CHI25 — Sketch2Terrain: AI-Driven Real-Time Terrain Sketch Mapping in Augmented Reality — Dataset

The dataset for CHI2025 paper: Sketch2Terrain: AI-Driven Real-Time Terrain Sketch Mapping in AR.

In this paper, we present a generative AI model (Pix2Pix model) that converts 3D sketches created in AR into 3D terrain models. The GitHub page for this open-source project is https://github.com/TX-XR/Sketch2Terrain.

Introduction: The dataset contains the pairs of human-sketched main structures of the terrain and the corresponding height map of the ground truth terrain. The dataset uses real terrain features from all over the world, including rivers, ridges, basins, and peaks, as training data.

Data Collection: We collected 287 sketches, created by two researchers at a rate of 10 sketches per hour using the AR 3D sketching tools we developed. Both sketch and terrain height map values are normalized to a range of [0, 255] and saved as PNG files. 

Data Augmentation: The collected sketch maps were split into training (80%) and testing (20%) subsets, with augmentation applied only to the training set. Augmentation included height value scaling and tailored transformations like translation and rotation, while blank spaces created during transformations were filled with black pixels. Augmentation increased the training dataset to over 2,000 samples.

Feel free to distribute and use the data.

本数据集对应CHI 2025会议论文《Sketch2Terrain：增强现实中AI驱动的实时地形草图映射》。
本文提出了生成式AI模型（Pix2Pix model），可将增强现实（Augmented Reality, AR）环境中创建的3D草图转换为3D地形模型。该开源项目的GitHub页面为https://github.com/TX-XR/Sketch2Terrain。

数据集概述：本数据集包含人工绘制的地形主体结构草图与对应真实地形的真值高度图配对样本。数据集采用来自全球各地的真实地形特征（包括河流、山脊、盆地与山峰）作为训练数据。

数据收集：我们通过自研的AR 3D草图绘制工具，由两名研究人员以每小时10幅的速度完成绘制，共收集到287幅草图。所有草图与地形高度图的数值均归一化至[0, 255]区间，并以PNG格式存储。

数据增强：将收集到的草图样本划分为训练集（80%）与测试集（20%），仅对训练集实施数据增强操作。增强手段包括高度值缩放与定制化变换（如平移、旋转），变换过程中产生的空白区域将以黑色像素填充。经数据增强后，训练集样本量扩充至2000余幅。

本数据集可自由分发与使用。