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Image Generation
Image Generation (synthesis) is the task of generating new images from an existing dataset.
- Unconditional generation refers to generating samples unconditionally from the dataset, i.e. $p(y)$
- Conditional image generation (subtask) refers to generating samples conditionally from the dataset, based on a label, i.e. $p(y|x)$.
In this section, you can find state-of-the-art leaderboards for unconditional generation. For conditional generation, and other types of image generations, refer to the subtasks.
<span style="color:grey; opacity: 0.6">( Image credit: StyleGAN )</span>
데이터셋
249개ImageNet 256x256CIFAR-10GTAV-to-Cityscapes LabelsCOCO (Common Objects in Context)ImageNet 64x64ImageNet 512x512FFHQ 256 x 256CelebA 64x64SYNTHIA-to-CityscapesImageNet 32x32LSUN Bedroom 256 x 256STL-10SYNTHIA-to-CityscapesLSUN Churches 256 x 256CIFAR-10ImageNet 128x128GTAV-to-Cityscapes LabelsImageNet 128x128Cityscapes Labels-to-PhotoCUBFFHQ 1024 x 1024GenEvalCelebA-HQ 256x256PIE-BenchCelebA 256x256ADE20K Labels-to-PhotosiHarmony4COCO-Stuff Labels-to-PhotosMNISTPlaces2