专业编辑如何评估AI生成的影视视频广告的剪辑质量？
How Do Professional Editors Evaluate the Editing Quality of AI-Generated Cinematic Video Ads?
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中文总结 AI 辅助
该研究针对AI生成影视广告缺乏细粒度评估框架的问题，构建两阶段生成流程，通过专业编辑评价得出六个剪辑质量维度，为相关评估与生成提供指导。
中文摘要 AI 辅助
在社交媒体上，我们经常看到采用影视剪辑技巧来唤起情感反应的短视频广告。虽然AI工具开始自动生成这类影视广告，但我们缺乏用于评估这些广告的细粒度框架。本文首先描述社交媒体视频广告格式，并在语料库中将影视广告识别为一种常见格式。随后分析影视广告的时长、镜头结构、音频与文本元素以及剪辑技巧，以此构建两阶段生成流程：其中大型语言模型（LLM）先生成镜头计划，视频生成模型再渲染视频。利用该流程，我们为35个真实品牌生成了70条影视广告，并招募专业视频编辑对其剪辑选择进行评价。从他们的评价中，我们得出六个剪辑质量维度：叙事进展、视听协调与声音设计、视觉构图与图形、镜头间连贯性、信息与品牌一致性，以及时间节奏与速率。我们讨论这些维度如何指导AI生成影视广告的感知剪辑生成、人工评估及自动评估。
英文摘要
On social media, we often encounter short-form video ads that employ cinematic editing techniques to evoke an emotional response. While AI tools are beginning to generate such cinematic ads automatically, we lack a fine-grained framework for evaluating these ads. In this paper, we first characterize social media video ad formats and identify cinematic ads as a recurring format in our corpus. We then analyze the duration, shot structure, audio and text elements, and editing techniques of cinematic ads to inform a two-stage generation pipeline in which an LLM first generates a shot plan and a video generation model renders the video. Using this pipeline, we generated 70 cinematic ads for 35 real brands and recruited professional video editors to critique their editing choices. From their critiques, we derive six dimensions of editing quality: narrative progression, audiovisual coordination and sound design, visual composition and graphics, shot-to-shot continuity, message and brand coherence, and temporal rhythm and pacing. We discuss how these dimensions can guide editing-aware generation, human evaluation, and automated evaluation of AI-generated cinematic ads.
