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It's a Feature, Not a Bug: Measuring Creative Fluidity in Image Generators

arXiv 2406.18570 ↗First posted 3 Jun 2024cs.HC cs.AI cs.CVcited by 0

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Abstract (arXiv)

With the rise of freely available image generators, AI-generated art has become the centre of a series of heated debates, one of which concerns the concept of human creativity. Can an image generation AI exhibit ``creativity'' of the same type that artists do, and if so, how does that manifest? Our paper attempts to define and empirically measure one facet of creative behavior in AI, by conducting an experiment to quantify the "fluidity of prompt interpretation", or just "fluidity", in a series of selected popular image generators. To study fluidity, we (1) introduce a clear definition for it, (2) create chains of auto-generated prompts and images seeded with an initial "ground-truth: image, (3) measure these chains' breakage points using preexisting visual and semantic metrics, and (4) use both statistical tests and visual explanations to study these chains and determine whether the image generators used to produce them exhibit significant fluidity.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 16 of its 30 references that are in the map. First posted on arXiv 3 Jun 2024.

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References · 16

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  5. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  6. 2023Visual Instruction Tuningcited by 7,792
  7. 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generationcited by 4,310
  8. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,772
  9. 2023Adversarial Diffusion Distillationcited by 741
  10. 2023Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Modelscited by 696
  11. 2022GIT: A Generative Image-to-text Transformer for Vision and Languagecited by 536
  12. 2024YOLO-World: Real-Time Open-Vocabulary Object Detectioncited by 498
4 more
  1. 2023Kandinsky: an Improved Text-to-Image Synthesis with Image Prior and Latent Diffusioncited by 114
  2. 2022The Creativity of Text-to-Image Generationcited by 73
  3. 2023Artificial muses: Generative Artificial Intelligence Chatbots Have Risen to Human-Level Creativitycited by 24
  4. 2021Explanations for Occluded Imagescited by 14

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