activity
20172024
most citedLodoNet: A Deep Neural Network with 2D Keypoint Matchingfor 3D LiDAR Odometry Estimation

41 citations · 174 across the 22 of their papers we have counts for

collaborators

26 papers

cs.RO2021

Prediction of Metacarpophalangeal joint angles and Classification of Hand configurations based on Ultrasound Imaging of the Forearm

Keshav Bimbraw, Christopher Julius Nycz, Matt Schueler +2

With the advancement in computing and robotics, it is necessary to develop fluent and intuitive methods for interacting with digital systems, AR/VR interfaces, and physical robotic…

cs.RO202112 cited

LiDAR Odometry Methodologies for Autonomous Driving: A Survey

Nikhil Jonnavithula, Yecheng Lyu, Ziming Zhang

Vehicle odometry is an essential component of an automated driving system as it computes the vehicle's position and orientation. The odometry module has a higher demand and impact…

cs.CV20218 cited

Revisiting 2D Convolutional Neural Networks for Graph-based Applications

Yecheng Lyu, Xinming Huang, Ziming Zhang

Graph convolutional networks (GCNs) are widely used in graph-based applications such as graph classification and segmentation. However, current GCNs have limitations on implementat…

cs.CV20211 cited

Deep Lucas-Kanade Homography for Multimodal Image Alignment

Yiming Zhao, Xinming Huang, Ziming Zhang

Estimating homography to align image pairs captured by different sensors or image pairs with large appearance changes is an important and general challenge for many computer vision…

cs.CV202141 cited

A Surface Geometry Model for LiDAR Depth Completion

Yiming Zhao, Lin Bai, Ziming Zhang +1

LiDAR depth completion is a task that predicts depth values for every pixel on the corresponding camera frame, although only sparse LiDAR points are available. Most of the existing…

cs.CV2021

Training Deep Neural Networks via Branch-and-Bound

Yuanwei Wu, Ziming Zhang, Guanghui Wang

In this paper, we propose BPGrad, a novel approximate algorithm for deep nueral network training, based on adaptive estimates of feasible region via branch-and-bound. The method is…