COMPUTING PHOTOREALISTIC VERSIONS OF SYNTHETIC IMAGES

There is a region of interest of a synthetic image depicting an object from a class of objects. A trained neural image generator, having been trained to map embeddings from a latent space to photorealistic images of objects in the class, is accessed. A first embedding is computed from the latent spa...

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Bibliographische Detailangaben
Hauptverfasser: DE LA GORCE, Martin, JOHNSON, Matthew Alastair, BALTRUSAITIS, Tadas, DZIADZIO, Sebastian Karol, KOWALSKI, Marek Adam, GARBIN, Stephan Joachim, ESTELLERS CASAS, Virginia, SHOTTON, Jamie Daniel Joseph
Format: Patent
Sprache:eng ; fre ; ger
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Zusammenfassung:There is a region of interest of a synthetic image depicting an object from a class of objects. A trained neural image generator, having been trained to map embeddings from a latent space to photorealistic images of objects in the class, is accessed. A first embedding is computed from the latent space, the first embedding corresponding to an image which is similar to the region of interest while maintaining photorealistic appearance. A second embedding is computed from the latent space, the second embedding corresponding to an image which matches the synthetic image. Blending of the first embedding and the second embedding is done to form a blended embedding. At least one output image is generated from the blended embedding, the output image being more photorealistic than the synthetic image.