Syn-TODD

Transparent object perception is a crucial skill for applications such as robot manipulation in household and laboratory settings. We establish a novel procedural photo-realistic dataset generation pipeline and create a large-scale transparent object detection dataset, Syn-TODD, which is suitable for training networks with all three modalities, RGB-D, stereo and multi-view RGB.

透明物体感知是家庭与实验室场景下机器人操作等应用的核心关键能力。本研究构建了一套全新的过程式照片级真实感数据集生成流水线，并创建了大规模透明物体检测数据集Syn-TODD，该数据集可用于支持RGB-D、立体视觉以及多视角RGB三种模态的网络模型训练。