We present ClothesNet: a large-scale dataset of 3D clothes objects with information-rich annotations. Our dataset consists of around 4400 models covering 11 categories annotated with clothes features, boundary lines, and keypoints. ClothesNet can be used to facilitate a variety of computer vision and robot interaction tasks. Using our dataset, we establish benchmark tasks for clothes perception, including classification, boundary line segmentation, and keypoint detection, and develop simulated clothes environments for robotic interaction tasks, including rearranging, folding, hanging, and dressing. We also demonstrate the efficacy of our ClothesNet in real-world experiments. Supplemental materials and dataset are available on our project webpage.

翻译：我们提出了ClothesNet：一个包含丰富注释信息的大规模三维服装物体数据集。该数据集包含约4400个模型，涵盖11个类别，标注了服装特征、边界线和关键点。ClothesNet可用于促进多种计算机视觉和机器人交互任务。利用该数据集，我们建立了服装感知领域的基准任务，包括分类、边界线分割和关键点检测，并开发了用于机器人交互任务的模拟服装环境，涵盖衣物整理、折叠、悬挂和穿衣。我们还通过真实世界实验验证了ClothesNet的有效性。补充材料和数据集可在我们的项目网页上获取。