ChronoMagic-Bench：用于文本转时间延时视频生成的形变评估基准。

ChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation

June 26, 2024

作者: Shenghai Yuan, Jinfa Huang, Yongqi Xu, Yaoyang Liu, Shaofeng Zhang, Yujun Shi, Ruijie Zhu, Xinhua Cheng, Jiebo Luo, Li Yuan

cs.AI

摘要

我们提出了一个新颖的文本到视频（T2V）生成基准，ChronoMagic-Bench，用于评估T2V模型（如Sora和Lumiere）在延时视频生成中的时间和变形能力。与现有侧重于生成视频的视觉质量和文本相关性的基准不同，ChronoMagic-Bench专注于模型生成具有显著变形幅度和时间连贯性的延时视频的能力。该基准通过自由形式文本查询考察T2V模型的物理、生物和化学能力。为此，ChronoMagic-Bench引入了1,649个提示和真实世界视频作为参考，分为四种主要类型的延时视频：生物、人造、气象和物理现象，进一步划分为75个子类别。这种分类全面评估了模型处理多样化和复杂变换的能力。为了准确对齐人类偏好与基准，我们引入了两个新的自动度量标准，MTScore和CHScore，用于评估视频的变形属性和时间连贯性。MTScore衡量变形幅度，反映随时间变化的程度，而CHScore评估时间连贯性，确保生成的视频保持逻辑进展和连续性。基于ChronoMagic-Bench，我们对十个代表性T2V模型进行了全面的手动评估，揭示它们在不同提示类别上的优势和劣势，并提供了一个全面的评估框架，解决了视频生成研究中的当前差距。此外，我们创建了一个大规模的ChronoMagic-Pro数据集，包含460k对720p高质量延时视频和详细说明，确保具有高物理相关性和大变形幅度。

English

We propose a novel text-to-video (T2V) generation benchmark, ChronoMagic-Bench, to evaluate the temporal and metamorphic capabilities of the T2V models (e.g. Sora and Lumiere) in time-lapse video generation. In contrast to existing benchmarks that focus on the visual quality and textual relevance of generated videos, ChronoMagic-Bench focuses on the model's ability to generate time-lapse videos with significant metamorphic amplitude and temporal coherence. The benchmark probes T2V models for their physics, biology, and chemistry capabilities, in a free-form text query. For these purposes, ChronoMagic-Bench introduces 1,649 prompts and real-world videos as references, categorized into four major types of time-lapse videos: biological, human-created, meteorological, and physical phenomena, which are further divided into 75 subcategories. This categorization comprehensively evaluates the model's capacity to handle diverse and complex transformations. To accurately align human preference with the benchmark, we introduce two new automatic metrics, MTScore and CHScore, to evaluate the videos' metamorphic attributes and temporal coherence. MTScore measures the metamorphic amplitude, reflecting the degree of change over time, while CHScore assesses the temporal coherence, ensuring the generated videos maintain logical progression and continuity. Based on the ChronoMagic-Bench, we conduct comprehensive manual evaluations of ten representative T2V models, revealing their strengths and weaknesses across different categories of prompts, and providing a thorough evaluation framework that addresses current gaps in video generation research. Moreover, we create a large-scale ChronoMagic-Pro dataset, containing 460k high-quality pairs of 720p time-lapse videos and detailed captions ensuring high physical pertinence and large metamorphic amplitude.