The analysis of character appearance frequency is essential for understanding narrative structure, character prominence, and story progression in anime. In this work, we introduce OregairuChar, a benchmark dataset designed for appearance frequency analysis in the anime series My Teen Romantic Comedy SNAFU. The dataset comprises 1600 manually selected frames from the third season, annotated with 2860 bounding boxes across 11 main characters. OregairuChar captures diverse visual challenges, including occlusion, pose variation, and inter-character similarity, providing a realistic basis for appearance-based studies. To enable quantitative research, we benchmark several object detection models on the dataset and leverage their predictions for fine-grained, episode-level analysis of character presence over time. This approach reveals patterns of character prominence and their evolution within the narrative. By emphasizing appearance frequency, OregairuChar serves as a valuable resource for exploring computational narrative dynamics and character-centric storytelling in stylized media.

翻译：角色出场频率分析对于理解动画的叙事结构、角色重要性及故事进展至关重要。本研究提出了OregairuChar，一个专为动画《我的青春恋爱物语果然有问题》中角色出场频率分析设计的基准数据集。该数据集包含从第三季中人工选取的1600帧图像，标注了涵盖11位主要角色的2860个边界框。OregairuChar涵盖了遮挡、姿态变化及角色间相似性等多种视觉挑战，为基于出场频率的研究提供了真实基础。为支持定量研究，我们在数据集上对多种目标检测模型进行了基准测试，并利用其预测结果对角色随时间变化的出场情况进行细粒度的分集分析。该方法揭示了角色重要性在叙事中的模式及其演变规律。通过聚焦出场频率，OregairuChar为探索风格化媒体中的计算叙事动力学及以角色为中心的叙事方法提供了宝贵资源。