mlsanityData to 7 Oct 2026

Neutral Editing Framework for Diffusion-based Video Editing

arXiv 2312.06708 ↗First posted 10 Dec 2023cs.CVcited by 2

On the map: Diffusion models → Video generation

Abstract (arXiv)

Text-conditioned image editing has succeeded in various types of editing based on a diffusion framework. Unfortunately, this success did not carry over to a video, which continues to be challenging. Existing video editing systems are still limited to rigid-type editing such as style transfer and object overlay. To this end, this paper proposes Neutral Editing (NeuEdit) framework to enable complex non-rigid editing by changing the motion of a person/object in a video, which has never been attempted before. NeuEdit introduces a concept of `neutralization' that enhances a tuning-editing process of diffusion-based editing systems in a model-agnostic manner by leveraging input video and text without any other auxiliary aids (e.g., visual masks, video captions). Extensive experiments on numerous videos demonstrate adaptability and effectiveness of the NeuEdit framework. The website of our work is available here: https://neuedit.github.io

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Video generation, one of 14 directions in Diffusion models. Builds on 36 of its 39 references that are in the map. First posted on arXiv 10 Dec 2023.

Builds on

36 of 39 references.

Closest ancestors · 6

Same direction, newest first

  1. 2023StableVideo: Text-driven Consistency-aware Diffusion Video Editing18 Aug
  2. 2023FateZero: Fusing Attentions for Zero-shot Text-based Video Editing16 Mar
  3. 2023Structure and Content-Guided Video Synthesis with Diffusion Models6 Feb
  4. 2022Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation22 Dec
  5. 2022Imagen Video: High Definition Video Generation with Diffusion Models5 Oct
  6. 2022Video Diffusion Models7 Apr

Other references · 30

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  3. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2020Denoising Diffusion Implicit Modelscited by 9,655
  6. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  7. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  8. 2023Segment Anythingcited by 8,158
  9. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  10. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  11. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  12. 2022Generative Adversarial Networkscited by 5,603
18 more
  1. 2017Neural Discrete Representation Learningcited by 4,650
  2. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  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. 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,725
  7. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  8. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,419
  9. 2022Imagic: Text-Based Real Image Editing with Diffusion Modelscited by 1,172
  10. 2022CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformerscited by 973
  11. 2023Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generationcited by 950
  12. 2017The 2017 DAVIS Challenge on Video Object Segmentationcited by 942
  13. 2021DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulationcited by 640
  14. 2017Generative Adversarial Networks: An Overviewcited by 588
  15. 2022Text2LIVE: Text-Driven Layered Image and Video Editingcited by 312
  16. 2023Video-P2P: Video Editing with Cross-attention Controlcited by 312
  17. 2021N"UWA: Visual Synthesis Pre-training for Neural visUal World creAtioncited by 253
  18. 2023CVPR 2023 Text Guided Video Editing Competitioncited by 54

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Cited by year

Citing papers per year: 2024: 1; 2025: 1.

2 papers.

  1. 2024C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersioncited by 82
  2. 2025Prompting without Panic: Attribute-aware, Zero-shot, Test-Time Calibrationcited by 2

Similar, not cited

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  1. 2024Diffusion Model-Based Video Editing: A Survey
  2. 2023Zero-Shot Video Editing Using Off-The-Shelf Image Diffusion Models
  3. 2024EVA: Zero-shot Accurate Attributes and Multi-Object Video Editing
  4. 2025FADE: Frequency-Aware Diffusion Model Factorization for Video Editing
  5. 2024Temporally Consistent Object Editing in Videos using Extended Attention
  6. 2024I2VEdit: First-Frame-Guided Video Editing via Image-to-Video Diffusion Models
  7. 2024Object-Centric Diffusion for Efficient Video Editing
  8. 2023Pix2Video: Video Editing using Image Diffusion