45 citations · 61 across the 6 of their papers we have counts for
6 papers · 1 filter
Deep Learning Approaches in Pavement Distress Identification: A Review
Sizhe Guan, Haolan Liu, Hamid R. Pourreza +1
This paper presents a comprehensive review of recent advancements in image processing and deep learning techniques for pavement distress detection and classification, a critical as…
Connections between Operator-splitting Methods and Deep Neural Networks with Applications in Image Segmentation
Hao Liu, Xue-Cheng Tai, Raymond Chan
Deep neural network is a powerful tool for many tasks. Understanding why it is so successful and providing a mathematical explanation is an important problem and has been one popul…
PottsMGNet: A Mathematical Explanation of Encoder-Decoder Based Neural Networks
Xue-Cheng Tai, Hao Liu, Raymond Chan
For problems in image processing and many other fields, a large class of effective neural networks has encoder-decoder-based architectures. Although these networks have made impres…
Fine-grained Action Analysis: A Multi-modality and Multi-task Dataset of Figure Skating
Sheng-Lan Liu, Yu-Ning Ding, Gang Yan +4
The fine-grained action analysis of the existing action datasets is challenged by insufficient action categories, low fine granularities, limited modalities, and tasks. In this pap…
A Color Elastica Model for Vector-Valued Image Regularization
Hao Liu, Xue-Cheng Tai, Ron Kimmel +1
Models related to the Euler's elastica energy have proven to be useful for many applications including image processing. Extending elastica models to color images and multi-channel…
Curvature Regularized Surface Reconstruction from Point Cloud
Yuchen He, Sung Ha Kang, Hao Liu
We propose a variational functional and fast algorithms to reconstruct implicit surface from point cloud data with a curvature constraint. The minimizing functional balances the di…