CVAug 19, 2023

AltDiffusion: A Multilingual Text-to-Image Diffusion Model

Meta AI
arXiv:2308.09991v254 citationsh-index: 18Has Code
Originality Incremental advance
AI Analysis

This addresses the problem of underserved users in non-English languages, enabling global expansion of T2I models, though it is incremental as it builds on existing diffusion methods.

The paper tackles the limited language support in text-to-image diffusion models by introducing AltDiffusion, a multilingual model that supports eighteen languages and outperforms state-of-the-art models like Stable Diffusion in multilingual understanding, especially for culture-specific concepts, while maintaining comparable image quality.

Large Text-to-Image(T2I) diffusion models have shown a remarkable capability to produce photorealistic and diverse images based on text inputs. However, existing works only support limited language input, e.g., English, Chinese, and Japanese, leaving users beyond these languages underserved and blocking the global expansion of T2I models. Therefore, this paper presents AltDiffusion, a novel multilingual T2I diffusion model that supports eighteen different languages. Specifically, we first train a multilingual text encoder based on the knowledge distillation. Then we plug it into a pretrained English-only diffusion model and train the model with a two-stage schema to enhance the multilingual capability, including concept alignment and quality improvement stage on a large-scale multilingual dataset. Furthermore, we introduce a new benchmark, which includes Multilingual-General-18(MG-18) and Multilingual-Cultural-18(MC-18) datasets, to evaluate the capabilities of T2I diffusion models for generating high-quality images and capturing culture-specific concepts in different languages. Experimental results on both MG-18 and MC-18 demonstrate that AltDiffusion outperforms current state-of-the-art T2I models, e.g., Stable Diffusion in multilingual understanding, especially with respect to culture-specific concepts, while still having comparable capability for generating high-quality images. All source code and checkpoints could be found in https://github.com/superhero-7/AltDiffuson.

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Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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