activity
20162023
most citedDeep Online Correction for Monocular Visual Odometry

21 citations · 36 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023

RoMe: Towards Large Scale Road Surface Reconstruction via Mesh Representation

Ruohong Mei, Wei Sui, Jiaxin Zhang +4

In autonomous driving applications, accurate and efficient road surface reconstruction is paramount. This paper introduces RoMe, a novel framework designed for the robust reconstru…

cs.CV2023★ 2 cited

VMA: Divide-and-Conquer Vectorized Map Annotation System for Large-Scale Driving Scene

Shaoyu Chen, Yunchi Zhang, Bencheng Liao +7

High-definition (HD) map serves as the essential infrastructure of autonomous driving. In this work, we build up a systematic vectorized map annotation framework (termed VMA) for e…

cs.CV2022★ 8 cited

Towards Accurate Ground Plane Normal Estimation from Ego-Motion

Jiaxin Zhang, Wei Sui, Qian Zhang +2

In this paper, we introduce a novel approach for ground plane normal estimation of wheeled vehicles. In practice, the ground plane is dynamically changed due to braking and unstabl…

cs.CV2021★ 2 cited

Road-aware Monocular Structure from Motion and Homography Estimation

Wei Sui, Teng Chen, Jiaxin Zhang +2

Structure from motion (SFM) and ground plane homography estimation are critical to autonomous driving and other robotics applications. Recently, much progress has been made in usin…

cs.CV2021★ 3 cited

Monocular Road Planar Parallax Estimation

Haobo Yuan, Teng Chen, Wei Sui +4

Estimating the 3D structure of the drivable surface and surrounding environment is a crucial task for assisted and autonomous driving. It is commonly solved either by using 3D sens…

cs.CV2021★ 21 cited

Deep Online Correction for Monocular Visual Odometry

Jiaxin Zhang, Wei Sui, Xinggang Wang +3

In this work, we propose a novel deep online correction (DOC) framework for monocular visual odometry. The whole pipeline has two stages: First, depth maps and initial poses are ob…