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We introduce LeX-Art, a comprehensive suite for high-quality text-image synthesis that systematically bridges the gap between prompt expressiveness and text rendering fidelity.
The hungarian method for the assignment problem
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Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras, and Yejin Choi · 2021
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Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, and Aran Komatsuzaki · 2021
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Pp-ocrv3: More attempts for the improvement of ultra lightweight ocr system
Adding conditional control to text-to-image diffusion models
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Claude 3.5 haiku
Anthropic · 2024
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Textdiffuser-2: Unleashing the power of language models for text rendering
Jingye Chen, Yupan Huang, Tengchao Lv, Lei Cui, Qifeng Chen, and Furu Wei · 2024
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Scaling rectified flow transformers for high-resolution image synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, et al · 2024
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High-resolution image synthesis with latent diffusion models
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Self-consistency improves chain of thought reasoning in language models
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Textdiffuser: Diffusion models as text painters
Jingye Chen, Yupan Huang, Tengchao Lv, Lei Cui, Qifeng Chen, and Furu Wei · 2023
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Glyphdraw: Seamlessly rendering text with intricate spatial structures in text-to-image generation
Jian Ma, Mingjun Zhao, Chen Chen, Ruichen Wang, Di Niu, Haonan Lu, and Xiaodong Lin · 2023
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Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach · 2023
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Gen3-alpha prompt guide
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Anytext2: Visual text generation and editing with customizable attributes
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Diffusion model alignment using direct preference optimization
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