5 citations · 14 across the 5 of their papers we have counts for
5 papers
MotionTrack: End-to-End Transformer-based Multi-Object Tracing with LiDAR-Camera Fusion
Ce Zhang, Chengjie Zhang, Yiluan Guo +2
Multiple Object Tracking (MOT) is crucial to autonomous vehicle perception. End-to-end transformer-based algorithms, which detect and track objects simultaneously, show great poten…
ADCNet: Learning from Raw Radar Data via Distillation
Bo Yang, Ishan Khatri, Michael Happold +1
As autonomous vehicles and advanced driving assistance systems have entered wider deployment, there is an increased interest in building robust perception systems using radars. Rad…
Joint Pose and Shape Estimation of Vehicles from LiDAR Data
Hunter Goforth, Xiaoyan Hu, Michael Happold +1
We address the problem of estimating the pose and shape of vehicles from LiDAR scans, a common problem faced by the autonomous vehicle community. Recent work has tended to address…
Geometry-Aware Instance Segmentation with Disparity Maps
Cho-Ying Wu, Xiaoyan Hu, Michael Happold +2
Most previous works of outdoor instance segmentation for images only use color information. We explore a novel direction of sensor fusion to exploit stereo cameras. Geometric infor…
Hierarchical Deep Stereo Matching on High-resolution Images
Gengshan Yang, Joshua Manela, Michael Happold +1
We explore the problem of real-time stereo matching on high-res imagery. Many state-of-the-art (SOTA) methods struggle to process high-res imagery because of memory constraints or…