Attack on Titan (AoT): Anime image dataset for character, scene, emotion recognition and beyond
Year: 2025
Type: data-paper
Abstract: Anime is an influential medium with global popularity, combining visual aesthetics with narrative depth and offering potential applications in content analysis, style transfer, and emotion recognition within computer vision research. Despite its widespread appeal, publicly available anime character datasets remain scarce. To address this gap, we propose the Attack on Titan: Anime Image Dataset, derived from the popular series Attack on Titan , to support anime-focused computer vision research. The dataset comprises 4,041 high-quality images divided into 14 classes, each representing a prominent character from the series. These images are manually collected through high-resolution screenshots, capturing a wide range of character poses, expressions, costumes, and backgrounds. The dataset is suitable for various computer vision tasks, including character recognition, emotion detection, style classification, and domain adaptation.
Source: Data in Brief
Authors: Guldasta Imraj Khan, Hafeez Anwar, Qasim Jan, Shahid Hussain
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,220
OpenAlex ID: W4416040412