Text-based sequential image generation

Valeria Efimova; Andrey Filchenkov

doi:10.1117/12.2622734

4 March 2022 Text-based sequential image generation

Valeria Efimova, Andrey Filchenkov

Proceedings Volume 12084, Fourteenth International Conference on Machine Vision (ICMV 2021); 120840H (2022) https://doi.org/10.1117/12.2622734
Event: Fourteenth International Conference on Machine Vision (ICMV 2021), 2021, Rome, Italy

Abstract

Despite recent impressive results of generative adversarial networks on text-to-image generation, the generation of complex scenes with multiple objects in the complicated background remains challenging; moreover, end-to-end text-toimage generation still suffers from poor image quality. In this work, we propose a sequential algorithm of text-to-image generation, which allows synthesizing high-quality images (more than 1024x1024 pixels). The proposed approach consists of location inference, key objects extraction, image search, layout generation, and image harmonization stages. We compare the suggested approach with state-of-the-art image generation model DALL-E with text-to-image mapping. Our approach demonstrates the effectiveness and visual plausibility of the generated images based on golden section layouts.

Citation Download Citation

Valeria Efimova and Andrey Filchenkov "Text-based sequential image generation", Proc. SPIE 12084, Fourteenth International Conference on Machine Vision (ICMV 2021), 120840H (4 March 2022); https://doi.org/10.1117/12.2622734

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