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title
Modulating Pretrained Diffusion Models for Multimodal Image Synthesis
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Modulating Pretrained Diffusion Models for Multimodal Image Synthesis
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2026-01-30 08:02:37
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Modulating Pretrained Diffusion Models for Multimodal Image Synthesis Modulating Pretrained Diffusion Models for Multimodal Image Synthesis Cusuh Ham 1 James Hays 1 Jingwan Lu 2 Krishna Kumar Singh 2 Zhifei Zhang 2 Tobias Hinz 2 1 Georgia Institute of Technology 2 Adobe Inc. SIGGRAPH Conference Proceedings 2023 [Paper] tl;dr We introduce the multimodal conditioning module (MCM), a small modulation network that enables multimodal image synthesis using pretrained diffusion models without any updates to the diffusion model parameters. Results of using MCM to condition Stable Diffusion on new modalities (underlined). Abstract We present multimodal conditioning modules (MCM) for enabling conditional image synthesis using pretrained diffusion models. Previous multimodal synthesis works rely on training networks from scratch or fine-tuning pretrained networks, both of which are computationally expensive for large, state-of-the-ar...
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