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<p>As one of the ten major categories on the UNESCO’s Representative List of Intangible Cultural Heritage of Humanity, traditional opera is a crystallization of human civilization. ‌ The Chinese Traditional Opera Video Super-Resolution (CTOVSR) was developed to protect these precious and irreplaceable aged Chinese opera videos. We analyzed the entire degradation process throughout video lifecycle in this paper. By utilizing high-resolution (HR) videos from professionally restored films and their corresponding low-resolution (LR) versions distributed online, we proposed a novel construction method for LR-HR video sequence pairs, named “Real-world+”. This method ensures that the pairs accurately reflect the real-world degradation process and are strictly aligned both spatially and temporally. We further augmented CTOVSR with synthetically degraded data, resulting in 900 LR-HR video sequence pairs, each pair containing 100 consecutive frames, featuring various unique elements of Chinese traditional opera. While the primary focus of this work is the dataset itself, our proposed dataset construction methodology also offers a valuable practical approach for the preservation of other types of precious historical heritage.</p>

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A Chinese Traditional Opera Video Super-Resolution Dataset Based on the “Real-world+” Degradation Fusion

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月7日

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  • Wang Xi,
  • Bingxin Qin,
  • Yichi Zhang,
  • Xinyu Yang

摘要

As one of the ten major categories on the UNESCO’s Representative List of Intangible Cultural Heritage of Humanity, traditional opera is a crystallization of human civilization. ‌ The Chinese Traditional Opera Video Super-Resolution (CTOVSR) was developed to protect these precious and irreplaceable aged Chinese opera videos. We analyzed the entire degradation process throughout video lifecycle in this paper. By utilizing high-resolution (HR) videos from professionally restored films and their corresponding low-resolution (LR) versions distributed online, we proposed a novel construction method for LR-HR video sequence pairs, named “Real-world+”. This method ensures that the pairs accurately reflect the real-world degradation process and are strictly aligned both spatially and temporally. We further augmented CTOVSR with synthetically degraded data, resulting in 900 LR-HR video sequence pairs, each pair containing 100 consecutive frames, featuring various unique elements of Chinese traditional opera. While the primary focus of this work is the dataset itself, our proposed dataset construction methodology also offers a valuable practical approach for the preservation of other types of precious historical heritage.