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| cff-version: 1.2.0 | |
| message: "If you use SynthScope in your research, please cite it." | |
| title: "SynthScope: A Unified Library and Benchmark for AI-Generated Image and Video Detection" | |
| abstract: >- | |
| SynthScope re-implements a range of state-of-the-art AI-generated (synthetic) image and video | |
| detectors behind a single configuration system, training loop, datasets, transforms, and | |
| metrics, so that different methods can be trained and benchmarked under identical conditions, | |
| with results reported per generator/source. | |
| type: software | |
| authors: | |
| # TODO(maintainer): verify the author name(s) and affiliation, and add ORCID(s). | |
| - family-names: "Salehi Dehnavi" | |
| given-names: "Seyed" | |
| email: "s.salehidehnavi@uva.nl" | |
| affiliation: "University of Amsterdam" | |
| repository-code: "https://github.com/SMSD75/SynthScope" | |
| url: "https://github.com/SMSD75/SynthScope" | |
| license: Apache-2.0 | |
| version: "0.1.0" | |
| keywords: | |
| - AI-generated image detection | |
| - synthetic media detection | |
| - deepfake detection | |
| - benchmark | |