mlsanityData to 7 Oct 2026

Resolution-robust Large Mask Inpainting with Fourier Convolutions

arXiv 2109.07161 ↗First posted 15 Sep 2021cs.CV eess.IVcited by 730

Not on the map. Why?

Cited by 143 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Modern image inpainting systems, despite the significant progress, often struggle with large missing areas, complex geometric structures, and high-resolution images. We find that one of the main reasons for that is the lack of an effective receptive field in both the inpainting network and the loss function. To alleviate this issue, we propose a new method called large mask inpainting (LaMa). LaMa is based on i) a new inpainting network architecture that uses fast Fourier convolutions (FFCs), which have the image-wide receptive field; ii) a high receptive field perceptual loss; iii) large training masks, which unlocks the potential of the first two components. Our inpainting network improves the state-of-the-art across a range of datasets and achieves excellent performance even in challenging scenarios, e.g. completion of periodic structures. Our model generalizes surprisingly well to resolutions that are higher than those seen at train time, and achieves this at lower parameter&time costs than the competitive baselines. The code is available at urlhttps://github.com/saic-mdal/lama.

Key facts. Cited by 730 papers in the map (data through 7 Oct 2026). Builds on 53 of its 69 references that are in the map. First posted on arXiv 15 Sep 2021.

Builds on

53 of 69 references.

References · 53

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  4. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  5. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  6. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  7. 2014ImageNet Large Scale Visual Recognition Challengecited by 8,441
  8. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  9. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  10. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,229
  11. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
  12. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,678
38 more
  1. 2018ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustnesscited by 1,430
  2. 2016Context Encoders: Feature Learning by Inpaintingcited by 1,424
  3. 2017High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANscited by 1,176
  4. 2015Multi-Scale Context Aggregation by Dilated Convolutionscited by 1,128
  5. 2018Which Training Methods for GANs do actually Converge?cited by 672
  6. 2018Free-Form Image Inpainting with Gated Convolutioncited by 594
  7. 2018Generative Image Inpainting with Contextual Attentioncited by 578
  8. 2014Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFscited by 552
  9. 2017Understanding the Effective Receptive Field in Deep Convolutional Neural Networkscited by 549
  10. 2018Image Inpainting for Irregular Holes Using Partial Convolutionscited by 505
  11. 2021FNet: Mixing Tokens with Fourier Transformscited by 343
  12. 2021Global Filter Networks for Image Classificationcited by 257
  13. 2017Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradientscited by 236
  14. 2021Large Scale Image Completion via Co-Modulated Generative Adversarial Networkscited by 219
  15. 2019Pluralistic Image Completioncited by 162
  16. 2019EdgeConnect: Generative Image Inpainting with Adversarial Edge Learningcited by 161
  17. 2016Semantic Image Inpainting with Deep Generative Modelscited by 156
  18. 2020Contextual Residual Aggregation for Ultra High-Resolution Image Inpaintingcited by 124
  19. 2019StructureFlow: Image Inpainting via Structure-aware Appearance Flowcited by 118
  20. 2020Recurrent Feature Reasoning for Image Inpaintingcited by 107
  21. 2020Rethinking Image Inpainting via a Mutual Encoder-Decoder with Feature Equalizationscited by 102
  22. 2019Coherent Semantic Attention for Image Inpaintingcited by 97
  23. 2019Learning Pyramid-Context Encoder Network for High-Quality Image Inpaintingcited by 94
  24. 2019Foreground-aware Image Inpaintingcited by 90
  25. 2016High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesiscited by 89
  26. 2021Aggregated Contextual Transformations for High-Resolution Image Inpaintingcited by 89
  27. 2018Shift-Net: Image Inpainting via Deep Feature Rearrangementcited by 87
  28. 2018Image Inpainting via Generative Multi-column Convolutional Neural Networkscited by 81
  29. 2020High-Resolution Image Inpainting with Iterative Confidence Feedback and Guided Upsamplingcited by 79
  30. 2019Image Inpainting with Learnable Bidirectional Attention Mapscited by 64
  31. 2018SPG-Net: Segmentation Prediction and Guidance Network for Image Inpaintingcited by 58
  32. 2019Region Normalization for Image Inpaintingcited by 54
  33. 2017Contextual-based Image Inpainting: Infer, Match, and Translatecited by 50
  34. 2020Learning to Incorporate Structure Knowledge for Image Inpaintingcited by 37
  35. 2021Image Inpainting by End-to-End Cascaded Refinement with Mask Awarenesscited by 35
  36. 2019PEPSI++: Fast and Lightweight Network for Image Inpaintingcited by 24
  37. 2019Progressive Image Inpainting with Full-Resolution Residual Networkcited by 19
  38. 2019Region-wise Generative Adversarial ImageInpainting for Large Missing Areascited by 18

50 most cited of 53 All 53 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 79; 2023: 145; 2024: 190; 2025: 195; 2026: 115.

730 papers.

Sort:

By area:

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,419
  3. 2025FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Spacecited by 960
  4. 2024Grounded SAM: Assembling Open-World Models for Diverse Visual Taskscited by 914
  5. 2022On Distillation of Guided Diffusion Modelscited by 721
  6. 2022Improving Diffusion Models for Inverse Problems using Manifold Constraintscited by 501
  7. 2022Paint by Example: Exemplar-based Image Editing with Diffusion Modelscited by 489
  8. 2025VACE: All-in-One Video Creation and Editingcited by 467
  9. 2023V*: Guided Visual Search as a Core Mechanism in Multimodal LLMscited by 459
  10. 2023Gaussian Grouping: Segment and Edit Anything in 3D Scenescited by 387
  11. 2022Decomposing NeRF for Editing via Feature Field Distillationcited by 370
  12. 2023Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Modelscited by 323
38 more
  1. 2023The Stable Signature: Rooting Watermarks in Latent Diffusion Modelscited by 289
  2. 2023SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Modelscited by 283
  3. 2024Fast High-Resolution Image Synthesis with Latent Adversarial Diffusion Distillationcited by 276
  4. 2023DiffIR: Efficient Diffusion Model for Image Restorationcited by 253
  5. 2023Inpaint Anything: Segment Anything Meets Image Inpaintingcited by 233
  6. 2022Imagen Editor and EditBench: Advancing and Evaluating Text-Guided Image Inpaintingcited by 229
  7. 2022MAT: Mask-Aware Transformer for Large Hole Image Inpaintingcited by 216
  8. 2024Diffusion Model-Based Image Editing: A Surveycited by 212
  9. 2022DiffRF: Rendering-Guided 3D Radiance Field Diffusioncited by 204
  10. 2022Versatile Diffusion: Text, Images and Variations All in One Diffusion Modelcited by 199
  11. 2023Scaling Robot Learning with Semantically Imagined Experiencecited by 175
  12. 2024VR-GS: A Physical Dynamics-Aware Interactive Gaussian Splatting System in Virtual Realitycited by 175
  13. 2023A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpaintingcited by 168
  14. 2023InstructDiffusion: A Generalist Modeling Interface for Vision Taskscited by 162
  15. 2023Flow Matching in Latent Spacecited by 155
  16. 2024AnyV2V: A Tuning-Free Framework For Any Video-to-Video Editing Taskscited by 151
  17. 2022SPIn-NeRF: Multiview Segmentation and Perceptual Inpainting with Neural Radiance Fieldscited by 144
  18. 2023SelfOcc: Self-Supervised Vision-Based 3D Occupancy Predictioncited by 133
  19. 2024GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editingcited by 132
  20. 2022MegaPortraits: One-shot Megapixel Neural Head Avatarscited by 131
  21. 2024FakeShield: Explainable Image Forgery Detection and Localization via Multi-modal Large Language Modelscited by 111
  22. 2024MV-Adapter: Multi-view Consistent Image Generation Made Easycited by 111
  23. 2023EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protectioncited by 109
  24. 2022VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wildcited by 106
  25. 2024Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesiscited by 97
  26. 2024SEED-Data-Edit Technical Report: A Hybrid Dataset for Instructional Image Editingcited by 97
  27. 2022DifFace: Blind Face Restoration with Diffused Error Contractioncited by 96
  28. 2024VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasterscited by 87
  29. 2024TACO: Benchmarking Generalizable Bimanual Tool-ACtion-Object Understandingcited by 85
  30. 2022Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encodingcited by 83
  31. 2021Intriguing Findings of Frequency Selection for Image Deblurringcited by 80
  32. 2022Fine-Grained Egocentric Hand-Object Segmentation: Dataset, Model, and Applicationscited by 78
  33. 2024ObjectDrop: Bootstrapping Counterfactuals for Photorealistic Object Removal and Insertioncited by 71
  34. 2022SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolutioncited by 67
  35. 2022Removing Objects From Neural Radiance Fieldscited by 66
  36. 2025LEGION: Learning to Ground and Explain for Synthetic Image Detectioncited by 65
  37. 2025PhysGen3D: Crafting a Miniature Interactive World from a Single Imagecited by 65
  38. 2023A Comprehensive Survey on Segment Anything Model for Vision and Beyondcited by 64

50 most cited of 730 All 730 (JSON)