Present and Future Generalization of Synthetic Image Detectors
The continued release of new and better image generation models increases the
demand for synthetic image detectors. In such a dynamic field, detectors need
to be able to generalize widely and be robust to uncontrolled alterations. The
present work is motivated by this setting, when looking at the role of time,
image transformations and data sources, for detector generalization. In these
experiments, none of the evaluated detectors is found universal, but results
indicate an ensemble could be. Experiments on data collected in the wild show
this task to be more challenging than the one defined by large-scale datasets,
pointing to a gap between experimentation and actual practice. Finally, we
observe a race equilibrium effect, where better generators lead to better
detectors, and vice versa. We hypothesize this pushes the field towards a
perpetually close race between generators and detectors.
66f3cc15ec5d94d8cb43ada9
Pablo Bernabeu-Perez
extracted_confirmed
2024-09-25T09:05:43.094Z
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/avatars/d0309ac9408530a74f1799e175cc5fad.svg
Pablo Bernabeu
user
pabberpe
66f3cc15ec5d94d8cb43adaa
Enrique Lopez-Cuena
66f3cc15ec5d94d8cb43adab
Dario Garcia-Gasulla
extracted_confirmed
2024-09-25T08:50:20.388Z
62f7a16192950415b637e201
https://cdn-avatars.huggingface.co/v1/production/uploads/62f7a16192950415b637e201/4IIqYap43vujvSuql68Vj.jpeg
Dario
user
dariog
Present and Future Generalization of Synthetic Image Detectors
The continued release of new and better image generation models increases the
demand for synthetic image detectors. In such a dynamic field, detectors need
to be able to generalize widely and be robust to uncontrolled alterations. The
present work is motivated by this setting, when looking at the role of time,
image transformations and data sources, for detector generalization. In these
experiments, none of the evaluated detectors is found universal, but results
indicate an ensemble could be. Experiments on data collected in the wild show
this task to be more challenging than the one defined by large-scale datasets,
pointing to a gap between experimentation and actual practice. Finally, we
observe a race equilibrium effect, where better generators lead to better
detectors, and vice versa. We hypothesize this pushes the field towards a
perpetually close race between generators and detectors.
Synthetic image detectors must generalize widely and resist alterations in a rapidly evolving field, where the improvement of generators drives advancements in detectors and vice versa.
image generation models synthetic image detectors detector generalization image transformations race equilibrium effect