mlsanityData to 7 Oct 2026

CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoders

arXiv 2106.14843 ↗First posted 28 Jun 2021cs.CVcited by 186

Not on the map. Why?

Cited by 31 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

This work presents CLIPDraw, an algorithm that synthesizes novel drawings based on natural language input. CLIPDraw does not require any training; rather a pre-trained CLIP language-image encoder is used as a metric for maximizing similarity between the given description and a generated drawing. Crucially, CLIPDraw operates over vector strokes rather than pixel images, a constraint that biases drawings towards simpler human-recognizable shapes. Results compare between CLIPDraw and other synthesis-through-optimization methods, as well as highlight various interesting behaviors of CLIPDraw, such as satisfying ambiguous text in multiple ways, reliably producing drawings in diverse artistic styles, and scaling from simple to complex visual representations as stroke count is increased. Code for experimenting with the method is available at: https://colab.research.google.com/github/kvfrans/clipdraw/blob/main/clipdraw.ipynb

Key facts. Cited by 186 papers in the map (data through 7 Oct 2026). Builds on 17 of its 44 references that are in the map. First posted on arXiv 28 Jun 2021.

Builds on

17 of 44 references.

References · 17

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  3. 2014Explaining and Harnessing Adversarial Examplescited by 7,287
  4. 2017Neural Discrete Representation Learningcited by 4,650
  5. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  6. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,229
  7. 2014Conditional Generative Adversarial Netscited by 2,152
  8. 2014Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Imagescited by 774
  9. 2016Generative Adversarial Text to Image Synthesiscited by 735
  10. 2015A Neural Algorithm of Artistic Stylecited by 480
  11. 2016Synthesizing the preferred inputs for neurons in neural networks via deep generator networkscited by 181
  12. 2021Im2Vec: Synthesizing Vector Graphics without Vector Supervisioncited by 114
5 more
  1. 2021Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Searchcited by 57
  2. 2021Adversarial Text-to-Image Synthesis: A Reviewcited by 52
  3. 2021Rethinking Style Transfer: From Pixels to Parameterized Brushstrokescited by 42
  4. 2021ClipGen: A Deep Generative Model for Clipart Vectorization and Synthesiscited by 23
  5. 2021Generative Art Using Neural Visual Grammars and Dual Encoderscited by 6

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 13; 2022: 31; 2023: 49; 2024: 31; 2025: 36; 2026: 26.

186 papers.

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  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2021Zero-Shot Text-Guided Object Generation with Dream Fieldscited by 513
  3. 2022MotionCLIP: Exposing Human Motion Generation to CLIP Spacecited by 406
  4. 2021Text2Mesh: Text-Driven Neural Stylization for Meshescited by 332
  5. 2022Text2LIVE: Text-Driven Layered Image and Video Editingcited by 312
  6. 2024Long-CLIP: Unlocking the Long-Text Capability of CLIPcited by 298
  7. 2022Inversion-Based Style Transfer with Diffusion Modelscited by 290
  8. 2022VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidancecited by 285
  9. 2021CLIP-Forge: Towards Zero-Shot Text-to-Shape Generationcited by 254
  10. 2021CLIPstyler: Image Style Transfer with a Single Text Conditioncited by 203
  11. 2021Simple but Effective: CLIP Embeddings for Embodied AIcited by 191
  12. 2022VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Modelscited by 112
38 more
  1. 2023Iterative Prompt Learning for Unsupervised Backlit Image Enhancementcited by 107
  2. 2021CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIPcited by 88
  3. 2022Learning to generate line drawings that convey geometry and semanticscited by 82
  4. 2023SVGDreamer: Text Guided SVG Generation with Diffusion Modelcited by 75
  5. 2022StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuationcited by 74
  6. 2023AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZcited by 74
  7. 2023IconShop: Text-Guided Vector Icon Synthesis with Autoregressive Transformerscited by 73
  8. 2022Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation?cited by 70
  9. 2022CLIPascene: Scene Sketching with Different Types and Levels of Abstractioncited by 63
  10. 2024Empowering LLMs to Understand and Generate Complex Vector Graphicscited by 63
  11. 2023Word-As-Image for Semantic Typographycited by 62
  12. 2022CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIPcited by 60
  13. 2023Diffusion Handles: Enabling 3D Edits for Diffusion Models by Lifting Activations to 3Dcited by 59
  14. 2022CLIPasso: Semantically-Aware Object Sketchingcited by 57
  15. 2022AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatarscited by 55
  16. 2023Shape-aware Text-driven Layered Video Editingcited by 54
  17. 2023DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Modelscited by 54
  18. 2023Renderable Neural Radiance Map for Visual Navigationcited by 51
  19. 2023Breathing Life Into Sketches Using Text-to-Video Priorscited by 47
  20. 2023OMG: Towards Open-vocabulary Motion Generation via Mixture of Controllerscited by 47
  21. 2022Being Comes from Not-being: Open-vocabulary Text-to-Motion Generation with Wordless Trainingcited by 45
  22. 2025LayerTracer: Cognitive-Aligned Layered SVG Synthesis via Diffusion Transformercited by 43
  23. 2023CLIP2Protect: Protecting Facial Privacy using Text-Guided Makeup via Adversarial Latent Searchcited by 42
  24. 2022CLIP-Actor: Text-Driven Recommendation and Stylization for Animating Human Meshescited by 41
  25. 2021Modern Evolution Strategies for Creativity: Fitting Concrete Images and Abstract Conceptscited by 40
  26. 2024VideoCLIP-XL: Advancing Long Description Understanding for Video CLIP Modelscited by 40
  27. 2022One-shot Implicit Animatable Avatars with Model-based Priorscited by 38
  28. 2023High-fidelity Generalized Emotional Talking Face Generation with Multi-modal Emotion Space Learningcited by 37
  29. 2024ProcessPainter: Learn Painting Process from Sequence Datacited by 37
  30. 2024Diffusion Feedback Helps CLIP See Bettercited by 37
  31. 2024Rethinking Score Distillation as a Bridge Between Image Distributionscited by 36
  32. 2024Chat2SVG: Vector Graphics Generation with Large Language Models and Image Diffusion Modelscited by 36
  33. 2023Text2Layer: Layered Image Generation using Latent Diffusion Modelcited by 35
  34. 2024LLMs Meet Multimodal Generation and Editing: A Surveycited by 35
  35. 2021Predict, Prevent, and Evaluate: Disentangled Text-Driven Image Manipulation Empowered by Pre-Trained Vision-Language Modelcited by 34
  36. 2022CLIPVG: Text-Guided Image Manipulation Using Differentiable Vector Graphicscited by 34
  37. 20223D Highlighter: Localizing Regions on 3D Shapes via Text Descriptionscited by 32
  38. 2024Text-to-Vector Generation with Neural Path Representationcited by 32

50 most cited of 186 All 186 (JSON)