Titlebook: Document Analysis and Recognition – ICDAR 2024 Workshops; Athens, Greece, Augu Harold Mouchère,Anna Zhu Conference proceedings 2024 The Edi

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Comics Datasets Framework: Mix of?Comics Datasets for?Detection Benchmarkingarch on comics has evolved from basic object detection to more sophisticated tasks. However, the field faces persistent challenges such as small datasets, inconsistent annotations, inaccessible model weights, and results that cannot be directly compared due to varying train/test splits and metrics.

Pigeon

A Comprehensive Gold Standard and?Benchmark for?Comics Text Detection and?Recognitionfrom comic books. To do this, we developed a pipeline for OCR processing and labeling of comic books and created the first text detection and recognition datasets for Western comics, called . and .. We evaluated the performance of fine-tuned state-of-the-art text detection and recognition models on

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Toward Accessible Comics for?Blind and?Low Vision Readersext description of the full story, ready to be forwarded to off-the-shelve speech synthesis tools. We propose to use existing computer vision and optical character recognition techniques to build a grounded context from the comic strip image content, such as panels, characters, text, reading order a

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Colonoscopy

Spatially Augmented Speech Bubble to?Character Association via?Comic Multi-task Learningg increased attention as it enhances the accessibility and analyzability of this rapidly growing medium. Current methods often struggle with the complex spatial relationships within comic panels, which lead to inconsistent associations. To address these shortcomings, we developed a robust machine le

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ances visual and linguistic information, preserving the authenticity of the original texts. Furthermore, the model is able to adapt to historical data even when the recogniser is trained solely on contemporary data, mitigating the need for a large number of annotated historical handwritten images.

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