mlsanityData to 14 Oct 2026

Perspective (In)consistency of Paint by Text

arXiv 2206.14617 ↗First posted 27 Jun 2022cs.GR cs.AI cs.CVcited by 34

Not on the map. Why?

Abstract (arXiv)

Type "a sea otter with a pearl earring by Johannes Vermeer" or "a photo of a teddy bear on a skateboard in Times Square" into OpenAI's DALL-E-2 paint-by-text synthesis engine and you will not be disappointed by the delightful and eerily pertinent results. The ability to synthesize highly realistic images -- with seemingly no limitation other than our imagination -- is sure to yield many exciting and creative applications. These images are also likely to pose new challenges to the photo-forensic community. Motivated by the fact that paint by text is not based on explicit geometric modeling, and the human visual system's often obliviousness to even glaring geometric inconsistencies, we provide an initial exploration of the perspective consistency of DALL-E-2 synthesized images to determine if geometric-based forensic analyses will prove fruitful in detecting this new breed of synthetic media.

Key facts. Cited by 34 papers in the map (data through 14 Oct 2026). Builds on 9 of its 22 references that are in the map. First posted on arXiv 27 Jun 2022.

Builds on

9 of 22 references.

References · 9

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  3. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 6,013
  4. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,588
  5. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,988
  6. 2019Generating Diverse High-Fidelity Images with VQ-VAE-2cited by 1,387
  7. 2022Scaling Autoregressive Models for Content-Rich Text-to-Image Generationcited by 1,295
  8. 2021Alias-Free Generative Adversarial Networkscited by 1,184
  9. 2021Paint by Wordcited by 107

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 5; 2023: 10; 2024: 9; 2025: 7; 2026: 3.

34 papers.

Sort:

By area:

  1. 2023The Stable Signature: Rooting Watermarks in Latent Diffusion Modelscited by 304
  2. 2022On the detection of synthetic images generated by diffusion modelscited by 283
  3. 2023Raising the Bar of AI-generated Image Detection with CLIPcited by 164
  4. 2023Intriguing properties of synthetic images: from generative adversarial networks to diffusion modelscited by 123
  5. 2022Towards the Detection of Diffusion Model Deepfakescited by 111
  6. 2024Detecting Multimedia Generated by Large AI Models: A Surveycited by 76
  7. 2022Testing Relational Understanding in Text-Guided Image Generationcited by 59
  8. 2024Any-Resolution AI-Generated Image Detection by Spectral Learningcited by 57
  9. 2024Zero-Shot Detection of AI-Generated Imagescited by 50
  10. 2024FakeBench: Probing Explainable Fake Image Detection via Large Multimodal Modelscited by 36
  11. 2022Lighting (In)consistency of Paint by Textcited by 35
  12. 2023Qualitative Failures of Image Generation Models and Their Application in Detecting Deepfakescited by 31
22 more
  1. 2023Deep Image Fingerprint: Towards Low Budget Synthetic Image Detection and Model Lineage Analysiscited by 30
  2. 2023Weakly-supervised deepfake localization in diffusion-generated imagescited by 24
  3. 2024Robust CLIP-Based Detector for Exposing Diffusion Model-Generated Imagescited by 20
  4. 2023Enhancing Diffusion Models with 3D Perspective Geometry Constraintscited by 16
  5. 2023The Age of Synthetic Realities: Challenges and Opportunitiescited by 15
  6. 2025Characterizing Photorealism and Artifacts in Diffusion Model-Generated Imagescited by 14
  7. 2024Synthetic Image Verification in the Era of Generative AI: What Works and What Isn't There Yetcited by 13
  8. 2022DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic Modelscited by 12
  9. 2025Survey on AI-Generated Media Detection: From Non-MLLM to MLLMcited by 12
  10. 2024Relations, Negations, and Numbers: Looking for Logic in Generative Text-to-Image Modelscited by 9
  11. 2024A Survey on Responsible Generative AI: What to Generate and What Notcited by 8
  12. 2023Local Statistics for Generative Image Detectioncited by 5
  13. 2023Synthetic images aid the recognition of human-made art forgeriescited by 4
  14. 2024Synthetic Photography Detection: A Visual Guidance for Identifying Synthetic Images Created by AIcited by 3
  15. 2026A Difference-in-Difference Approach to Detecting AI-Generated Imagescited by 2
  16. 2025Where's the liability in the Generative Era? Recovery-based Black-Box Detection of AI-Generated Contentcited by 1
  17. 2025PRADA: Probability-Ratio-Based Attribution and Detection of Autoregressive-Generated Imagescited by 1
  18. 2025A parameter-efficient three-branch architecture for multimodal misinformation detection with limited annotationscited by 1
  19. 2026Fake3DGS: A Benchmark for 3D Manipulation Detection in Neural Renderingcited by 1
  20. 2025Robustness in AI-Generated Detection: Enhancing Resistance to Adversarial Attackscited by 0
  21. 2025AdaptPrompt: Parameter-Efficient Adaptation of VLMs for Generalizable Deepfake Detectioncited by 0
  22. 2026Unknown Aware AI-Generated Content Attributioncited by 0