Constrained Graphic Layout Generation via Latent Optimization-Reference-Cited by-同舟云学术

Constrained Graphic Layout Generation via Latent Optimization

Published:2021-10-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM International Conference on Multimedia
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Author:

Kikuchi Kotaro¹,Simo-Serra Edgar¹,Otani Mayu²,Yamaguchi Kota²

Affiliation:

1. Waseda University, Shinjuku-ku, Japan

2. CyberAgent, Shibuya-ku, Japan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3474085.3475497

Reference40 articles.

1. Diego Martin Arroyo Janis Postels and Federico Tombari. 2021. Variational Transformer Networks for Layout Generation. arXiv:arXiv:2104.02416 Diego Martin Arroyo Janis Postels and Federico Tombari. 2021. Variational Transformer Networks for Layout Generation. arXiv:arXiv:2104.02416

2. Semantic Photo Manipulation with a Generative Image Prior;Bau David;ACM Trans. Graph.,2019

3. Alexandre Carlier Martin Danelljan Alexandre Alahi and Radu Timofte. 2020. DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation. In Adv. Neural Inform. Process. Syst. Alexandre Carlier Martin Danelljan Alexandre Alahi and Radu Timofte. 2020. DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation. In Adv. Neural Inform. Process. Syst.

4. Chia-Hsing Chiu Yuki Koyama Yu-Chi Lai Takeo Igarashi and Yonghao Yue. 2020. Human-in-the-Loop Differential Subspace Search in High-Dimensional Latent Space. ACM Trans. Graph. (2020). Chia-Hsing Chiu Yuki Koyama Yu-Chi Lai Takeo Igarashi and Yonghao Yue. 2020. Human-in-the-Loop Differential Subspace Search in High-Dimensional Latent Space. ACM Trans. Graph. (2020).

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