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Traditional Classification Neural Networks are Good Generators: They are Competitive with DDPMs and GANs
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2026-02-26 14:55:55
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Traditional Classification Neural Networks are Good Generators: They are Competitive with DDPMs and GANs Traditional Classification Neural Networks are Good Generators: They are Competitive with DDPMs and GANs Technical Report Guangrun Wang , Philip H.S. Torr TVG of University of Oxford Paper GitHub Our Result Overview Abstract Classifiers and generators have long been separated. We break down this separation and showcase that conventional neural network classifiers can generate high-quality images of a large number of categories, being comparable to the state-of-the-art generative models (e.g., DDPMs and GANs). We achieve this by computing the partial derivative of the classification loss function with respect to the input to optimize the input to produce an image. Since it is widely known that directly optimizing the inputs is similar to targeted adversarial attacks incapable of generating human-meaningful images, we propose a mask-based stochastic re...
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