2.4k citations · 4.4k across the 15 of their papers we have counts for
15 papers
Class-Distribution-Aware Pseudo Labeling for Semi-Supervised Multi-Label Learning
Ming-Kun Xie, Jia-Hao Xiao, Hao-Zhe Liu +3
Pseudo-labeling has emerged as a popular and effective approach for utilizing unlabeled data. However, in the context of semi-supervised multi-label learning (SSMLL), conventional…
Learning from Maps: Visual Common Sense for Autonomous Driving
Ari Seff, Jianxiong Xiao
Today's autonomous vehicles rely extensively on high-definition 3D maps to navigate the environment. While this approach works well when these maps are completely up-to-date, safe…
Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge
Andy Zeng, Kuan-Ting Yu, Shuran Song +4
Robot warehouse automation has attracted significant interest in recent years, perhaps most visibly in the Amazon Picking Challenge (APC). A fully autonomous warehouse pick-and-pla…
3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions
Andy Zeng, Shuran Song, Matthias Nießner +3
Matching local geometric features on real-world depth images is a challenging task due to the noisy, low-resolution, and incomplete nature of 3D scan data. These difficulties limit…
DeepContext: Context-Encoding Neural Pathways for 3D Holistic Scene Understanding
Yinda Zhang, Mingru Bai, Pushmeet Kohli +2
While deep neural networks have led to human-level performance on computer vision tasks, they have yet to demonstrate similar gains for holistic scene understanding. In particular,…
ShapeNet: An Information-Rich 3D Model Repository
Angel X. Chang, Thomas Funkhouser, Leonidas Guibas +10
We present ShapeNet: a richly-annotated, large-scale repository of shapes represented by 3D CAD models of objects. ShapeNet contains 3D models from a multitude of semantic categori…