Summary of Dreammotion: Space-time Self-similar Score Distillation For Zero-shot Video Editing, by Hyeonho Jeong et al.
DreamMotion: Space-Time Self-Similar Score Distillation for Zero-Shot Video Editing
by Hyeonho Jeong, Jinho Chang, Geon Yeong Park, Jong Chul Ye
First submitted to arxiv on: 18 Mar 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a novel approach to text-driven video editing, focusing on establishing real-world motion. Unlike existing methods, it employs score distillation sampling to initiate optimization from videos with natural motion. The analysis reveals that video score distillation can introduce new content but also cause structure and motion deviation. To address this, the authors propose matching space-time self-similarities between the original and edited videos during score distillation. This model-agnostic approach is applicable to both cascaded and non-cascaded video diffusion frameworks. The paper demonstrates its superiority in altering appearances while preserving original structure and motion through extensive comparisons with leading methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research is about making video editing more like real life. Normally, when you edit a video, it looks fake because the movement isn’t natural. This paper finds a way to make videos look more realistic by using a special technique called score distillation sampling. It takes a video and makes changes based on what someone wants, but also keeps the original motion intact. The results show that this approach is better than others at changing how things look while keeping the movement natural. |
Keywords
» Artificial intelligence » Diffusion » Distillation » Optimization
