mlsanityData to 7 Oct 2026

Generative Image Inpainting with Contextual Attention

arXiv 1801.07892 ↗First posted 24 Jan 2018cs.CV cs.GRcited by 578

Not on the map. Why?

Cited by 72 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Recent deep learning based approaches have shown promising results for the challenging task of inpainting large missing regions in an image. These methods can generate visually plausible image structures and textures, but often create distorted structures or blurry textures inconsistent with surrounding areas. This is mainly due to ineffectiveness of convolutional neural networks in explicitly borrowing or copying information from distant spatial locations. On the other hand, traditional texture and patch synthesis approaches are particularly suitable when it needs to borrow textures from the surrounding regions. Motivated by these observations, we propose a new deep generative model-based approach which can not only synthesize novel image structures but also explicitly utilize surrounding image features as references during network training to make better predictions. The model is a feed-forward, fully convolutional neural network which can process images with multiple holes at arbitrary locations and with variable sizes during the test time. Experiments on multiple datasets including faces (CelebA, CelebA-HQ), textures (DTD) and natural images (ImageNet, Places2) demonstrate that our proposed approach generates higher-quality inpainting results than existing ones. Code, demo and models are available at: https://github.com/JiahuiYu/generative_inpainting.

Key facts. Cited by 578 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Jan 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 159; 2022: 140; 2023: 113; 2024: 79; 2025: 60; 2026: 27.

578 papers.

Sort:

By area:

  1. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,419
  2. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  3. 2021Resolution-robust Large Mask Inpainting with Fourier Convolutionscited by 730
  4. 2022DiffEdit: Diffusion-based semantic image editing with mask guidancecited by 643
  5. 2022Paint by Example: Exemplar-based Image Editing with Diffusion Modelscited by 489
  6. 2021Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contractioncited by 306
  7. 2023DiffIR: Efficient Diffusion Model for Image Restorationcited by 253
  8. 2023Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylizationcited by 251
  9. 2022Imagen Editor and EditBench: Advancing and Evaluating Text-Guided Image Inpaintingcited by 229
  10. 2021Large Scale Image Completion via Co-Modulated Generative Adversarial Networkscited by 219
  11. 2022MAT: Mask-Aware Transformer for Large Hole Image Inpaintingcited by 216
  12. 2022DiffRF: Rendering-Guided 3D Radiance Field Diffusioncited by 204
38 more
  1. 2021GAN Prior Embedded Network for Blind Face Restoration in the Wildcited by 197
  2. 2023Scaling Robot Learning with Semantically Imagined Experiencecited by 175
  3. 2021ARCH++: Animation-Ready Clothed Human Reconstruction Revisitedcited by 174
  4. 2023A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpaintingcited by 168
  5. 2021TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Upcited by 162
  6. 2022SPIn-NeRF: Multiview Segmentation and Perceptual Inpainting with Neural Radiance Fieldscited by 144
  7. 2021High-Fidelity Pluralistic Image Completion with Transformerscited by 134
  8. 2022Towards An End-to-End Framework for Flow-Guided Video Inpaintingcited by 111
  9. 2023Diffusion Models for Image Restoration and Enhancement: A Comprehensive Surveycited by 108
  10. 2021Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAEcited by 106
  11. 2021FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpaintingcited by 94
  12. 2024EscherNet: A Generative Model for Scalable View Synthesiscited by 94
  13. 2021Inpainting Transformer for Anomaly Detectioncited by 91
  14. 2021Aggregated Contextual Transformations for High-Resolution Image Inpaintingcited by 89
  15. 2021Equivariant Imaging: Learning Beyond the Range Spacecited by 83
  16. 2022Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encodingcited by 83
  17. 2021PixelSynth: Generating a 3D-Consistent Experience from a Single Imagecited by 82
  18. 2022InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Imagescited by 82
  19. 2023AVID: Any-Length Video Inpainting with Diffusion Modelcited by 81
  20. 2021Diverse Image Inpainting with Bidirectional and Autoregressive Transformerscited by 80
  21. 2021PD-GAN: Probabilistic Diverse GAN for Image Inpaintingcited by 80
  22. 2021Defect-GAN: High-Fidelity Defect Synthesis for Automated Defect Inspectioncited by 77
  23. 2021Open-World Entity Segmentationcited by 74
  24. 2022StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuationcited by 74
  25. 2021Intermediate Layer Optimization for Inverse Problems using Deep Generative Modelscited by 70
  26. 2023HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Modelscited by 67
  27. 2021Image Inpainting via Conditional Texture and Structure Dual Generationcited by 66
  28. 2022Removing Objects From Neural Radiance Fieldscited by 66
  29. 2023Monte Carlo guided Diffusion for Bayesian linear inverse problemscited by 65
  30. 2024Zero-shot Image Editing with Reference Imitationcited by 64
  31. 2024Attentive Eraser: Unleashing Diffusion Model's Object Removal Potential via Self-Attention Redirection Guidancecited by 63
  32. 2021PISE: Person Image Synthesis and Editing with Decoupled GANcited by 62
  33. 2023Uni-paint: A Unified Framework for Multimodal Image Inpainting with Pretrained Diffusion Modelcited by 60
  34. 2022Flow-Guided Transformer for Video Inpaintingcited by 59
  35. 2023RealFill: Reference-Driven Generation for Authentic Image Completioncited by 58
  36. 2022PMP-Net++: Point Cloud Completion by Transformer-Enhanced Multi-step Point Moving Pathscited by 57
  37. 2021Countering Malicious DeepFakes: Survey, Battleground, and Horizoncited by 56
  38. 2021VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learningcited by 56

50 most cited of 578 All 578 (JSON)