Yu Xiang, Wonhui Kim, Wei Chen, Jingwei Ji, Christopher Bongsoo Choy, Hao Su, Roozbeh Mottaghi, Leonidas J. Guibas, Silvio Savarese: ObjectNet3D: A Large Scale Database for 3D Object Recognition. ECCV (8) 2016: 160-176


We contribute a large scale database for 3D object recognition, named ObjectNet3D, that consists of 100 categories, 90,127 images, 201,888 objects in these images and 44,147 3D shapes. Objects in the 2D images in our database are aligned with the 3D shapes, and the alignment provides both accurate 3D pose annotation and the closest 3D shape annotation for each 2D object. Consequently, our database is useful for recognizing the 3D pose and 3D shape of objects from 2D images. We also provide baseline experiments on four tasks: region proposal generating, 2D object detection, joint 2D detection and 3D object pose estimation, and image-based 3D shape retrieval, which can serve as baselines for future research using our database. Our database is available online at http://cvgl.stanford.edu/projects/objectnet3d


  title     = {ObjectNet3D: A Large Scale Database for 3D Object Recognition},
  author    = {Xiang, Yu and Kim, Wonhui and Chen, Wei and Ji, Jingwei and Choy, Christopher and Su, Hao and Mottaghi, Roozbeh and Guibas, Leonidas and Savarese, Silvio},
  booktitle = {European Conference Computer Vision (ECCV)},
  year      = {2016}