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- W4288804709 abstract "Whereas generative adversarial networks are capable of synthesizing highly realistic images of faces, cats, landscapes, or almost any other single category, paint-by-text synthesis engines can -- from a single text prompt -- synthesize realistic images of seemingly endless categories with arbitrary configurations and combinations. This powerful technology poses new challenges to the photo-forensic community. Motivated by the fact that paint by text is not based on explicit geometric or physical models, and the human visual system's general insensitivity to lighting inconsistencies, we provide an initial exploration of the lighting consistency of DALL-E-2 synthesized images to determine if physics-based forensic analyses will prove fruitful in detecting this new breed of synthetic media." @default.
- W4288804709 created "2022-07-30" @default.
- W4288804709 creator A5041843517 @default.
- W4288804709 date "2022-07-27" @default.
- W4288804709 modified "2023-09-23" @default.
- W4288804709 title "Lighting (In)consistency of Paint by Text" @default.
- W4288804709 doi "https://doi.org/10.48550/arxiv.2207.13744" @default.
- W4288804709 hasPublicationYear "2022" @default.
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