真实考古残片重建数据集，挑战复杂现实世界拼图算法。
Re-assembling the past: The RePAIR dataset and benchmark for real world 2D and 3D puzzle solving
- 基于庞贝古城壁画崩塌真实碎片构建，形状不规则且缺损。
- 含1.6万片碎片，1000片经考古学家人工拼合得真值。
- 多模态数据支持，适合研究真实场景下的智能重建方法。
本文提出RePAIR数据集，为2D与3D拼图复原任务提供具有挑战性的现实基准。数据源自二战期间庞贝考古公园壁画因轰炸倒塌的碎片，其断裂形态逼真，表面侵蚀严重，存在缺失与不规则形状，显著增加复原难度。数据集包含高分辨率图像、碎片3D扫描及考古学家标注的元数据。真值通过数年实地工作生成：包括每片碎片的挖掘清理，以及对约1000片（共16000片）的专家手动拼合。所有碎片完成3D数字化后，构建了用于评估现有复原与拼图方法的基准。测试基线表明，当前算法在解决此类复杂现实问题上仍有明显差距。
原文摘要 · Abstract (English)
This paper proposes the RePAIR dataset that represents a challenging benchmark to test modern computational and data driven methods for puzzle-solving and reassembly tasks. Our dataset has unique properties that are uncommon to current benchmarks for 2D and 3D puzzle solving. The fragments and fractures are realistic, caused by a collapse of a fresco during a World War II bombing at the Pompeii archaeological park. The fragments are also eroded and have missing pieces with irregular shapes and different dimensions, challenging further the reassembly algorithms. The dataset is multi-modal providing high resolution images with characteristic pictorial elements, detailed 3D scans of the fragments and meta-data annotated by the archaeologists. Ground truth has been generated through several years of unceasing fieldwork, including the excavation and cleaning of each fragment, followed by manual puzzle solving by archaeologists of a subset of approx. 1000 pieces among the 16000 available. After digitizing all the fragments in 3D, a benchmark was prepared to challenge current reassembly and puzzle-solving methods that often solve more simplistic synthetic scenarios. The tested baselines show that there clearly exists a gap to fill in solving this computationally complex problem.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。