mlsanityData to 7 Oct 2026

DiffuEraser: A Diffusion Model for Video Inpainting

arXiv 2501.10018 ↗First posted 17 Jan 2025cs.CVcited by 69

On the map: Diffusion models → 3D, point cloud and scene generation

Abstract (arXiv)

Recent video inpainting algorithms integrate flow-based pixel propagation with transformer-based generation to leverage optical flow for restoring textures and objects using information from neighboring frames, while completing masked regions through visual Transformers. However, these approaches often encounter blurring and temporal inconsistencies when dealing with large masks, highlighting the need for models with enhanced generative capabilities. Recently, diffusion models have emerged as a prominent technique in image and video generation due to their impressive performance. In this paper, we introduce DiffuEraser, a video inpainting model based on stable diffusion, designed to fill masked regions with greater details and more coherent structures. We incorporate prior information to provide initialization and weak conditioning,which helps mitigate noisy artifacts and suppress hallucinations. Additionally, to improve temporal consistency during long-sequence inference, we expand the temporal receptive fields of both the prior model and DiffuEraser, and further enhance consistency by leveraging the temporal smoothing property of Video Diffusion Models. Experimental results demonstrate that our proposed method outperforms state-of-the-art techniques in both content completeness and temporal consistency while maintaining acceptable efficiency.

Key facts. Cited by 69 papers in the map (data through 7 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 15 of its 47 references that are in the map. First posted on arXiv 17 Jan 2025.

Builds on

15 of 47 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023AVID: Any-Length Video Inpainting with Diffusion Model6 Dec

Other references · 14

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2020Denoising Diffusion Implicit Modelscited by 9,655
  3. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,286
  4. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
  5. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
  6. 2022Video Diffusion Modelscited by 2,280
  7. 2023T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Modelscited by 1,339
  8. 2022Null-text Inversion for Editing Real Images using Guided Diffusion Modelscited by 1,168
  9. 2023FateZero: Fusing Attentions for Zero-shot Text-based Video Editingcited by 462
  10. 2023ControlVideo: Training-free Controllable Text-to-Video Generationcited by 324
  11. 2023Make-Your-Video: Customized Video Generation Using Textual and Structural Guidancecited by 129
  12. 2024Phased Consistency Modelscited by 83
2 more
  1. 2024Towards Language-Driven Video Inpainting via Multimodal Large Language Modelscited by 33
  2. 2024Coherent Video Inpainting Using Optical Flow-Guided Efficient Diffusioncited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 27; 2026: 42.

69 papers.

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  1. 2025MotionStream: Real-Time Video Generation with Interactive Motion Controlscited by 71
  2. 2025Se~norita-2M: A High-Quality Instruction-based Dataset for General Video Editing by Video Specialistscited by 61
  3. 2026Being-H0.5: Scaling Human-Centric Robot Learning for Cross-Embodiment Generalizationcited by 61
  4. 2025EditVerse: Unifying Image and Video Editing and Generation with In-Context Learningcited by 53
  5. 2025OpenVE-3M: A Large-Scale High-Quality Dataset for Instruction-Guided Video Editingcited by 50
  6. 2025MiniMax-Remover: Taming Bad Noise Helps Video Object Removalcited by 42
  7. 2025ROSE: Remove Objects with Side Effects in Videoscited by 32
  8. 2025InstructX: Towards Unified Visual Editing with MLLM Guidancecited by 31
  9. 2025OmnimatteZero: Fast Training-free Omnimatte with Pre-trained Video Diffusion Modelscited by 15
  10. 2025UniLumos: Fast and Unified Image and Video Relighting with Physics-Plausible Feedbackcited by 12
  11. 2026Robotic Video World Models: A Survey of Applications, Research Challenges, Future Directionscited by 12
  12. 2026EffectErase: Joint Video Object Removal and Insertion for High-Quality Effect Erasingcited by 12
38 more
  1. 2025Vivid4D: Improving 4D Reconstruction from Monocular Video by Video Inpaintingcited by 11
  2. 2025See4D: Pose-Free 4D Generation via Auto-Regressive Video Inpaintingcited by 11
  3. 2026Bernini: Latent Semantic Planning for Video Diffusioncited by 11
  4. 2025O-DisCo-Edit: Object Distortion Control for Unified Realistic Video Editingcited by 10
  5. 2026PISCO: Precise Video Instance Insertion with Sparse Controlcited by 9
  6. 2026VOID: Video Object and Interaction Deletioncited by 9
  7. 2026Tele-Omni: a Unified Multimodal Framework for Video Generation and Editingcited by 8
  8. 2026SAMA: Factorized Semantic Anchoring and Motion Alignment for Instruction-Guided Video Editingcited by 8
  9. 2025IllumiCraft: Unified Geometry and Illumination Diffusion for Controllable Video Generationcited by 6
  10. 2025EraserDiT: Fast Video Inpainting with Diffusion Transformer Modelcited by 5
  11. 2025VideoCoF: Unified Video Editing with Temporal Reasonercited by 5
  12. 2026Object-WIPER : Training-Free Object and Associated Effect Removal in Videoscited by 5
  13. 2025IC-Effect: Precise and Efficient Video Effects Editing via In-Context Learningcited by 4
  14. 2026EditCtrl: Disentangled Local and Global Control for Real-Time Generative Video Editingcited by 4
  15. 2026From Ideal to Real: Stable Video Object Removal under Imperfect Conditionscited by 4
  16. 2025BVINet: Unlocking Blind Video Inpainting with Zero Annotationscited by 3
  17. 2025FakeParts: a New Family of AI-Generated DeepFakescited by 3
  18. 2025RobustSora: De-Watermarked Benchmark for Robust AI-Generated Video Detectioncited by 3
  19. 2025Over++: Generative Video Compositing for Layer Interaction Effectscited by 3
  20. 2026Glove2Hand: Synthesizing Natural Hand-Object Interaction from Multi-Modal Sensing Glovescited by 3
  21. 2026ArtHOI: Taming Foundation Models for Monocular 4D Reconstruction of Hand-Articulated-Object Interactionscited by 3
  22. 2025LoVoRA: Text-guided and Mask-free Video Object Removal and Addition with Learnable Object-aware Localizationcited by 2
  23. 2026Diff2DGS: Reliable Reconstruction of Occluded Surgical Scenes via 2D Gaussian Splattingcited by 2
  24. 2026Physics-Aware Video Instance Removal Benchmarkcited by 2
  25. 2026YOSE: You Only Select Essential Tokens for Efficient DiT-based Video Object Removalcited by 2
  26. 2026WorldAct: Activating Monolithic 3D Worlds into Interactive-Ready Object-Centric Scenescited by 2
  27. 2026SPLIT: Training-Free AI-Generated and Partially Edited Video Detection via Spatial Patch-Level Incoherence and Temporal Roughnesscited by 2
  28. 2025AVFakeBench: A Comprehensive Audio-Video Forgery Detection Benchmark for AV-LMMscited by 1
  29. 2025Refaccade: Editing Object with Given Reference Texturecited by 1
  30. 2025CustomX: Unified Character, Action, and Scene Customization in Video World Modelscited by 1
  31. 2025EasyOmnimatte: Taming Pretrained Inpainting Diffusion Models for End-to-End Video Layered Decompositioncited by 1
  32. 2026Learning Stochastic Bridges for Video Object Removal via Video-to-Video Translationcited by 1
  33. 2026CLEAR: Context-Aware Learning with End-to-End Mask-Free Inference for Adaptive Video Subtitle Removalcited by 1
  34. 2026From Understanding to Erasing: Towards Complete and Stable Video Object Removalcited by 1
  35. 2026Sparkle: Realizing Lively Instruction-Guided Video Background Replacement via Decoupled Guidancecited by 1
  36. 2026DualEraser: Joint Video Object and Effect Removal via Balanced Text-Mask Guidance and Decoupled Locator-Preservercited by 1
  37. 2026From Draft to Draft-Free: One-Step Video Object Removal via Privileged Distillation and Fast Plantingcited by 1
  38. 2026OmniEdit-Bench: A Comprehensive Benchmark for Instruction-based Video Editingcited by 1

50 most cited of 69 All 69 (JSON)

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  1. 2024Semantically Consistent Video Inpainting with Conditional Diffusion Models
  2. 2024Video Diffusion Models are Strong Video Inpainter
  3. 2025VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models
  4. 2025DiTPainter: Efficient Video Inpainting with Diffusion Transformers
  5. 2023Infusion: internal diffusion for inpainting of dynamic textures and complex motion
  6. 2024DiffMVR: Diffusion-based Automated Multi-Guidance Video Restoration
  7. 20243D-Consistent Image Inpainting with Diffusion Models
  8. 2025IS-Diff: Improving Diffusion-Based Inpainting with Better Initial Seed