(ෆ`꒳´ෆ) A Survey on Text-to-Image Generation/Synthesis.
𝓐𝔀𝓮𝓼𝓸𝓶𝓮 𝓣𝓮𝔁𝓽📝-𝓽𝓸-𝓘𝓶𝓪𝓰𝓮🌇
If you find this paper and repo helpful for your research, please cite it below:
@inproceedings{zhou2023vision+,
title={Vision+ Language Applications: A Survey},
author={Zhou, Yutong and Shimada, Nobutaka},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={826--842},
year={2023}
}
[!TIP] Version 1.0 (All-in-one version) can be found here and will be stop updating from 24/02/29.
In the last few decades, the fields of Computer Vision (CV) and Natural Language Processing (NLP) have been made several major technological breakthroughs in deep learning research. Recently, researchers interested in combining semantic information and visual information in these traditionally independent fields. A number of studies have been conducted on text-to-image synthesis techniques that transfer input textual descriptions (keywords or sentences) into realistic images.
Papers, codes, and datasets for the text-to-image task are available here.
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