Geometry Aligned Variational Transformer for Image-conditioned Layout Generation

Author:

Cao Yunning1,Ma Ye2,Zhou Min2,Liu Chuanbin1,Xie Hongtao1,Ge Tiezheng2,Jiang Yuning2

Affiliation:

1. University of Science and Technology of China, Hefei, China

2. Alibaba Group, Beijing, China

Funder

the National Nature Science Foundation of China

the Youth Innovation Promotion Association Chinese Academy of Sciences

the Fundamental Research Funds for the Central Universities

Publisher

ACM

Reference28 articles.

1. Variational Transformer Networks for Layout Generation

2. Generating Sentences from a Continuous Space

3. End-to-End Object Detection with Transformers

4. Alexey Dosovitskiy , Lucas Beyer , Alexander Kolesnikov , Dirk Weissenborn , Xiaohua Zhai , Thomas Unterthiner , Mostafa Dehghani , Matthias Minderer , Georg Heigold , Sylvain Gelly , 2020 . An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale . In International Conference on Learning Representations. Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al. 2020. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. In International Conference on Learning Representations.

5. Hao Fu , Chunyuan Li , Xiaodong Liu , Jianfeng Gao , Asli Celikyilmaz , and Lawrence Carin . 2019 . Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing . In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , Volume 1 (Long and Short Papers). Association for Computational Linguistics, Minneapolis, Minnesota, 240--250. https://doi.org/10. 18653/v1/N19--1021 Hao Fu, Chunyuan Li, Xiaodong Liu, Jianfeng Gao, Asli Celikyilmaz, and Lawrence Carin. 2019. Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, Minneapolis, Minnesota, 240--250. https://doi.org/10.18653/v1/N19--1021

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