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Diffusion-based generative models have significantly advanced text-to-image generation but encounter challenges when processing lengthy and intricate text prompts describing complex scenes with multiple objects.
Stackgan++: Realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris N Metaxas · 1962
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The pascal visual object classes (voc) challenge
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Denoising diffusion implicit models
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Score-based generative modeling through stochastic differential equations
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Generative adversarial nets
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Microsoft coco: Common objects in context
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Generative adversarial text to image synthesis
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Wasserstein generative adversarial networks
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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 N Metaxas · 2017
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Large scale gan training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 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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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Semantic image synthesis with spatially-adaptive normalization
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Generative modeling by estimating gradients of the data distribution
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Image synthesis from reconfigurable layout and style
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Image generation from layout
Bo Zhao, Lili Meng, Weidong Yin, and Leonid Sigal · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Blended diffusion for text-driven editing of natural images
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Clipscore: A reference-free evaluation metric for image captioning
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Universal guidance for diffusion models
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