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State-of-the-Art Image Generative Models

arankomatsuzaki.wordpress.com · 2,031 words · saved by 1 readers

I have aggregated some of the SotA image generative models released recently, with short summaries, visualizations and comments. The overall development is summarized, and the future trends are spe…

I have aggregated some of the SotA image generative models released recently, with short summaries, visualizations and comments. The overall development is summarized, and the future trends are speculated. Many of the statements and the results here are easily applicable to other non-textual modalities, such as audio and video. Summary: The papers we featured in this post belong to either of the following paradigms of SotA image generative models: VAE: VDVAE and VQVAE variants offer SotA diversity (NLL or recall). Furthermore, the sampling speed of VAEs without discrete bottleneck (e.g. VDVAE)

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