21 citations · 38 across the 5 of their papers we have counts for
7 papers · 1 filter
Cross-Modal Self-Supervised Learning with Effective Contrastive Units for LiDAR Point Clouds
Mu Cai, Chenxu Luo, Yong Jae Lee +1
3D perception in LiDAR point clouds is crucial for a self-driving vehicle to properly act in 3D environment. However, manually labeling point clouds is hard and costly. There has b…
Exploring Simple 3D Multi-Object Tracking for Autonomous Driving
Chenxu Luo, Xiaodong Yang, Alan Yuille
3D multi-object tracking in LiDAR point clouds is a key ingredient for self-driving vehicles. Existing methods are predominantly based on the tracking-by-detection pipeline and ine…
Self-Supervised Pillar Motion Learning for Autonomous Driving
Chenxu Luo, Xiaodong Yang, Alan Yuille
Autonomous driving can benefit from motion behavior comprehension when interacting with diverse traffic participants in highly dynamic environments. Recently, there has been a grow…
Grouped Spatial-Temporal Aggregation for Efficient Action Recognition
Chenxu Luo, Alan Yuille
Temporal reasoning is an important aspect of video analysis. 3D CNN shows good performance by exploring spatial-temporal features jointly in an unconstrained way, but it also incre…
OriNet: A Fully Convolutional Network for 3D Human Pose Estimation
Chenxu Luo, Xiao Chu, Alan Yuille
In this paper, we propose a fully convolutional network for 3D human pose estimation from monocular images. We use limb orientations as a new way to represent 3D poses and bind the…
Joint Unsupervised Learning of Optical Flow and Depth by Watching Stereo Videos
Yang Wang, Zhenheng Yang, Peng Wang +3
Learning depth and optical flow via deep neural networks by watching videos has made significant progress recently. In this paper, we jointly solve the two tasks by exploiting the…