Physically realistic video editing from natural language instructions
Hsu, Hao-Yu
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https://hdl.handle.net/2142/129197
Description
Title
Physically realistic video editing from natural language instructions
Author(s)
Hsu, Hao-Yu
Issue Date
2025-04-15
Director of Research (if dissertation) or Advisor (if thesis)
Wang, Shenlong
Department of Study
Siebel School Comp & Data Sci
Discipline
Computer Science
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Visual effects
text-guided video editing
3D simulation
physical-based editing
Language
eng
Abstract
Modern visual effects (VFX) software has made it possible for skilled artists to create imagery of virtually anything. However, the creation process remains laborious, complex, and largely inaccessible to everyday users. In this work, we present AutoVFX, a framework that automatically creates realistic and dynamic VFX videos from a single video and natural language instructions. By carefully integrating neural scene modeling, LLM-based code generation, and physical simulation, AutoVFX is able to provide physically-grounded, photorealistic editing effects that can be controlled directly using natural language instructions. We conduct extensive experiments to validate AutoVFX’s efficacy across a diverse spectrum of videos and instructions. Quantitative and qualitative results suggest that AutoVFX outperforms all competing methods by a large margin in generative quality, instruction alignment, editing versatility, and physical plausibility.
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