Face Consistency Benchmark for GenAI Video
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Abstract (arXiv)
Video generation driven by artificial intelligence has advanced significantly, enabling the creation of dynamic and realistic content. However, maintaining character consistency across video sequences remains a major challenge, with current models struggling to ensure coherence in appearance and attributes. This paper introduces the Face Consistency Benchmark (FCB), a framework for evaluating and comparing the consistency of characters in AI-generated videos. By providing standardized metrics, the benchmark highlights gaps in existing solutions and promotes the development of more reliable approaches. This work represents a crucial step toward improving character consistency in AI video generation technologies.
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References · 4
- 2015FaceNet: A Unified Embedding for Face Recognition and Clusteringcited by 2,849
- 2024CogVideoX: Text-to-Video Diffusion Models with An Expert Transformercited by 2,261
- 2024HunyuanVideo: A Systematic Framework For Large Video Generative Modelscited by 1,660
- 2024AIGCBench: Comprehensive Evaluation of Image-to-Video Content Generated by AIcited by 27
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