mlsanityData to 14 Oct 2026

CMEdataset Advancing China Map Detection and Standardization with Digital Image Resources

arXiv 2504.07476 ↗First posted 10 Apr 2025cs.CV cs.AIcited by 0

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Abstract (arXiv)

Digital images of Chinas maps play a crucial role in map detection, particularly in ensuring national sovereignty, territorial integrity, and map compliance. However, there is currently no publicly available dataset specifically dedicated to problematic maps the CME dataset. Existing datasets primarily focus on general map data and are insufficient for effectively identifying complex issues such as national boundary misrepresentations, missing elements, and blurred boundaries. Therefore, this study creates a Problematic Map dataset that covers five key problem areas, aiming to provide diverse samples for problematic map detection technologies, support high-precision map compliance detection, and enhance map data quality and timeliness. This dataset not only provides essential resources for map compliance, national security monitoring, and map updates, but also fosters innovation and application of related technologies.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 15 references that are in the map. First posted on arXiv 10 Apr 2025.

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References · 4

  1. 2024YOLOv10: Real-Time End-to-End Object Detectioncited by 515
  2. 2024YOLOv11: An Overview of the Key Architectural Enhancementscited by 425
  3. 2021Fast Convergence of DETR with Spatially Modulated Co-Attentioncited by 176
  4. 2023Lite DETR : An Interleaved Multi-Scale Encoder for Efficient DETRcited by 36

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