ClothesNet: An Information-Rich 3D Garment Model Repository with Simulated Clothes Environment
This dataset addresses the need for comprehensive 3D garment data for computer vision and robotics applications, though it is incremental as it builds on existing dataset creation efforts.
The authors introduced ClothesNet, a large-scale dataset of 3D garment models with rich annotations, consisting of around 4400 models across 11 categories, to facilitate computer vision and robotic interaction tasks. They established benchmark tasks for clothes perception and developed simulated environments for robotic manipulation, demonstrating efficacy in real-world experiments.
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.