X Fuse: Fusing Visual Information in Text-to-Image Generation
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We introduce X Fuse, a general approach for conditioning on visual information when generating images from text. We demonstrate the potential of X Fuse in three different text-to-image generation scenarios. (i) When a bank of images is available, we retrieve and condition on a related image (Retrieve Fuse), resulting in significant improvements on the MS-COCO benchmark, gaining a state-of-the-art FID score of 6.65 in zero-shot settings. (ii) When cropped-object images are at hand, we utilize them and perform subject-driven generation (Crop Fuse), outperforming the textual inversion method while being more than x100 faster. (iii) Having oracle access to the image scene (Scene Fuse), allows us to achieve an FID score of 5.03 on MS-COCO in zero-shot settings. Our experiments indicate that X Fuse is an effective, easy-to-adapt, simple, and general approach for scenarios in which the model may benefit from additional visual information.
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