activity
20182021
most citedGrouped Spatial-Temporal Aggregation for Efficient Action Recognition

21 citations · 38 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2021

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…

cs.CV20215 cited

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…

cs.RO202012 cited

Probabilistic Multi-modal Trajectory Prediction with Lane Attention for Autonomous Vehicles

Chenxu Luo, Lin Sun, Dariush Dabiri +1

Trajectory prediction is crucial for autonomous vehicles. The planning system not only needs to know the current state of the surrounding objects but also their possible states in…

cs.CV201921 cited

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…

cs.CV2018

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…

cs.CV2018

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…