image-generation
Multi class one-shot image synthesis
3260 papers • 126 benchmarks • 313 datasets
The goal of Multi-class one-shot image synthesis is to learn a generative model that can generate samples with visual attributes from as few as one or more images of at least 2 related classes.
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Most implemented papers
DEff-GAN: Diverse Attribute Transfer for Few-Shot Image Synthesis
Rajiv Kumar, G. Sivakumar•Mon Feb 27 2023
The single-image GAN method is extended to model multiple images for sample synthesis and the discriminator is modified with an auxiliary classifier branch, which helps to generate a wide variety of samples and to classify the input labels.
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