Core Concepts
Large video generative models require a comprehensive evaluation framework beyond simple metrics to assess performance accurately.
Abstract
The article introduces EvalCrafter, a novel framework for evaluating large video generation models comprehensively.
It highlights the limitations of current evaluation methods based on simple metrics like FVD or IS.
Proposes a new approach involving 700 prompts for text-to-video generation and 17 objective metrics for evaluation.
Discusses the importance of considering visual qualities, content qualities, motion qualities, and text-video alignment in evaluating video generative models.
Presents findings from the evaluation process and emphasizes the need for multi-aspect evaluations in T2V models.
Stats
我々は、テキストからビデオへの生成に関する総合的な評価フレームワークを導入します。
700のプロンプトと17の客観的指標を使用して、大規模ビデオ生成モデルを評価します。
ビジュアル品質、コンテンツ品質、動きの品質、およびテキストとビデオの整合性を考慮することが重要です。