activity
20172020
most citedEfficient ADMM and Splitting Methods for Continuous Min-cut and Max-flow Problems

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

math.OC2020

Variational Image Motion Estimation by Accelerated Dual Optimization

Hongpeng Sun, Xue-Cheng Tai, Jing Yuan

Estimating optical flows is one of the most interesting problems in computer vision, which estimates the essential information about pixel-wise displacements between two consecutiv…

math.OC20202 cited

Efficient ADMM and Splitting Methods for Continuous Min-cut and Max-flow Problems

Hongpeng Sun, Xuecheng Tai, Jing Yuan

The Potts model has many applications. It is equivalent to some min-cut and max-flow models. Primal-dual algorithms have been used to solve these problems. Due to the special struc…

cs.CV2018

Multi-region segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks

Jose Dolz, Xiaopan Xu, Jerome Rony +7

Precise segmentation of bladder walls and tumor regions is an essential step towards non-invasive identification of tumor stage and grade, which is critical for treatment decision…

cs.CV2018

HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation

Jose Dolz, Karthik Gopinath, Jing Yuan +3

Recently, dense connections have attracted substantial attention in computer vision because they facilitate gradient flow and implicit deep supervision during training. Particularl…

cs.CV2017

Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation

Jose Dolz, Christian Desrosiers, Li Wang +3

Precise 3D segmentation of infant brain tissues is an essential step towards comprehensive volumetric studies and quantitative analysis of early brain developement. However, comput…