3 papers
cs.CV2018
Learning to predict crisp boundaries
Ruoxi Deng, Chunhua Shen, Shengjun Liu +2
Recent methods for boundary or edge detection built on Deep Convolutional Neural Networks (CNNs) typically suffer from the issue of predicted edges being thick and need post-proces…
cs.CV2017
Relative Depth Order Estimation Using Multi-scale Densely Connected Convolutional Networks
Ruoxi Deng, Tianqi Zhao, Chunhua Shen +1
We study the problem of estimating the relative depth order of point pairs in a monocular image. Recent advances mainly focus on using deep convolutional neural networks (DCNNs) to…
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…