AutoVFX: Physically Realistic Video Editing from Natural Language
  Instructions
Authors: name: Hao-Yu Hsu, name: Zhi-Hao Lin, name: Albert Zhai, name: Hongchi Xia, name: Shenlong Wang

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.