activity
20152023
most citedStructure-Aware Network for Lane Marker Extraction with Dynamic Vision Sensor

17 citations · 40 across the 18 of their papers we have counts for

collaborators

18 papers

eess.IV2023

"Seeing'' Electric Network Frequency from Events

Lexuan Xu, Guang Hua, Haijian Zhang +2

Most of the artificial lights fluctuate in response to the grid's alternating current and exhibit subtle variations in terms of both intensity and spectrum, providing the potential…

eess.SP2020

Improving Spiking Sparse Recovery via Non-Convex Penalties

Xiang Zhang, Lei Yu, Gang Zheng

Compared with digital methods, sparse recovery based on spiking neural networks has great advantages like high computational efficiency and low power-consumption. However, current…

eess.IV2020

Mixed Noise Removal with Pareto Prior

Zhou Liu, Lei Yu, Gui-Song Xia +1

Denoising images contaminated by the mixture of additive white Gaussian noise (AWGN) and impulse noise (IN) is an essential but challenging problem. The presence of impulsive distu…

cs.CV2020★ 17 cited

Structure-Aware Network for Lane Marker Extraction with Dynamic Vision Sensor

Wensheng Cheng, Hao Luo, Wen Yang +2

Lane marker extraction is a basic yet necessary task for autonomous driving. Although past years have witnessed major advances in lane marker extraction with deep learning models,…

cs.CV2020

Event Enhanced High-Quality Image Recovery

Bishan Wang, Jingwei He, Lei Yu +2

With extremely high temporal resolution, event cameras have a large potential for robotics and computer vision. However, their asynchronous imaging mechanism often aggravates the m…

cs.CV2020

Implicit Euler ODE Networks for Single-Image Dehazing

Jiawei Shen, Zhuoyan Li, Lei Yu +2

Deep convolutional neural networks (CNN) have been applied for image dehazing tasks, where the residual network (ResNet) is often adopted as the basic component to avoid the vanish…

eess.SP2020★ 3 cited

Kernel Learning for High-Resolution Time-Frequency Distribution

Lei Jiang, Haijian Zhang, Lei Yu +1

The design of high-resolution and cross-term (CT) free time-frequency distributions (TFDs) has been an open problem. Classical kernel based methods are limited by the trade-off bet…

eess.IV2020★ 3 cited

Single Image Deraining with Continuous Rain Density Estimation

Jingwei He, Lei Yu, Gui-Song Xia +1

Single image deraining (SIDR) often suffers from over/under deraining due to the nonuniformity of rain densities and the variety of raindrop scales. In this paper, we propose a \te…

eess.SP2020★ 9 cited

Robust Time-Frequency Reconstruction by Learning Structured Sparsity

Lei Jiang, Haijian Zhang, Lei Yu

Time-frequency distributions (TFDs) play a vital role in providing descriptive analysis of non-stationary signals involved in realistic scenarios. It is well known that low time-fr…

cs.LG2019★ 1 cited

Learning Cluster Structured Sparsity by Reweighting

Yulun Jiang, Lei Yu, Haijian Zhang +1

Recently, the paradigm of unfolding iterative algorithms into finite-length feed-forward neural networks has achieved a great success in the area of sparse recovery. Benefit from a…

cs.CV2019★ 2 cited

Facial Feature Embedded CycleGAN for VIS-NIR Translation

Huijiao Wang, Li Wang, Xulei Yang +2

VIS-NIR face recognition remains a challenging task due to the distinction between spectral components of two modalities and insufficient paired training data. Inspired by the Cycl…

cs.CV2018★ 5 cited

Image Super-Resolution via RL-CSC: When Residual Learning Meets Convolutional Sparse Coding

Menglei Zhang, Zhou Liu, Lei Yu

We propose a simple yet effective model for Single Image Super-Resolution (SISR), by combining the merits of Residual Learning and Convolutional Sparse Coding (RL-CSC). Our model i…

cs.IT2016

Frequency Estimation of Multiple Sinusoids with Three Sub-Nyquist Channels

Shan Huang, Haijian Zhang, Hong Sun +2

Frequency estimation of multiple sinusoids is significant in both theory and application. In some application scenarios, only sub-Nyquist samples are available to estimate the freq…

cs.IT2016

Line Spectral Estimation Based on Compressed Sensing with Deterministic Sub-Nyquist Sampling

Shan Huang, Hong Sun, Haijian Zhang +1

As an alternative to the traditional sampling theory, compressed sensing allows acquiring much smaller amount of data, still estimating the spectra of frequency-sparse signals accu…

cs.IT2016

Frequency Estimation of Multiple Sinusoids with Sub-Nyquist Sampling Sequences

Shan Huang, Hong Sun, Haijian Zhang +1

In some applications of frequency estimation, the frequencies of multiple sinusoids are required to be estimated from sub-Nyquist sampling sequences. In this paper, we propose a no…

cs.IT2015

A Class of Deterministic Sensing Matrices and Their Application in Harmonic Detection

Shan Huang, Hong Sun, Lei Yu +1

In this paper, a class of deterministic sensing matrices are constructed by selecting rows from Fourier matrices. These matrices have better performance in sparse recovery than ran…

cs.IT2015

An algorithm of frequency estimation for multi-channel coprime sampling

Shan Huang, Haijian Zhang, Hong Sun +1

In some applications of frequency estimation, it is challenging to sample at as high as the Nyquist rate due to hardware limitations. An effective solution is to use multiple sub-N…

cs.IT2015

Joint Frequency Estimation with Two Sub-Nyquist Sampling Sequences

Shan Huang, Hong Sun, Lei Yu +1

In many applications of frequency estimation, the frequencies of the signals are so high that the data sampled at Nyquist rate are hard to acquire due to hardware limitation. In th…