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2024-09-16 04:00:34

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Open Graph

title

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De-Diffusion Makes Text a Strong Cross-Modal Interface

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site name

author

updated

2026-02-20 11:26:54

raw text

De-Diffusion De-Diffusion Makes Text a Strong Cross-Modal Interface Chen Wei 1,2 , Chenxi Liu 1 , Siyuan Qiao 1 , Zhishuai Zhang 1 , Alan Yuille 2 , Jiahui Yu 1 1 Google DeepMind , 2 Johns Hopkins University arXiv Code [coming soon!] De-Diffusion is an autoencoder whose decoder is a text-to-image diffusion model. It encodes an input image into information-rich text, which acts as a flexible interface between modalities. Abstract We demonstrate text as a strong cross-modal interface. Rather than relying on deep embeddings to connect image and language as the interface representation, our approach represents an image as text, from which we enjoy the interpretability and flexibility inherent to natural language. We employ an autoencoder that uses a pre-trained text-to-image diffusion model for decoding. The encoder is trained to transform an input image into text, which is then fed into the fixed text-to-i...

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