activity
20152020
most citedMLCVNet: Multi-Level Context VoteNet for 3D Object Detection

28 citations · 37 across the 3 of their papers we have counts for

collaborators

5 papers

cs.GR20209 cited

Deep Feature-preserving Normal Estimation for Point Cloud Filtering

Dening Lu, Xuequan Lu, Yangxing Sun +1

Point cloud filtering, the main bottleneck of which is removing noise (outliers) while preserving geometric features, is a fundamental problem in 3D field. The two-step schemes inv…

cs.CV202028 cited

MLCVNet: Multi-Level Context VoteNet for 3D Object Detection

Qian Xie, Yu-Kun Lai, Jing Wu +4

In this paper, we address the 3D object detection task by capturing multi-level contextual information with the self-attention mechanism and multi-scale feature fusion. Most existi…

eess.IV2019

DRD-Net: Detail-recovery Image Deraining via Context Aggregation Networks

Sen Deng, Mingqiang Wei, Jun Wang +3

Image deraining is a fundamental, yet not well-solved problem in computer vision and graphics. The traditional image deraining approaches commonly behave ineffectively in medium an…

cs.CV2018

Matrix Recovery with Implicitly Low-Rank Data

Xingyu Xie, Jianlong Wu, Guangcan Liu +1

In this paper, we study the problem of matrix recovery, which aims to restore a target matrix of authentic samples from grossly corrupted observations. Most of the existing methods…

cs.GR2015

A Closed-Form Formulation of HRBF-Based Surface Reconstruction

Shengjun Liu, Charlie C. L. Wang, Guido Brunnett +1

The Hermite radial basis functions (HRBFs) implicits have been used to reconstruct surfaces from scattered Hermite data points. In this work, we propose a closed-form formulation t…