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 key points. 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.