracy: 31.89. Result ID: 6a3ceaeafbc373592c52a5bb.

[Reporting paper](<https://www.sota2.com/research/paper/691bfdf36750be83fe5ceb57.md>)

[Method origin paper](<https://www.sota2.com/research/paper/691bfdf36750be83fe5ceb57.md>)

Recorded evaluation configuration: {"Backbone":"CLIP (ViT /32b)","Evaluation Protocol":"Linear Probing"}. This record does not assert independent reproduction.

### Chen et al.

Top-1 Accuracy: 31.69. Result ID: 6a3ceaeafbc373592c52a5ba.

[Reporting paper](<https://www.sota2.com/research/paper/691bfdf36750be83fe5ceb57.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa780b1e209131cea7681b.md>)

Recorded evaluation configuration: {"Backbone":"CLIP (ViT /32b)","Evaluation Protocol":"Linear Probing"}. This record does not assert independent reproduction.

### Xiao et al.

Top-1 Accuracy: 31.65. Result ID: 6a3ceaeafbc373592c52a5b9.

[Reporting paper](<https://www.sota2.com/research/paper/691bfdf36750be83fe5ceb57.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6ef21e209131cea4315e.md>)

[Implementation](<https://github.com/Coxy7/robust-finetuning>)

Recorded evaluation configuration: {"Backbone":"CLIP (ViT /32b)","Evaluation Protocol":"Linear Probing"}. This record does not assert independent reproduction.

### Conventional Training

Top-1 Accuracy: 31.63. Result ID: 6a3ceaeafbc373592c52a5b8.

[Reporting paper](<https://www.sota2.com/research/paper/691bfdf36750be83fe5ceb57.md>)

Recorded evaluation configuration: {"Backbone":"CLIP (ViT /32b)","Evaluation Protocol":"Linear Probing"}. This record does not assert independent reproduction.

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