337 citations · 366 across the 3 of their papers we have counts for
3 papers
cs.RO2019★ 17 cited
DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions
Zhenjia Xu, Jiajun Wu, Andy Zeng +2
We study the problem of learning physical object representations for robot manipulation. Understanding object physics is critical for successful object manipulation, but also chall…
cs.CV2017★ 12 cited
Im2Pano3D: Extrapolating 360 Structure and Semantics Beyond the Field of View
Shuran Song, Andy Zeng, Angel X. Chang +3
We present Im2Pano3D, a convolutional neural network that generates a dense prediction of 3D structure and a probability distribution of semantic labels for a full 360 panoramic vi…
cs.CV2017★ 337 cited
Matterport3D: Learning from RGB-D Data in Indoor Environments
Angel Chang, Angela Dai, Thomas Funkhouser +6
Access to large, diverse RGB-D datasets is critical for training RGB-D scene understanding algorithms. However, existing datasets still cover only a limited number of views or a re…