# Infringement Model Detection on FFHQ

Source: [Infringement Model Detection on FFHQ](<https://www.sota2.com/research/sota/infringement-model-detection-on-ffhq>)

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

Data updated: 2026-02-26T06:07:43.175Z

Evaluation of a model's ability to detect infringement using the FFHQ dataset, measured by standard binary classification metrics (TP, FP, TN, FN, 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 | Infringement Model Detection |
| Dataset (including any stated split) | FFHQ |
| Metric | True Positives |
| Unit | SCALAR |
| Direction | Higher is better |
| Results loaded | 2 of 2 |
| 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

- [True Positives](<https://www.sota2.com/research/sota/infringement-model-detection-on-ffhq.md?metric=True%20Positives>): Higher is better; unit: SCALAR.

- [False Positives](<https://www.sota2.com/research/sota/infringement-model-detection-on-ffhq.md?metric=False%20Positives>): Lower is better; unit: SCALAR.

- [True Negatives](<https://www.sota2.com/research/sota/infringement-model-detection-on-ffhq.md?metric=True%20Negatives>): Higher is better; unit: SCALAR.

- [False Negatives](<https://www.sota2.com/research/sota/infringement-model-detection-on-ffhq.md?metric=False%20Negatives>): Lower is better; unit: SCALAR.

- [Accuracy](<https://www.sota2.com/research/sota/infringement-model-detection-on-ffhq.md?metric=Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | True Positives | Result date | Report paper |
| --- | --- | --- | --- |
| CoprGuard | 10 | Not recorded | 68fa77721e209131cea73257 |
| CoprGuard | 0 | Not recorded | 68fa77721e209131cea73257 |

### CoprGuard

True Positives: 10. Result ID: 69949e463a6c3148491e7206.

[Reporting paper](<https://www.sota2.com/research/paper/68fa77721e209131cea73257.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa77721e209131cea73257.md>)

[Implementation](<https://github.com/sccsok/CoprGuard.git>)

Recorded evaluation configuration: {"Model":"DDIM","Watermark Injection Ratio R":"10%/25%/50%/100%"}. This record does not assert independent reproduction.

### CoprGuard

True Positives: 0. Result ID: 69949e463a6c3148491e7205.

[Reporting paper](<https://www.sota2.com/research/paper/68fa77721e209131cea73257.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa77721e209131cea73257.md>)

[Implementation](<https://github.com/sccsok/CoprGuard.git>)

Recorded evaluation configuration: {"Model":"DDIM","Watermark Injection Ratio R":"0"}. This record does not assert independent reproduction.

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