mlsanityData to 7 Oct 2026

OregairuChar: A Benchmark Dataset for Character Appearance Frequency Analysis in My Teen Romantic Comedy SNAFU

arXiv 2511.05263 ↗First posted 7 Nov 2025cs.CV cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 11 of its 18 references that are in the map. First posted on arXiv 7 Nov 2025.

Builds on

11 of 18 references.

References · 11

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  3. 2020End-to-End Object Detection with Transformerscited by 7,384
  4. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  5. 2017Adversarial Discriminative Domain Adaptationcited by 1,309
  6. 2022DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detectioncited by 1,306
  7. 2018Domain Adaptive Faster R-CNN for Object Detection in the Wildcited by 442
  8. 2015Sketch-based Manga Retrieval using Manga109 Datasetcited by 326
  9. 2021AnimeCeleb: Large-Scale Animation CelebHeads Dataset for Head Reenactmentcited by 11
  10. 2021DAF:re: A Challenging, Crowd-Sourced, Large-Scale, Long-Tailed Dataset For Anime Character Recognitioncited by 9
  11. 2021Graph Jigsaw Learning for Cartoon Face Recognitioncited by 4

Built on by

Not cited yet.