Software Engineering Meets Text-to-Image Synthesis Breakthrough
Meissonic model breaks through in text-to-image synthesis, matching state-of-the-art diffusion models with non-autoregressive MIM approach & high-quality training data.
This is a Plain English Papers summary of a research paper called Meissonic: Non-Autoregressive MIM Breakthrough for Efficient High-Res Text-to-Image Synthesis. If you like these kinds of analysis, you should join AImodels.fyi or follow me on Twitter. Overview Diffusion models like Stable Diffusion have made significant progress in visual generation, but their approach differs from autoregressive language models, making it challenging to develop unified language-vision models. Recent efforts like LlamaGen have explored autoregressive image generation using discrete VQVAE tokens, but...