  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.
