Comic Datasets

Research on comic datasets focuses on developing comprehensive benchmarks and large-scale datasets to facilitate advancements in automated comic understanding and generation. Current efforts concentrate on multi-task learning approaches, addressing challenges like object detection, character recognition (including re-identification and speaker prediction), text extraction and recognition, and multimodal reasoning across diverse comic styles. These datasets and associated benchmarks are crucial for evaluating and improving the performance of machine learning models, ultimately enabling more sophisticated applications in areas such as comic analysis, generation, and accessibility.