mlsanityData to 7 Oct 2026

Deep Video Inpainting

arXiv 1905.01639 ↗First posted 5 May 2019cs.CVcited by 107

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Abstract (arXiv)

Video inpainting aims to fill spatio-temporal holes with plausible content in a video. Despite tremendous progress of deep neural networks for image inpainting, it is challenging to extend these methods to the video domain due to the additional time dimension. In this work, we propose a novel deep network architecture for fast video inpainting. Built upon an image-based encoder-decoder model, our framework is designed to collect and refine information from neighbor frames and synthesize still-unknown regions. At the same time, the output is enforced to be temporally consistent by a recurrent feedback and a temporal memory module. Compared with the state-of-the-art image inpainting algorithm, our method produces videos that are much more semantically correct and temporally smooth. In contrast to the prior video completion method which relies on time-consuming optimization, our method runs in near real-time while generating competitive video results. Finally, we applied our framework to video retargeting task, and obtain visually pleasing results.

Key facts. Cited by 107 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 May 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 23; 2022: 22; 2023: 18; 2024: 20; 2025: 11; 2026: 13.

107 papers.

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  1. 2022FlowFormer: A Transformer Architecture for Optical Flowcited by 273
  2. 2023ProPainter: Improving Propagation and Transformer for Video Inpaintingcited by 193
  3. 2024SEA-RAFT: Simple, Efficient, Accurate RAFT for Optical Flowcited by 169
  4. 2023FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimationcited by 114
  5. 2022Towards An End-to-End Framework for Flow-Guided Video Inpaintingcited by 111
  6. 2021FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpaintingcited by 94
  7. 2025VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Controlcited by 83
  8. 2023VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimationcited by 82
  9. 2023AVID: Any-Length Video Inpainting with Diffusion Modelcited by 81
  10. 2022Flow-Guided Transformer for Video Inpaintingcited by 59
  11. 2021VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learningcited by 56
  12. 2022RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-Resolutioncited by 44
38 more
  1. 2024Deep Learning-based Image and Video Inpainting: A Surveycited by 44
  2. 2024Generative Video Propagationcited by 36
  3. 2022Disentangling Architecture and Training for Optical Flowcited by 32
  4. 2022PS-NeRV: Patch-wise Stylized Neural Representations for Videoscited by 32
  5. 2022Tell Me What Happened: Unifying Text-guided Video Completion via Multimodal Masked Video Generationcited by 32
  6. 2025ROSE: Remove Objects with Side Effects in Videoscited by 32
  7. 2022Bringing Old Films Back to Lifecited by 31
  8. 2021Occlusion-Aware Video Object Inpaintingcited by 30
  9. 2021Decoupled Spatial-Temporal Transformer for Video Inpaintingcited by 28
  10. 2022ClothFormer:Taming Video Virtual Try-on in All Modulecited by 26
  11. 2021Learning to Associate Every Segment for Video Panoptic Segmentationcited by 25
  12. 2022Unidirectional Video Denoising by Mimicking Backward Recurrent Modules with Look-ahead Forward Onescited by 24
  13. 2021Learning Semantic-Aware Dynamics for Video Predictioncited by 21
  14. 2023Look Ma, No Hands! Agent-Environment Factorization of Egocentric Videoscited by 21
  15. 2022Error Compensation Framework for Flow-Guided Video Inpaintingcited by 20
  16. 2021Internal Video Inpainting by Implicit Long-range Propagationcited by 19
  17. 2022Deep Video Prior for Video Consistency and Propagationcited by 18
  18. 2023Bitstream-Corrupted Video Recovery: A Novel Benchmark Dataset and Methodcited by 14
  19. 2021Seeing Through Clouds in Satellite Imagescited by 13
  20. 2024UniPaint: Unified Space-time Video Inpainting via Mixture-of-Expertscited by 13
  21. 2021VCGAN: Video Colorization with Hybrid Generative Adversarial Networkcited by 12
  22. 2021Flow-Guided Video Inpainting with Scene Templatescited by 12
  23. 2022DeViT: Deformed Vision Transformers in Video Inpaintingcited by 12
  24. 2021Deep Video Inpainting Detectioncited by 11
  25. 2021The DEVIL is in the Details: A Diagnostic Evaluation Benchmark for Video Inpaintingcited by 11
  26. 2025TACO: Taming Diffusion for in-the-wild Video Amodal Completioncited by 10
  27. 2021Unsupervised Domain Adaptation for Video Semantic Segmentationcited by 9
  28. 2023Context-PIPs: Persistent Independent Particles Demands Spatial Context Featurescited by 9
  29. 2026PISCO: Precise Video Instance Insertion with Sparse Controlcited by 9
  30. 2021M3L: Language-based Video Editing via Multi-Modal Multi-Level Transformerscited by 8
  31. 2024Semantically Consistent Video Inpainting with Conditional Diffusion Modelscited by 8
  32. 2021Deep Face Video Inpainting via UV Mappingcited by 7
  33. 2021A Review on Visual Privacy Preservation Techniques for Active and Assisted Livingcited by 6
  34. 2022Video Manipulations Beyond Faces: A Dataset with Human-Machine Analysiscited by 6
  35. 2022Bridging Images and Videos: A Simple Learning Framework for Large Vocabulary Video Object Detectioncited by 6
  36. 2023Exploiting Optical Flow Guidance for Transformer-Based Video Inpaintingcited by 6
  37. 2024Repositioning the Subject within Imagecited by 6
  38. 2021Out-of-boundary View Synthesis Towards Full-Frame Video Stabilizationcited by 5

50 most cited of 107 All 107 (JSON)