19 citations · 30 across the 10 of their papers we have counts for
6 papers · 1 filter
Camera Pose Refinement via 3D Gaussian Splatting
Lulu Hao, Lipu Zhou, Zhenzhong Wei +1
Camera pose refinement aims at improving the accuracy of initial pose estimation for applications in 3D computer vision. Most refinement approaches rely on 2D-3D correspondences wi…
Ada3D : Exploiting the Spatial Redundancy with Adaptive Inference for Efficient 3D Object Detection
Tianchen Zhao, Xuefei Ning, Ke Hong +8
Voxel-based methods have achieved state-of-the-art performance for 3D object detection in autonomous driving. However, their significant computational and memory costs pose a chall…
Efficient Second-Order Plane Adjustment
Lipu Zhou
Planes are generally used in 3D reconstruction for depth sensors, such as RGB-D cameras and LiDARs. This paper focuses on the problem of estimating the optimal planes and sensor po…
An Efficient Planar Bundle Adjustment Algorithm
Lipu Zhou, Daniel Koppel, Hui Ju +2
This paper presents an efficient algorithm for the least-squares problem using the point-to-plane cost, which aims to jointly optimize depth sensor poses and plane parameters for 3…
Do not Omit Local Minimizer: a Complete Solution for Pose Estimation from 3D Correspondences
Lipu Zhou, Shengze Wang, Jiamin Ye +1
Estimating pose from given 3D correspondences, including point-to-point, point-to-line and point-to-plane correspondences, is a fundamental task in computer vision with many applic…
Unsupervised Learning of Monocular Depth Estimation with Bundle Adjustment, Super-Resolution and Clip Loss
Lipu Zhou, Jiamin Ye, Montiel Abello +2
We present a novel unsupervised learning framework for single view depth estimation using monocular videos. It is well known in 3D vision that enlarging the baseline can increase t…