Summary of Omnidocbench: Benchmarking Diverse Pdf Document Parsing with Comprehensive Annotations, by Linke Ouyang et al.
OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotations
by Linke Ouyang, Yuan Qu, Hongbin Zhou, Jiawei Zhu, Rui Zhang, Qunshu Lin, Bin Wang, Zhiyuan Zhao, Man Jiang, Xiaomeng Zhao, Jin Shi, Fan Wu, Pei Chu, Minghao Liu, Zhenxiang Li, Chao Xu, Bo Zhang, Botian Shi, Zhongying Tu, Conghui He
First submitted to arxiv on: 10 Dec 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Information Retrieval (cs.IR)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel benchmark, OmniDocBench, is introduced to advance automated document content extraction in computer vision. This multi-source benchmark addresses limitations of current methods by providing a meticulously curated and annotated high-quality evaluation dataset comprising nine diverse document types. The benchmark offers a flexible and comprehensive evaluation framework with 19 layout category labels and 14 attribute labels, enabling assessments across entire datasets or specific data types. A comparative analysis is performed on existing modular pipelines and multimodal end-to-end methods, highlighting their limitations in handling document diversity. OmniDocBench establishes a robust, diverse, and fair evaluation standard for the field, offering crucial insights for future advancements. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary OmniDocBench is a new way to test how well computers can understand documents. Right now, computers are really good at understanding some kinds of text, but they struggle with others. To help fix this problem, researchers created OmniDocBench, a big collection of different types of documents that computers need to be able to read and understand. The goal is to make sure computers can handle all sorts of documents, not just the easy ones. By testing how well computers do on these different types of documents, we can figure out what they’re good at and where they need more help. |
