Recognizing symbols in architectural CAD drawings is critical for various advanced engineering applications. In this paper, we propose a novel CAD data annotation engine that leverages intrinsic attributes from systematically archived CAD drawings to automatically generate high-quality annotations, thus significantly reducing manual labeling efforts. Utilizing this engine, we construct ArchCAD-400K, a large-scale CAD dataset consisting of 413,062 chunks from 5538 highly standardized drawings, making it over 26 times larger than the largest existing CAD dataset. ArchCAD-400K boasts an extended drawing diversity and broader categories, offering line-grained annotations. Furthermore, we present a new baseline model for panoptic symbol spotting, termed Dual-Pathway Symbol Spotter (DPSS). It incorporates an adaptive fusion module to enhance primitive features with complementary image features, achieving state-of-the-art performance and enhanced robustness. Extensive experiments validate the effectiveness of DPSS, demonstrating the value of ArchCAD-400K and its potential to drive innovation in architectural design and construction.

翻译：识别建筑CAD图纸中的符号对于各种高级工程应用至关重要。本文提出了一种新颖的CAD数据标注引擎，该引擎利用系统归档的CAD图纸中的固有属性自动生成高质量标注，从而显著减少了人工标注工作量。利用该引擎，我们构建了ArchCAD-400K，这是一个大规模CAD数据集，包含来自5538张高度标准化图纸的413,062个图块，其规模是现有最大CAD数据集的26倍以上。ArchCAD-400K拥有更广泛的图纸多样性和更全面的类别，并提供线粒度的标注。此外，我们提出了一种用于全景符号识别的新基线模型，称为双通路符号识别器（DPSS）。它集成了一个自适应融合模块，利用互补的图像特征增强原始图元特征，实现了最先进的性能和更强的鲁棒性。大量实验验证了DPSS的有效性，证明了ArchCAD-400K的价值及其在推动建筑设计与施工创新方面的潜力。