Synthetic Image Attribution
3 papers with code • 0 benchmarks • 0 datasets
Determine the source or origin of a generated image, such as identifying the model or tool used to create it. This information can be useful for detecting copyright infringement or for investigating digital crimes.
Benchmarks
These leaderboards are used to track progress in Synthetic Image Attribution
Most implemented papers
ArtiFact: A Large-Scale Dataset with Artificial and Factual Images for Generalizable and Robust Synthetic Image Detection
awsaf49/artifact
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Synthetic image generation has opened up new opportunities but has also created threats in regard to privacy, authenticity, and security.
A Siamese-based Verification System for Open-set Architecture Attribution of Synthetic Images
lydialy8/openset_attribution_synthetic_images
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In the second setting, the system verifies a claim about the architecture used to generate a synthetic image, utilizing one or multiple reference images generated by the claimed architecture.
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy
Modern computer vision offers a great variety of models to practitioners, and selecting a model from multiple options for specific applications can be challenging.
