# ArchCAD-400K: A Large-Scale CAD drawings Dataset and New Baseline for Panoptic Symbol Spotting

arXiv: https://arxiv.org/abs/2503.22346 · HTML: https://mlsanity.com/paper/2503.22346/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 28 of its 44 references that are in the map.
- First posted on arXiv 28 Mar 2025.

## Builds on (most cited first, 28 of 28)

- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [Semi-Supervised Classification with Graph Convolutional Networks](https://mlsanity.com/paper/1609.02907/) (2016)
- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [End-to-End Object Detection with Transformers](https://mlsanity.com/paper/2005.12872/) (2020)
- [ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes](https://mlsanity.com/paper/1702.04405/) (2017)
- [Masked-attention Mask Transformer for Universal Image Segmentation](https://mlsanity.com/paper/2112.01527/) (2021)
- [V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation](https://mlsanity.com/paper/1606.04797/) (2016)
- [Rethinking Atrous Convolution for Semantic Image Segmentation](https://mlsanity.com/paper/1706.05587/) (2017)
- [LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs](https://mlsanity.com/paper/2111.02114/) (2021)
- [Point Transformer](https://mlsanity.com/paper/2011.00931/) (2020)
- [Deep High-Resolution Representation Learning for Visual Recognition](https://mlsanity.com/paper/1908.07919/) (2019)
- [Deep High-Resolution Representation Learning for Human Pose Estimation](https://mlsanity.com/paper/1902.09212/) (2019)
- [DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection](https://mlsanity.com/paper/2203.03605/) (2022)
- [LVIS: A Dataset for Large Vocabulary Instance Segmentation](https://mlsanity.com/paper/1908.03195/) (2019)
- [COCO-Stuff: Thing and Stuff Classes in Context](https://mlsanity.com/paper/1612.03716/) (2016)
- [Panoptic Segmentation](https://mlsanity.com/paper/1801.00868/) (2018)
- [KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D](https://mlsanity.com/paper/2109.13410/) (2021)
- [Point Transformer V2: Grouped Vector Attention and Partition-based Pooling](https://mlsanity.com/paper/2210.05666/) (2022)
- [YouTube-8M: A Large-Scale Video Classification Benchmark](https://mlsanity.com/paper/1609.08675/) (2016)
- [CubiCasa5K: A Dataset and an Improved Multi-Task Model for Floorplan Image Analysis](https://mlsanity.com/paper/1904.01920/) (2019)
- [FloorPlanCAD: A Large-Scale CAD Drawing Dataset for Panoptic Symbol Spotting](https://mlsanity.com/paper/2105.07147/) (2021)
- [Deep Floor Plan Recognition Using a Multi-Task Network with Room-Boundary-Guided Attention](https://mlsanity.com/paper/1908.11025/) (2019)
- [Symbol Spotting on Digital Architectural Floor Plans Using a Deep Learning-based Framework](https://mlsanity.com/paper/2006.00684/) (2020)
- [GAT-CADNet: Graph Attention Network for Panoptic Symbol Spotting in CAD Drawings](https://mlsanity.com/paper/2201.00625/) (2022)
- [Symbol as Points: Panoptic Symbol Spotting via Point-based Representation](https://mlsanity.com/paper/2401.10556/) (2024)
- [SymPoint Revolutionized: Boosting Panoptic Symbol Spotting with Layer Feature Enhancement](https://mlsanity.com/paper/2407.01928/) (2024)
- [CADSpotting: Robust Panoptic Symbol Spotting on Large-Scale CAD Drawings](https://mlsanity.com/paper/2412.07377/) (2024)

## Built on by (most cited first, 5 of 5)

- [Point or Line? Using Line-based Representation for Panoptic Symbol Spotting in CAD Drawings](https://mlsanity.com/paper/2505.23395/) (2025)
- [DoorDet: Semi-Automated Multi-Class Door Detection Dataset via Object Detection and Large Language Models](https://mlsanity.com/paper/2508.07714/) (2025)
- [Architect-Ant: Editable Automatic Furnishing of Architectural Floor Plans](https://mlsanity.com/paper/2606.10953/) (2026)
- [Text-Aided Multi-Modal Panoptic Symbol Spotting for CAD Floor Plan Drawings](https://mlsanity.com/paper/2607.12678/) (2026)
- [Why VLMs Miss Small Objects, and When Zooming In Is Safe](https://mlsanity.com/paper/2610.09313/) (2026)

## Abstract (arXiv)

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.