IndustryShapes Dataset

RGB-D dataset for 6D pose estimation of industrial components/tools

BOP format: This dataset fully complies with the BOP format

5 objects commonly found in an industrial assembly environment: The objects are symmetric and textureless presenting challenges for 6D pose estimation.

Data acquisition with an Intel RealSense D455 camera: The dataset was captured at a resolution of 640×480. Both training and test images were collected under controlled conditions.

Training images (4,107 in total): 1361 synthetic images, 2.746 real including scenes with individual and multiple objects are depicted

Test images (1,354 in total): 1354 real test images.

The photorealistic synthetic images were generated using a custom OpenGL-based implementation: 6DL-PoseGenerator [1]

[1] Pateraki, M., Sapoutzoglou, P., Lourakis, M.I.: Crane spreader pose estimation from a single view. In: Proceedings of the 18th International Joint Conference on Computer Vision, vol. 5, pp. 796-805. SCITEPRESS (2023)

用于工业零部件/工具6D位姿估计的RGB-D数据集

BOP格式：本数据集完全符合BOP格式规范

工业装配场景中常见的5类物体：此类物体均为对称无纹理类型，为6D位姿估计任务带来了显著挑战。

数据采集采用英特尔RealSense D455相机：本数据集的采集分辨率为640×480，训练集与测试集图像均在可控环境下完成采集。

训练图像总计4107张：其中包含1361张合成图像，另有2746张真实场景图像，涵盖单物体与多物体的拍摄场景。

测试图像总计1354张，全部为真实场景采集的测试图像。

本数据集的照片级真实感合成图像基于自研的OpenGL实现生成：6DL-PoseGenerator [1]

[1] Pateraki, M., Sapoutzoglou, P., Lourakis, M.I.: 基于单视图的起重机吊具位姿估计. 见: 第18届国际计算机视觉联合会议论文集, 第5卷, 第796-805页. SCITEPRESS (2023)