[41] Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever. Zero-shot text-to-image generation. In Proceedings of the ICML, pages 8821-8831, 2021.
[42] Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. High-resolution image synthesis with latent diffusion models. In Proceedings of the CVPR, pages 10674-10685, 2022.
[43] Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In Proceedings of the MICCAI, pages 234-241, 2015.
[44] Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen. Improved techniques for training gans. In Proceedings of the NeurIPS, pages 2226-2234, 2016.
[45] Brigit Schroeder and Subarna Tripathi. Structured query-based image retrieval using scene graphs. In Proceedings of the CVPR, pages 680-684, 2020.
[46] Sebastian Schuster, Ranjay Krishna, Angel X. Chang, Li Fei-Fei, and Christopher D. Manning. Generating semantically precise scene graphs from textual descriptions for improved image retrieval. In Proceedings of the EMNLP, pages 70–80, 2015.
[47] Jiaming Song, Chenlin Meng, and Stefano Ermon. Denoising diffusion implicit models. In Proceedings of the ICLR, 2021.
[48] Ming Tao, Hao Tang, Songsong Wu, Nicu Sebe, Fei Wu, and Xiao-Yuan Jing. DF-GAN: deep fusion generative adversarial networks for text-to-image synthesis. CoRR, abs/2008.05865, 2020.
[49] Aäron van den Oord, Nal Kalchbrenner, Lasse Espeholt, Koray Kavukcuoglu, Oriol Vinyals, and Alex Graves. Conditional image generation with pixelCNN decoders. In Proceedings of the NeurIPS, pages 4790-4798, 2016.
[50] Aäron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu. Neural discrete representation learning. In Proceedings of the NeurIPS, pages 6306-6315, 2017.
[51] Andrey Voynov, Qinghao Chu, Daniel Cohen-Or, and Kfir Aberman. P+: extended textual conditioning in text-to-image generation. CoRR, abs/2303.09522, 2023.
[52] Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, and Xiaodong He. Attngan: Fine-grained text to image generation with attentional generative adversarial networks. In Proceedings of the CVPR, pages 1316-1324, 2018.
[53] Ling Yang, Zhilin Huang, Yang Song, Shenda Hong, Guohao Li, Wentao Zhang, Bin Cui, Bernard Ghanem, and Ming-Hsuan Yang. Diffusion-based scene graph to image generation with masked contrastive pre-training. CoRR, abs/2211.11138, 2022.
[54] Xu Yang, Kaihua Tang, Hanwang Zhang, and Jianfei Cai. Auto-encoding scene graphs for image captioning. In Proceedings of the CVPR, pages 10685–10694, 2019.
[55] Xu Yang, Chongyang Gao, Hanwang Zhang, and Jianfei Cai. Hierarchical scene graph encoder-decoder for image paragraph captioning. In Proceedings of the ACM MM, pages 4181-4189, 2020.
[56] Sangwoong Yoon, Woo-Young Kang, Sungwook Jeon, SeongEun Lee, Changjin Han, Jonghun Park, and Eun-Sol Kim. Image-to-image retrieval by learning similarity between scene graphs. In Proceedings of the AAAI, pages 10718-10726, 2021.
[57] Jiaxuan You, Rex Ying, Xiang Ren, William L. Hamilton, and Jure Leskovec. Graphnn: Generating realistic graphs with deep auto-regressive models. In Proceedings of the ICML, pages 5694-5703, 2018.
[58] Xiang Yu, Ruoxin Chen, Jie Li, Jiawei Sun, Shijing Yuan, Huxiao Ji, Xinyu Lu, and Chentao Wu. Zero-shot scene graph generation with knowledge graph completion. In Proceedings of the ICME, pages 1-6, 2022.
[59] Rowan Zellers, Mark Yatskar, Sam Thomson, and Yejin Choi. Neural motifs: Scene graph parsing with global context. In Proceedings of the CVPR, pages 5831-5840, 2018.
[60] Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, and Oliver Wang. The unreasonable effectiveness of deep features as a perceptual metric. In Proceedings of the CVPR, pages 586-595, 2018.
[61] Minfeng Zhu, Pingbo Pan, Wei Chen, and Yi Yang. DM-GAN: dynamic memory generative adversarial networks for text-to-image synthesis. In Proceedings of the CVPR, pages 5802-5810, 2019.