CVJul 15

KeyFrame-Compass: Towards Comprehensive Evaluation of Keyframe-Conditioned Video Generation

arXiv:2607.1420230.8h-index: 10Has Code
Predicted impact top 1% in CV · last 90 daysOriginality Incremental advance
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This benchmark provides the first systematic evaluation framework for keyframe-conditioned video generation, enabling controlled analysis of model limitations for practitioners.

KeyFrame-Compass is the first comprehensive benchmark for keyframe-conditioned video generation, evaluating nine models across diverse settings. It reveals a fundamental trade-off between faithful keyframe execution and natural video synthesis, with performance degrading under denser keyframe constraints.

Video generation increasingly relies on keyframe-based workflows, where creators specify a sequence of reference images to guide generation. Although recent models support multi-keyframe conditioning, it remains unclear whether they can faithfully reproduce the prescribed keyframes while maintaining overall video quality. We present KeyFrame-Compass, the first comprehensive benchmark for evaluating keyframe-conditioned video generation. The benchmark contains 386 carefully curated samples spanning three application domains, two video structures, two prompt granularities, two conditioning formats, and four keyframe densities, enabling controlled analysis under diverse generation settings. We further introduce an automated evaluation framework that jointly measures keyframe execution and overall video quality. Specifically, we decompose keyframe execution into six complementary metrics covering presence, fidelity, temporal ordering, localization, persistence, and uniqueness, while assessing overall video quality through evidence-grounded MLLM judgments augmented with specialized perception models. Experiments on nine representative video generation systems reveal several fundamental limitations. Current models exhibit a clear trade-off between faithful keyframe execution and natural video synthesis. Their performance further degrades as keyframe constraints become denser and most open-source models also fail to interpret storyboard-grid inputs as temporally ordered keyframe sequences.

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