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Generating images that fit a given text description using machine learning has improved greatly with the release of technologies such as the CLIP image-text encoder model; however, current methods lack artistic control of the style of image to be generated.
The dichotomy of form and content
Duncan Robertson · 1967
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A computer system for the analysis of color-related elements in art therapy assessment: Computer_color-related elements art therapy evaluation system (c_creates)
Seong-in Kim · 2010
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How autonomy impacts performance and satisfaction: Results from a study with spinal cord injured subjects using an assistive robot
Dae-Jin Kim, Rebekah Hazlett-Knudsen, Heather Culver-Godfrey, Greta Rucks, Tara Cunningham, David Portee, John Bricout, Zhao Wang, and Aman Behal · 2011
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New image descriptors based on color, texture, shape, and wavelets for object and scene image classification
Sugata Banerji, Atreyee Sinha, and Chengjun Liu · 2013
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Fourth-Grade Students’ Subjective Interactions with the Seven Elements of Art: An Exploratory Case Study Using Q-methodology
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Image style transfer using convolutional neural networks
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Learning to paint with model-based deep reinforcement learning
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Style transfer by relaxed optimal transport and self-similarity
Nicholas Kolkin, Jason Salavon, and Gregory Shakhnarovich · 2019
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Content-based image retrieval using color, shape and texture descriptors and features
Mutasem K Alsmadi · 2020
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Peter Schaldenbrand and Jean Oh · 2020
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Formal elements of art
Paint transformer: Feed forward neural painting with stroke prediction
Songhua Liu, Tianwei Lin, Dongliang He, Fu Li, Ruifeng Deng, Xin Li, Errui Ding, and Hao Wang · 2021
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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Mark Thorson · 2020
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Creating for creatives: A humanistic approach to designing ai tools targeted at professional animators
Cole Bateman · 2021
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Clipdraw: Exploring text-to-drawing synthesis through language-image encoders
Kevin Frans, LB Soros, and Olaf Witkowski · 2021
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Generating images from caption and vice versa via clip-guided generative latent space search
Federico Galatolo., Mario Cimino., and Gigliola Vaglini · 2021
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Sylvestre-Alvise Rebuffi, Sven Gowal, Dan Andrei Calian, Florian Stimberg, Olivia Wiles, and Timothy A Mann · 2021
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Autonomy in physical human-robot interaction: A brief survey
Mario Selvaggio, Marco Cognetti, Stefanos Nikolaidis, Serena Ivaldi, and Bruno Siciliano · 2021
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Clip-guided gan image generation: An artistic exploration
Amy Smith and Simon Colton · 2021
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Modern evolution strategies for creativity: Fitting concrete images and abstract concepts
Yingtao Tian and David Ha · 2021
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Formal analysis of art: Proxy learning of visual concepts from style through language models
Diana Kim, Ahmed Elgammal, and Marian Mazzone · 2022
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