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arxiv:2406.18522

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

Published on Jun 26
· Submitted by BestWishYsh on Jun 27
#3 Paper of the day
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Abstract

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.

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We have developed a new text-to-video generation benchmark for metamorphic evaluation. We specifically design four major categories for time.lapse videos (as shown below), including biological, human-created, meteorological, and physical videos.and extend these to 75 subcategories.
paper: https://arxiv.org/abs/2406.18522
leaderboard: https://huggingface.co/spaces/BestWishYsh/ChronoMagic-Bench
code: https://github.com/PKU-YuanGroup/ChronoMagic-Bench

Another great work by PKU Yuan group! 🚀

It would be great if you could set up an organisation on the hub to gather all your impressive projects like: Open-Sora Plan and MagicTime.
Here is the guide 👉https://huggingface.co/docs/hub/organizations-managing

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Paper author

Thanks for the encouragement! We'll check out the guide you shared and create an organization in the future.

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