Vision-aided GAN training involves using pretrained computer vision models in an ensemble of discriminators to improve GAN performance. Linear separability between real and fake samples in pretrained model embeddings is used as a measure to choose the most accurate pretrained models for a dataset.
Source: Ensembling Off-the-shelf Models for GAN TrainingPaper | Code | Results | Date | Stars |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |