# Image Classification on CIFAR-10-C Severity 5 Mild Scenario

Source: [Image Classification on CIFAR-10-C Severity 5 Mild Scenario](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario>)

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

Data updated: 2026-07-02T08:19:46.696Z

Evaluation of Image Classification model robustness on the CIFAR-10-C dataset specifically configured at Severity Level 5 under mild scenario conditions, reporting performance across various common corruptions (e.g., noise, blur, compression).

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) | CIFAR-10-C Severity 5 Mild Scenario |
| Metric | Accuracy (Gaussian Noise) |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 8 of 8 |
| 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

- [Accuracy (Gaussian Noise)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Accuracy%20(Gaussian%20Noise)>): Higher is better; unit: PERCENT.

- [Accuracy (Shot Noise)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Accuracy%20(Shot%20Noise)>): Higher is better; unit: PERCENT.

- [Accuracy (Impulse Noise)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Accuracy%20(Impulse%20Noise)>): Higher is better; unit: PERCENT.

- [Accuracy (Speckle Noise)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Accuracy%20(Speckle%20Noise)>): Higher is better; unit: PERCENT.

- [Accuracy (Gaussian Blur)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Accuracy%20(Gaussian%20Blur)>): Higher is better; unit: PERCENT.

- [Accuracy (Brightness)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Accuracy%20(Brightness)>): Higher is better; unit: PERCENT.

- [Accuracy (Spatter)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Accuracy%20(Spatter)>): Higher is better; unit: PERCENT.

- [Accuracy (Contrast)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Accuracy%20(Contrast)>): Higher is better; unit: PERCENT.

- [Accuracy (Elastic Transform)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Accuracy%20(Elastic%20Transform)>): Higher is better; unit: PERCENT.

- [Accuracy (Pixelate)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Accuracy%20(Pixelate)>): Higher is better; unit: PERCENT.

- [Accuracy (JPEG Compression)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Accuracy%20(JPEG%20Compression)>): Higher is better; unit: PERCENT.

- [Accuracy (Saturate)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Accuracy%20(Saturate)>): Higher is better; unit: PERCENT.

- [Average Accuracy (C5 Mild)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-severity-5-mild-scenario.md?metric=Average%20Accuracy%20(C5%20Mild)>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Accuracy (Gaussian Noise) | Result date | Report paper |
| --- | --- | --- | --- |
| Grad | 62.82 | Not recorded | 6a45f082dc71372d7795a1b9 |
| Naive | 62.02 | Not recorded | 6a45f082dc71372d7795a1b9 |
| SVGD | 61.28 | Not recorded | 6a45f082dc71372d7795a1b9 |
| SAR | 41.4 | Not recorded | 6a45f082dc71372d7795a1b9 |
| KL | 34.63 | Not recorded | 6a45f082dc71372d7795a1b9 |
| DeYO | 33.35 | Not recorded | 6a45f082dc71372d7795a1b9 |
| CLIP-ViT-B-32 | 25.21 | Not recorded | 6a45f082dc71372d7795a1b9 |
| Tent | 13.54 | Not recorded | 6a45f082dc71372d7795a1b9 |

### Grad

Accuracy (Gaussian Noise): 62.82. Result ID: 6a461f2160b88bb33984dff6.

[Reporting paper](<https://www.sota2.com/research/paper/6a45f082dc71372d7795a1b9.md>)

[Method origin paper](<https://www.sota2.com/research/paper/6a45f082dc71372d7795a1b9.md>)

Recorded evaluation configuration: {"Severity Level":"5","Batch Size":"64","Scenario":"Mild"}. This record does not assert independent reproduction.

### Naive

Accuracy (Gaussian Noise): 62.02. Result ID: 6a461f2160b88bb33984dff3.

[Reporting paper](<https://www.sota2.com/research/paper/6a45f082dc71372d7795a1b9.md>)

[Method origin paper](<https://www.sota2.com/research/paper/6a45f082dc71372d7795a1b9.md>)

Recorded evaluation configuration: {"Severity Level":"5","Batch Size":"64","Scenario":"Mild"}. This record does not assert independent reproduction.

### SVGD

Accuracy (Gaussian Noise): 61.28. Result ID: 6a461f2160b88bb33984dff4.

[Reporting paper](<https://www.sota2.com/research/paper/6a45f082dc71372d7795a1b9.md>)

[Method origin paper](<https://www.sota2.com/research/paper/6a45f082dc71372d7795a1b9.md>)

Recorded evaluation configuration: {"Severity Level":"5","Batch Size":"64","Scenario":"Mild"}. This record does not assert independent reproduction.

### SAR

Accuracy (Gaussian Noise): 41.4. Result ID: 6a461f2160b88bb33984dff1.

[Reporting paper](<https://www.sota2.com/research/paper/6a45f082dc71372d7795a1b9.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6e961e209131cea40e77.md>)

Recorded evaluation configuration: {"Severity Level":"5","Batch Size":"64","Scenario":"Mild"}. This record does not assert independent reproduction.

### KL

Accuracy (Gaussian Noise): 34.63. Result ID: 6a461f2160b88bb33984dff5.

[Reporting paper](<https://www.sota2.com/research/paper/6a45f082dc71372d7795a1b9.md>)

[Method origin paper](<https://www.sota2.com/research/paper/6a45f082dc71372d7795a1b9.md>)

Recorded evaluation configuration: {"Severity Level":"5","Batch Size":"64","Scenario":"Mild"}. This record does not assert independent reproduction.

### DeYO

Accuracy (Gaussian Noise): 33.35. Result ID: 6a461f2160b88bb33984dff2.

[Reporting paper](<https://www.sota2.com/research/paper/6a45f082dc71372d7795a1b9.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa72801e209131cea56d2d.md>)

[Implementation](<https://whitesnowdrop.github.io/DeYO/>)

Recorded evaluation configuration: {"Severity Level":"5","Batch Size":"64","Scenario":"Mild"}. This record does not assert independent reproduction.

### CLIP-ViT-B-32

Accuracy (Gaussian Noise): 25.21. Result ID: 6a461f2160b88bb33984dfef.

[Reporting paper](<https://www.sota2.com/research/paper/6a45f082dc71372d7795a1b9.md>)

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

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

Recorded evaluation configuration: {"Severity Level":"5","Batch Size":"64","Scenario":"Mild"}. This record does not assert independent reproduction.

### Tent

Accuracy (Gaussian Noise): 13.54. Result ID: 6a461f2160b88bb33984dff0.

[Reporting paper](<https://www.sota2.com/research/paper/6a45f082dc71372d7795a1b9.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69941e209131cea22d2b.md>)

Recorded evaluation configuration: {"Severity Level":"5","Batch Size":"64","Scenario":"Mild"}. This record does not assert independent reproduction.

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