Tuning-free Instruction-based Video Editing Via Structural Noise Initialization and Guidance
A new framework for video editing has been proposed that eliminates the need for extensive tuning. This method utilizes a Structural Noise Initialization Strategy and a Noise Guidance Mechanism to enhance editing quality. Experiments indicate that the approach achieves superior visual quality and performance compared to existing methods.
- ▪The proposed framework is tuning-free and instruction-based.
- ▪It employs a Structural Noise Initialization Strategy to optimize editing regions.
- ▪The Noise Guidance Mechanism integrates rich information from noisy latent to improve visual coherence.
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Computer Science > Computer Vision and Pattern Recognition arXiv:2605.15533 (cs) [Submitted on 15 May 2026] Title:Tuning-free Instruction-based Video Editing Via Structural Noise Initialization and Guidance Authors:Song Wu, Xinyu Chen, Qian Wang, Liang Li, Zili Yi, Junlan Feng View a PDF of the paper titled Tuning-free Instruction-based Video Editing Via Structural Noise Initialization and Guidance, by Song Wu and 5 other authors View PDF HTML (experimental) Abstract:Video editing poses a significant challenge. While a series of tuning-free methods circumvent the need for extensive data collection and model training, they often underutilize the rich information embedded within noisy latent, leading to unsatisfactory results.
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