mlsanityData to 7 Oct 2026

StyleCLIPDraw: Coupling Content and Style in Text-to-Drawing Synthesis

arXiv 2111.03133 ↗First posted 4 Nov 2021cs.CV cs.CLcited by 15

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Abstract (arXiv)

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. We introduce StyleCLIPDraw which adds a style loss to the CLIPDraw text-to-drawing synthesis model to allow artistic control of the synthesized drawings in addition to control of the content via text. Whereas performing decoupled style transfer on a generated image only affects the texture, our proposed coupled approach is able to capture a style in both texture and shape, suggesting that the style of the drawing is coupled with the drawing process itself. More results and our code are available at https://github.com/pschaldenbrand/StyleCLIPDraw

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 5 of its 6 references that are in the map. First posted on arXiv 4 Nov 2021.

Builds on

5 of 6 references.

References · 5

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  3. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  4. 2021CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoderscited by 186
  5. 2019Style Transfer by Relaxed Optimal Transport and Self-Similaritycited by 167

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Citing papers per year: 2021: 1; 2022: 4; 2023: 7; 2024: 2; 2025: 1.

15 papers.

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  1. 2021Zero-Shot Text-Guided Object Generation with Dream Fieldscited by 513
  2. 2023SVGDreamer: Text Guided SVG Generation with Diffusion Modelcited by 75
  3. 2023DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Modelscited by 54
  4. 2023High-fidelity Generalized Emotional Talking Face Generation with Multi-modal Emotion Space Learningcited by 37
  5. 2022Text2Light: Zero-Shot Text-Driven HDR Panorama Generationcited by 24
  6. 2022Name Your Style: An Arbitrary Artist-aware Image Style Transfercited by 14
  7. 2023ExpCLIP: Bridging Text and Facial Expressions via Semantic Alignmentcited by 13
  8. 2022End-to-End Visual Editing with a Generatively Pre-Trained Artistcited by 7
  9. 2023Open Vocabulary Semantic Scene Sketch Understandingcited by 4
  10. 2023Fine-Tuned but Zero-Shot 3D Shape Sketch View Similarity and Retrievalcited by 3
  11. 2022Bridging the prosody GAP: Genetic Algorithm with People to efficiently sample emotional prosodycited by 2
  12. 2025Birth of a Painting: Differentiable Brushstroke Reconstructioncited by 1
3 more
  1. 2023TextCLIP: Text-Guided Face Image Generation And Manipulation Without Adversarial Trainingcited by 0
  2. 2024Bridging Text and Image for Artist Style Transfer via Contrastive Learningcited by 0
  3. 2024SVGDreamer++: Advancing Editability and Diversity in Text-Guided SVG Generationcited by 0