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Evaluating Design Video Generation: Metrics for Compositional Fidelity

Adrienne Deganutti, Dingning Cao, Jaejung Seol, Elad Hirsch, Purvanshi Mehta

arXiv:2605.16223Published May 15, 20260 citations
  • cs.GR
  • cs.AI
  • cs.CV

Abstract

Generative video models are increasingly used in design animation tasks, yet no standardized evaluation framework exists for this domain. Unlike natural video generation, design animation imposes structured constraints: specific components shall animate with prescribed motion types, directions, speed and timing, while non-animated regions must remain stable and layout structure must be preserved. This paper provides a fully automated evaluation framework organized across four dimensions: layout fidelity, motion correctness, temporal quality, and content fidelity. This eliminates the reliance on subjective human evaluation and establishes a common basis for benchmarking progress in the field.

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