research-article

End-to-End Text-to-Image Synthesis with Spatial Constrains

Authors:

Yutong GaoAuthors Info & Claims

ACM Transactions on Intelligent Systems and Technology (TIST), Volume 11, Issue 4

Article No.: 47, Pages 1 - 19

https://doi.org/10.1145/3391709

Published: 25 May 2020 Publication History

Abstract

Although the performance of automatically generating high-resolution realistic images from text descriptions has been significantly boosted, many challenging issues in image synthesis have not been fully investigated, due to shapes variations, viewpoint changes, pose changes, and the relations of multiple objects. In this article, we propose a novel end-to-end approach for text-to-image synthesis with spatial constraints by mining object spatial location and shape information. Instead of learning a hierarchical mapping from text to image, our algorithm directly generates multi-object fine-grained images through the guidance of the generated semantic layouts. By fusing text semantic and spatial information into a synthesis module and jointly fine-tuning them with multi-scale semantic layouts generated, the proposed networks show impressive performance in text-to-image synthesis for complex scenes. We evaluate our method both on single-object CUB dataset and multi-object MS-COCO dataset. Comprehensive experimental results demonstrate that our method significantly outperforms the state-of-the-art approaches consistently across different evaluation metrics.

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Cited By

Zeng WZhu HLin CXiao Z(2023)A survey of generative adversarial networks and their application in text-to-image synthesisElectronic Research Archive10.3934/era.202336231:12(7142-7181)Online publication date: 2023
https://doi.org/10.3934/era.2023362
M DA K(2023)TAM GAN: Tamil Text to Naturalistic Image Synthesis Using Conventional Deep Adversarial NetworksACM Transactions on Asian and Low-Resource Language Information Processing10.1145/358401922:5(1-18)Online publication date: 16-Feb-2023
https://dl.acm.org/doi/10.1145/3584019
Zhan FYu YWu RZhang JLu SLiu LKortylewski ATheobalt CXing E(2023)Multimodal Image Synthesis and Editing: The Generative AI EraIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2023.330524345:12(15098-15119)Online publication date: Dec-2023
https://doi.org/10.1109/TPAMI.2023.3305243
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Index Terms

End-to-End Text-to-Image Synthesis with Spatial Constrains
1. Computing methodologies
  1. Artificial intelligence
  2. Computer graphics
    1. Image manipulation
      1. Image processing

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cover image ACM Transactions on Intelligent Systems and Technology

ACM Transactions on Intelligent Systems and Technology Volume 11, Issue 4

Survey Paper and Regular Paper

August 2020

358 pages

ISSN:2157-6904

EISSN:2157-6912

DOI:10.1145/3401889

Editor:
Yu Zheng
JD Finance, China

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Copyright © 2020 ACM.

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Publication History

Published: 25 May 2020

Online AM: 07 May 2020

Accepted: 01 March 2020

Revised: 01 March 2020

Received: 01 July 2019

Published in TIST Volume 11, Issue 4

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Cited By

Zeng WZhu HLin CXiao Z(2023)A survey of generative adversarial networks and their application in text-to-image synthesisElectronic Research Archive10.3934/era.202336231:12(7142-7181)Online publication date: 2023
https://doi.org/10.3934/era.2023362
M DA K(2023)TAM GAN: Tamil Text to Naturalistic Image Synthesis Using Conventional Deep Adversarial NetworksACM Transactions on Asian and Low-Resource Language Information Processing10.1145/358401922:5(1-18)Online publication date: 16-Feb-2023
https://dl.acm.org/doi/10.1145/3584019
Zhan FYu YWu RZhang JLu SLiu LKortylewski ATheobalt CXing E(2023)Multimodal Image Synthesis and Editing: The Generative AI EraIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2023.330524345:12(15098-15119)Online publication date: Dec-2023
https://doi.org/10.1109/TPAMI.2023.3305243
Cheng QWen KGu X(2023)Vision-Language Matching for Text-to-Image Synthesis via Generative Adversarial NetworksIEEE Transactions on Multimedia10.1109/TMM.2022.321738425(7062-7075)Online publication date: 2023
https://doi.org/10.1109/TMM.2022.3217384
Fu ZLiu HBi XWang X(2023)Text Guided Image Inpainting Based on Generative Adversarial Network2023 8th International Conference on Computational Intelligence and Applications (ICCIA)10.1109/ICCIA59741.2023.00031(128-132)Online publication date: 23-Jun-2023
https://doi.org/10.1109/ICCIA59741.2023.00031
Zhou YShimada N(2023)Vision + Language Applications: A Survey2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW59228.2023.00090(826-842)Online publication date: Jun-2023
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Tan YLee CNeo MLim KLim JAlqahtani A(2023)Recent Advances in Text-to-Image Synthesis: Approaches, Datasets and Future Research ProspectsIEEE Access10.1109/ACCESS.2023.330642211(88099-88115)Online publication date: 2023
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Tan YLee CNeo MLim KLim J(2023)Enhanced Text-to-Image Synthesis With Self-SupervisionIEEE Access10.1109/ACCESS.2023.326886911(39508-39519)Online publication date: 2023
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Ullah ULee JAn CLee HPark SBaek RChoi H(2022)A Review of Multi-Modal Learning from the Text-Guided Visual Processing ViewpointSensors10.3390/s2218681622:18(6816)Online publication date: 8-Sep-2022
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Alati ECaracciolo CCosta MSanzari MRusso PAmerini I(2022)aRTIC GAN: A Recursive Text-Image-Conditioned GANElectronics10.3390/electronics1111173711:11(1737)Online publication date: 30-May-2022
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