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.

ClothesNet 是一个大规模的 3D 服装对象数据集，注释包含服装特征、边界线和关键点，可用于计算机视觉和机器人交互任务。通过该数据集，我们为服装感知建立了基准任务，并在机器人交互任务中开发了模拟服装环境，并展示了 ClothesNet 在现实世界实验中的功效。