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Face Consistency Benchmark for GenAI Video

arXiv 2505.11425 ↗First posted 16 May 2025cs.CV cs.MMcited by 0

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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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 10 references that are in the map. First posted on arXiv 16 May 2025.

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References · 4

  1. 2015FaceNet: A Unified Embedding for Face Recognition and Clusteringcited by 2,849
  2. 2024CogVideoX: Text-to-Video Diffusion Models with An Expert Transformercited by 2,261
  3. 2024HunyuanVideo: A Systematic Framework For Large Video Generative Modelscited by 1,660
  4. 2024AIGCBench: Comprehensive Evaluation of Image-to-Video Content Generated by AIcited by 27

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