VideoDiff: Human-AI Video Co-Creation with Alternatives
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Abstract (arXiv)
To make an engaging video, people sequence interesting moments and add visuals such as B-rolls or text. While video editing requires time and effort, AI has recently shown strong potential to make editing easier through suggestions and automation. A key strength of generative models is their ability to quickly generate multiple variations, but when provided with many alternatives, creators struggle to compare them to find the best fit. We propose VideoDiff, an AI video editing tool designed for editing with alternatives. With VideoDiff, creators can generate and review multiple AI recommendations for each editing process: creating a rough cut, inserting B-rolls, and adding text effects. VideoDiff simplifies comparisons by aligning videos and highlighting differences through timelines, transcripts, and video previews. Creators have the flexibility to regenerate and refine AI suggestions as they compare alternatives. Our study participants (N=12) could easily compare and customize alternatives, creating more satisfying results.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Feb 2025.
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Citing papers per year: 2025: 4; 2026: 4.
8 papers.
- 2025Prompt-Driven Agentic Video Editing System: Autonomous Comprehension of Long-Form, Story-Driven Mediacited by 6
- 2025GenTune: Toward Traceable Prompts to Improve Controllability of Image Refinement in Environment Designcited by 5
- 2025Exploration vs. Fixation: Scaffolding Divergent and Convergent Thinking for Human-AI Co-Creation with Generative Modelscited by 2
- 2026Vidmento: Creating Video Stories Through Context-Aware Expansion With Generative Videocited by 2
- 2026EditYourself: Audio-Driven Generation and Manipulation of Talking Head Videos with Diffusion Transformerscited by 2
- 2025Generative Augmented Reality: Paradigms, Technologies, and Future Applicationscited by 1
- 2026Designing Multi-Robot Ground Video Sensemaking with Public Safety Professionalscited by 1
- 2026Unified Agentic Video Editing Across Levels of Complexity and Creativitycited by 0
- 2026Unified Agentic Video Editing Across Levels of Complexity and Creativity11 Sep 2026
- 2026Designing Multi-Robot Ground Video Sensemaking with Public Safety Professionals9 Feb 2026
- 2026EditYourself: Audio-Driven Generation and Manipulation of Talking Head Videos with Diffusion Transformers29 Jan 2026
- 2026Vidmento: Creating Video Stories Through Context-Aware Expansion With Generative Video29 Jan 2026
- 2025Exploration vs. Fixation: Scaffolding Divergent and Convergent Thinking for Human-AI Co-Creation with Generative Models20 Dec 2025
- 2025Generative Augmented Reality: Paradigms, Technologies, and Future Applications20 Nov 2025
- 2025Prompt-Driven Agentic Video Editing System: Autonomous Comprehension of Long-Form, Story-Driven Media20 Sep 2025
- 2025GenTune: Toward Traceable Prompts to Improve Controllability of Image Refinement in Environment Design21 Aug 2025