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Human evaluation is critical for validating the performance of text-to-image generative models, as this highly cognitive process requires deep comprehension of text and images.
Content analysis: An introduction to its methodology, 1980
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Distribution theory for glass’s estimator of effect size and related estimators
Larry V Hedges · 1981
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Recommendation ITU-T P.800, 1996
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Microsoft COCO: Common objects in context
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Improved techniques for training GANs
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Rethinking the inception architecture for computer vision
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GANs trained by a two time-scale update rule converge to a local nash equilibrium
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StackGAN: Text to photo-realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris Metaxas · 2017
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StackGAN: Text to photo-realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris Metaxas · 2017
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Bottom-up and top-down attention for image captioning and visual question answering
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Demystifying MMD GANs
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Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis
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Striving to earn more: A survey of work strategies and tool use among crowd workers
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An improved evaluation framework for generative adversarial networks
Shaohui Liu, Yi Wei, Jiwen Lu, and Jie Zhou · 2018
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Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
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Responsible research with crowds: Pay crowdworkers at least minimum wage
M. S. Silberman, B. Tomlinson, R. LaPlante, J. Ross, L. Irani, and A. Zaldivar · 2018
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AttnGAN: Fine-grained text to image generation with attentional generative adversarial networks
Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, and Xiaodong He · 2018
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Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis
Seunghoon Hong, Dingdong Yang, Jongwook Choi, and Honglak Lee · 2018
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AttnGAN: Fine-Grained Text to Image Generation With Attentional Generative Adversarial Networks
Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, and Xiaodong He · 2018
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StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks, 2018
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris Metaxas · 2018
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Photographic Text-to-Image Synthesis With a Hierarchically-Nested Adversarial Network
Zizhao Zhang, Yuanpu Xie, and Lin Yang · 2018
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Improved precision and recall metric for assessing generative models
Tuomas Kynkäänniemi, Tero Karras, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2019
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HYPE: A benchmark for human eye perceptual evaluation of generative models
Sharon Zhou, Mitchell L. Gordon, Ranjay Krishna, Austin Narcomey, Li Fei-Fei, and Michael S. Bernstein · 2019
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Dual Adversarial Inference for Text-to-Image Synthesis
Qicheng Lao, Mohammad Havaei, Ahmad Pesaranghader, Francis Dutil, Lisa Di Jorio, and Thomas Fevens · 2019
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Controllable Text-to-Image Generation
Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, and Philip Torr · 2019
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Object-Driven Text-To-Image Synthesis via Adversarial Training
Wenbo Li, Pengchuan Zhang, Lei Zhang, Qiuyuan Huang, Xiaodong He, Siwei Lyu, and Jianfeng Gao · 2019
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MirrorGAN: Learning Text-To-Image Generation by Redescription
Tingting Qiao, Jing Zhang, Duanqing Xu, and Dacheng Tao · 2019
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Semantics-Enhanced Adversarial Nets for Text-to-Image Synthesis
Hongchen Tan, Xiuping Liu, Xin Li, Yi Zhang, and Baocai Yin · 2019
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Semantics Disentangling for Text-To-Image Generation
Guojun Yin, Bin Liu, Lu Sheng, Nenghai Yu, Xiaogang Wang, and Jing Shao · 2019
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DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-To-Image Synthesis
Minfeng Zhu, Pingbo Pan, Wei Chen, and Yi Yang · 2019
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Findings of the 2020 conference on machine translation (WMT20)
Loïc Barrault, Magdalena Biesialska, Ondřej Bojar, Marta R. Costa-jussà, Christian Federmann, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Matthias Huck, Eric Joanis, Tom Kocmi, Philipp Koehn, Chi-kiu Lo, Nikola Ljubešić, Christof Monz, Makoto Morishita, Masaaki Nagata, Toshiaki Nakazawa, Santanu Pal, Matt Post, and Marcos Zampieri · 2020
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GLIDE: towards photorealistic image generation and editing with text-guided diffusion models
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On aliased resizing and surprising subtleties in GAN evaluation
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High-resolution image synthesis with latent diffusion models
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Photorealistic text-to-image diffusion models with deep language understanding
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Trace controlled text to image generation
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The shape of and solutions to the mturk quality crisis
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CPGAN: Content-parsing generative adversarial networks for text-to-image synthesis
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RiFeGAN: Rich Feature Generation for Text-to-Image Synthesis From Prior Knowledge
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CPGAN: Content-parsing generative adversarial networks for text-to-image synthesis
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CookGAN: Causality Based Text-to-Image Synthesis
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Mturk research: Review and recommendations
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On training sample memorization: Lessons from benchmarking generative modeling with a large-scale competition
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Scaling Autoregressive Models for Content-Rich Text-to-Image Generation, 2022
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, Ben Hutchinson, Wei Han, Zarana Parekh, Xin Li, Han Zhang, Jason Baldridge, and Yonghui Wu · 2022
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LAFITE: Towards language-free training for text-to-image generation
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CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers, 2022
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TISE: Bag of metrics for text-to-image synthesis evaluation
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Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priors
Oran Gafni, Adam Polyak, Oron Ashual, Shelly Sheynin, Devi Parikh, and Yaniv Taigman · 2022
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An image is worth one word: Personalizing text-to-image generation using textual inversion, 2022
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H. Bermano, Gal Chechik, and Daniel Cohen-Or · 2022
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Vector Quantized Diffusion Model for Text-to-Image Synthesis
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Imagic: Text-Based Real Image Editing with Diffusion Models, 2022
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StyleT2I: Toward compositional and high-fidelity text-to-image synthesis
Zhiheng Li, Martin Renqiang Min, Kai Li, and Chenliang Xu · 2022
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Text to Image Generation With Semantic-Spatial Aware GAN
Wentong Liao, Kai Hu, Michael Ying Yang, and Bodo Rosenhahn · 2022
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StoryDALL-E: Adapting pretrained text-to-image transformers for story continuation
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GLIDE: towards photorealistic image generation and editing with text-guided diffusion models
Alexander Quinn Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2022
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High-Resolution Image Synthesis With Latent Diffusion Models
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DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation, 2022
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 2022
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Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding, 2022
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, and Mohammad Norouzi · 2022
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DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis
Ming Tao, Hao Tang, Fei Wu, Xiao-Yuan Jing, Bing-Kun Bao, and Changsheng Xu · 2022
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Text-to-Image Synthesis Based on Object-Guided Joint-Decoding Transformer
Fuxiang Wu, Liu Liu, Fusheng Hao, Fengxiang He, and Jun Cheng · 2022
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Trace controlled text to image generation
Kun Yan, Lei Ji, Chenfei Wu, Ming Zhou, Nan Duan, and Shuai Ma · 2022
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Scaling autoregressive models for content-rich text-to-image generation, 2022
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Towards Language-Free Training for Text-to-Image Generation
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