mlsanityData to 7 Oct 2026

GANravel: User-Driven Direction Disentanglement in Generative Adversarial Networks

arXiv 2302.00079 ↗First posted 31 Jan 2023cs.HC cs.LGcited by 5

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Abstract (arXiv)

Generative adversarial networks (GANs) have many application areas including image editing, domain translation, missing data imputation, and support for creative work. However, GANs are considered 'black boxes'. Specifically, the end-users have little control over how to improve editing directions through disentanglement. Prior work focused on new GAN architectures to disentangle editing directions. Alternatively, we propose GANravel a user-driven direction disentanglement tool that complements the existing GAN architectures and allows users to improve editing directions iteratively. In two user studies with 16 participants each, GANravel users were able to disentangle directions and outperformed the state-of-the-art direction discovery baselines in disentanglement performance. In the second user study, GANravel was used in a creative task of creating dog memes and was able to create high-quality edited images and GIFs.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 36 of its 50 references that are in the map. First posted on arXiv 31 Jan 2023.

Builds on

36 of 50 references.

References · 36

  1. 2017Attention Is All You Needcited by 59,932
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  3. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  4. 2022Generative Adversarial Networkscited by 5,603
  5. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
  6. 2015FaceNet: A Unified Embedding for Face Recognition and Clusteringcited by 2,833
  7. 2015Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networkscited by 2,048
  8. 2018ESRGAN: Enhanced Super-Resolution Generative Adversarial Networkscited by 1,250
  9. 2019StarGAN v2: Diverse Image Synthesis for Multiple Domainscited by 1,095
  10. 2021StyleCLIP: Text-Driven Manipulation of StyleGAN Imagerycited by 990
  11. 2019Interpreting the Latent Space of GANs for Semantic Face Editingcited by 691
  12. 2020GANSpace: Discovering Interpretable GAN Controlscited by 612
24 more
  1. 2020Closed-Form Factorization of Latent Semantics in GANscited by 407
  2. 2020InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANscited by 393
  3. 2016Generative Visual Manipulation on the Natural Image Manifoldcited by 348
  4. 2020StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flowscited by 348
  5. 2020StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generationcited by 331
  6. 2020Unsupervised Discovery of Interpretable Directions in the GAN Latent Spacecited by 288
  7. 2018Generative Adversarial Network in Medical Imaging: A Reviewcited by 257
  8. 2019On the "steerability" of generative adversarial networkscited by 247
  9. 2019GANalyze: Toward Visual Definitions of Cognitive Image Propertiescited by 193
  10. 2020Editing in Style: Uncovering the Local Semantics of GANscited by 183
  11. 2017SEGAN: Speech Enhancement Generative Adversarial Networkcited by 165
  12. 2021EditGAN: High-Precision Semantic Image Editingcited by 156
  13. 2021Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesiscited by 140
  14. 2021Generative Adversarial Transformerscited by 120
  15. 2019Semantic Hierarchy Emerges in Deep Generative Representations for Scene Synthesiscited by 106
  16. 2020Controlling generative models with continuous factors of variationscited by 93
  17. 2021WarpedGANSpace: Finding non-linear RBF paths in GAN latent spacecited by 48
  18. 2018Sequential Attention GAN for Interactive Image Editingcited by 33
  19. 2020Deep Generation of Face Images from Sketchescited by 32
  20. 2022GANSlider: How Users Control Generative Models for Images using Multiple Sliders with and without Feedforward Informationcited by 13
  21. 2019Constrained Generative Adversarial Networks for Interactive Image Generationcited by 10
  22. 2020Improving Workflow Integration with xPath: Design and Evaluation of a Human-AI Diagnosis System in Pathologycited by 9
  23. 2020Lessons Learned from Designing an AI-Enabled Diagnosis Tool for Pathologistscited by 9
  24. 2022GANzilla: User-Driven Direction Discovery in Generative Adversarial Networkscited by 7

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Cited by year

Citing papers per year: 2023: 2; 2024: 2; 2025: 1.

5 papers.

  1. 2023Promptify: Text-to-Image Generation through Interactive Prompt Exploration with Large Language Modelscited by 67
  2. 2024PromptCharm: Text-to-Image Generation through Multi-modal Prompting and Refinementcited by 61
  3. 2024Generative AI for Visualization: State of the Art and Future Directionscited by 23
  4. 2023Next Steps for Human-Centered Generative AI: A Technical Perspectivecited by 13
  5. 2025GenTune: Toward Traceable Prompts to Improve Controllability of Image Refinement in Environment Designcited by 5