mlsanityData to 7 Oct 2026

Large Scale Image Completion via Co-Modulated Generative Adversarial Networks

arXiv 2103.10428 ↗First posted 18 Mar 2021cs.CV cs.GR cs.LGcited by 219

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Cited by 58 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Numerous task-specific variants of conditional generative adversarial networks have been developed for image completion. Yet, a serious limitation remains that all existing algorithms tend to fail when handling large-scale missing regions. To overcome this challenge, we propose a generic new approach that bridges the gap between image-conditional and recent modulated unconditional generative architectures via co-modulation of both conditional and stochastic style representations. Also, due to the lack of good quantitative metrics for image completion, we propose the new Paired/Unpaired Inception Discriminative Score (P-IDS/U-IDS), which robustly measures the perceptual fidelity of inpainted images compared to real images via linear separability in a feature space. Experiments demonstrate superior performance in terms of both quality and diversity over state-of-the-art methods in free-form image completion and easy generalization to image-to-image translation. Code is available at https://github.com/zsyzzsoft/co-mod-gan.

Key facts. Cited by 219 papers in the map (data through 7 Oct 2026). Builds on 58 of its 80 references that are in the map. First posted on arXiv 18 Mar 2021.

Builds on

58 of 80 references.

References · 58

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  3. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
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  12. 2016COCO-Stuff: Thing and Stuff Classes in Contextcited by 858
38 more
  1. 2018Multimodal Unsupervised Image-to-Image Translationcited by 795
  2. 2018Which Training Methods for GANs do actually Converge?cited by 672
  3. 2017Unsupervised Image-to-Image Translation Networkscited by 602
  4. 2018Free-Form Image Inpainting with Gated Convolutioncited by 594
  5. 2017The Perception-Distortion Tradeoffcited by 582
  6. 2018Generative Image Inpainting with Contextual Attentioncited by 578
  7. 2016Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networkscited by 541
  8. 2018Image Inpainting for Irregular Holes Using Partial Convolutionscited by 505
  9. 2018Assessing Generative Models via Precision and Recallcited by 401
  10. 2020Differentiable Augmentation for Data-Efficient GAN Trainingcited by 361
  11. 2016A Learned Representation For Artistic Stylecited by 340
  12. 2017DualGAN: Unsupervised Dual Learning for Image-to-Image Translationcited by 310
  13. 2017Toward Multimodal Image-to-Image Translationcited by 295
  14. 2016Revisiting Classifier Two-Sample Testscited by 258
  15. 2019Few-Shot Unsupervised Image-to-Image Translationcited by 222
  16. 2019U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translationcited by 186
  17. 2019Pluralistic Image Completioncited by 162
  18. 2019EdgeConnect: Generative Image Inpainting with Adversarial Edge Learningcited by 161
  19. 2019Mode Seeking Generative Adversarial Networks for Diverse Image Synthesiscited by 138
  20. 2019StructureFlow: Image Inpainting via Structure-aware Appearance Flowcited by 118
  21. 2020Recurrent Feature Reasoning for Image Inpaintingcited by 107
  22. 2019SC-FEGAN: Face Editing Generative Adversarial Network with User's Sketch and Colorcited by 105
  23. 2020Rethinking Image Inpainting via a Mutual Encoder-Decoder with Feature Equalizationscited by 102
  24. 2019Coherent Semantic Attention for Image Inpaintingcited by 97
  25. 2019Learning Pyramid-Context Encoder Network for High-Quality Image Inpaintingcited by 94
  26. 2019Foreground-aware Image Inpaintingcited by 90
  27. 2016High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesiscited by 89
  28. 2018Shift-Net: Image Inpainting via Deep Feature Rearrangementcited by 87
  29. 2018Image Inpainting via Generative Multi-column Convolutional Neural Networkscited by 81
  30. 2017DeLiGAN : Generative Adversarial Networks for Diverse and Limited Datacited by 77
  31. 2019Image Inpainting with Learnable Bidirectional Attention Mapscited by 64
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  38. 2020Learning Oracle Attention for High-fidelity Face Completioncited by 21

50 most cited of 58 All 58 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 17; 2022: 52; 2023: 59; 2024: 47; 2025: 33; 2026: 11.

219 papers.

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  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,419
  3. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  4. 2022MaskGIT: Masked Generative Image Transformercited by 1,082
  5. 2023One-step Diffusion with Distribution Matching Distillationcited by 978
  6. 2021Resolution-robust Large Mask Inpainting with Fourier Convolutionscited by 730
  7. 2023Zero-shot Image-to-Image Translationcited by 503
  8. 2023Scaling up GANs for Text-to-Image Synthesiscited by 492
  9. 2022MAT: Mask-Aware Transformer for Large Hole Image Inpaintingcited by 216
  10. 2024BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusioncited by 200
  11. 2022Versatile Diffusion: Text, Images and Variations All in One Diffusion Modelcited by 199
  12. 2023Flow Matching in Latent Spacecited by 155
38 more
  1. 2022SPIn-NeRF: Multiview Segmentation and Perceptual Inpainting with Neural Radiance Fieldscited by 144
  2. 2023Scaling Data Generation in Vision-and-Language Navigationcited by 115
  3. 2024One-Step Image Translation with Text-to-Image Modelscited by 111
  4. 2023Generative Image Dynamicscited by 93
  5. 2021Aggregated Contextual Transformations for High-Resolution Image Inpaintingcited by 89
  6. 2021Ensembling Off-the-shelf Models for GAN Trainingcited by 84
  7. 2022Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encodingcited by 83
  8. 2022InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Imagescited by 82
  9. 2021Diverse Image Inpainting with Bidirectional and Autoregressive Transformerscited by 80
  10. 2024Distilling Diffusion Models into Conditional GANscited by 78
  11. 2022Any-resolution Training for High-resolution Image Synthesiscited by 72
  12. 2023HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Modelscited by 67
  13. 2023Inst-Inpaint: Instructing to Remove Objects with Diffusion Modelscited by 66
  14. 2022High-fidelity 3D GAN Inversion by Pseudo-multi-view Optimizationcited by 65
  15. 2025LEGION: Learning to Ground and Explain for Synthetic Image Detectioncited by 65
  16. 2023Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Modelscited by 61
  17. 2024DiffMOT: A Real-time Diffusion-based Multiple Object Tracker with Non-linear Predictioncited by 59
  18. 2023Putting People in Their Place: Affordance-Aware Human Insertion into Scenescited by 53
  19. 2023PanoDiffusion: 360-degree Panorama Outpainting via Diffusioncited by 50
  20. 2022CM-GAN: Image Inpainting with Cascaded Modulation GAN and Object-Aware Trainingcited by 49
  21. 2023Smooth Diffusion: Crafting Smooth Latent Spaces in Diffusion Modelscited by 48
  22. 2022InsetGAN for Full-Body Image Generationcited by 45
  23. 2022Shape-Guided Diffusion with Inside-Outside Attentioncited by 45
  24. 2023Designing a Better Asymmetric VQGAN for StableDiffusioncited by 45
  25. 2022Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Modelscited by 44
  26. 2023Persistent Nature: A Generative Model of Unbounded 3D Worldscited by 44
  27. 2024Deep Learning-based Image and Video Inpainting: A Surveycited by 44
  28. 2023Perceptual Artifacts Localization for Image Synthesis Taskscited by 43
  29. 2023360-Degree Panorama Generation from Few Unregistered NFoV Imagescited by 42
  30. 2021Bridging Global Context Interactions for High-Fidelity Image Completioncited by 40
  31. 2023Reference-guided Controllable Inpainting of Neural Radiance Fieldscited by 40
  32. 2022Reduce Information Loss in Transformers for Pluralistic Image Inpaintingcited by 36
  33. 2022Do better ImageNet classifiers assess perceptual similarity better?cited by 34
  34. 2024Generative Image Layer Decomposition with Visual Effectscited by 33
  35. 2022Guided Co-Modulated GAN for 360deg Field of View Extrapolationcited by 32
  36. 2023EverLight: Indoor-Outdoor Editable HDR Lighting Estimationcited by 32
  37. 2024BrushEdit: All-In-One Image Inpainting and Editingcited by 31
  38. 2024MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editingcited by 30

50 most cited of 219 All 219 (JSON)