181 citations · 312 across the 21 of their papers we have counts for
22 papers
Loop Closure Detection Based on Object-level Spatial Layout and Semantic Consistency
Xingwu Ji, Peilin Liu, Haochen Niu +3
Visual simultaneous localization and mapping (SLAM) systems face challenges in detecting loop closure under the circumstance of large viewpoint changes. In this paper, we present a…
Optimally Controllable Perceptual Lossy Compression
Zeyu Yan, Fei Wen, Peilin Liu
Recent studies in lossy compression show that distortion and perceptual quality are at odds with each other, which put forward the tradeoff between distortion and perception (D-P).…
Skeleton Sequence and RGB Frame Based Multi-Modality Feature Fusion Network for Action Recognition
Xiaoguang Zhu, Ye Zhu, Haoyu Wang +3
Action recognition has been a heated topic in computer vision for its wide application in vision systems. Previous approaches achieve improvement by fusing the modalities of the sk…
Masks Fusion with Multi-Target Learning For Speech Enhancement
Liangchen Zhou, Wenbin Jiang, Jingyan Xu +2
Recently, deep neural network (DNN) based time-frequency (T-F) mask estimation has shown remarkable effectiveness for speech enhancement. Typically, a single T-F mask is first esti…
Optimal Transport for Unsupervised Denoising Learning
Wei Wang, Fei Wen, Zeyu Yan +1
Recently, much progress has been made in unsupervised denoising learning. However, existing methods more or less rely on some assumptions on the signal and/or degradation model, wh…
A life-long SLAM approach using adaptable local maps based on rasterized LIDAR images
Waqas Ali, Peilin Liu, Rendong Ying +1
Most real-time autonomous robot applications require a robot to traverse through a dynamic space for a long time. In some cases, a robot needs to work in the same environment. Such…
On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Framework
Zeyu Yan, Fei Wen, Rendong Ying +2
Lossy compression algorithms are typically designed to achieve the lowest possible distortion at a given bit rate. However, recent studies show that pursuing high perceptual qualit…
6-DOF Feature based LIDAR SLAM using ORB Features from Rasterized Images of 3D LIDAR Point Cloud
Waqas Ali, Peilin Liu, Rendong Ying +1
An accurate and computationally efficient SLAM algorithm is vital for modern autonomous vehicles. To make a lightweight the algorithm, most SLAM systems rely on feature detection f…
A Robust 3D Registration Method via Simultaneous Inlier Identification and Model Estimation
Xianyun Qian, Fei Wen, Peilin Liu
Robust 3D registration is a fundamental problem in computer vision and robotics, where the goal is to estimate the geometric transformation between two sets of measurements in the…
A Simple Local Minimal Intensity Prior and An Improved Algorithm for Blind Image Deblurring
Fei Wen, Rendong Ying, Yipeng Liu +2
Blind image deblurring is a long standing challenging problem in image processing and low-level vision. Recently, sophisticated priors such as dark channel prior, extreme channel p…
Matrix Completion via Nonconvex Regularization: Convergence of the Proximal Gradient Algorithm
Fei Wen, Rendong Ying, Peilin Liu +1
Matrix completion has attracted much interest in the past decade in machine learning and computer vision. For low-rank promotion in matrix completion, the nuclear norm penalty is c…
3DTI-Net: Learn Inner Transform Invariant 3D Geometry Features using Dynamic GCN
Guanghua Pan, Jun Wang, Rendong Ying +1
Deep learning on point clouds has made a lot of progress recently. Many point cloud dedicated deep learning frameworks, such as PointNet and PointNet++, have shown advantages in ac…
StreamBox-TZ: Secure Stream Analytics at the Edge with TrustZone
Heejin Park, Shuang Zhai, Long Lu +1
While it is compelling to process large streams of IoT data on the cloud edge, doing so exposes the data to a sophisticated, vulnerable software stack on the edge and hence securit…
Efficient Outlier Removal in Large Scale Global Structure-from-Motion
Fei Wen, Danping Zou, Rendong Ying +1
This work addresses the outlier removal problem in large-scale global structure-from-motion. In such applications, global outlier removal is very useful to mitigate the deteriorati…
Benefit of Joint DOA and Delay Estimation with Application to Indoor Localization in WiFi and 5G
Fei Wen, Peilin Liu, Haichao Wei +1
Accurate indoor localization has long been a challenging problem due to the presence of multipath. Joint direction-of-arrival (DOA) and time delay (TD) estimation is a promising te…
Efficient and Robust Recovery of Sparse Signal and Image Using Generalized Nonconvex Regularization
Fei Wen, Yuan Yang, Ling Pei +2
This work addresses the robust reconstruction problem of a sparse signal from compressed measurements. We propose a robust formulation for sparse reconstruction which employs the $…
Nonconvex Regularization Based Sparse Recovery and Demixing with Application to Color Image Inpainting
Fei Wen, Lasith Adhikari, Ling Pei +3
This work addresses the recovery and demixing problem of signals that are sparse in some general dictionary. Involved applications include source separation, image inpainting, supe…
Dynamic Magnetometer Calibration and Alignment to Inertial Sensors by Kalman Filtering
Yuanxin Wu, Danping Zou, Peilin Liu +1
Magnetometer and inertial sensors are widely used for orientation estimation. Magnetometer usage is often troublesome, as it is prone to be interfered by onboard or ambient magneti…
Positive Definite Estimation of Large Covariance Matrix Using Generalized Nonconvex Penalties
Fei Wen, Yuan Yang, Peilin Liu +1
This work addresses the issue of large covariance matrix estimation in high-dimensional statistical analysis. Recently, improved iterative algorithms with positive-definite guarant…
Efficient Minimization Algorithms for Compressive Sensing Based on Proximity Operator
Fei Wen, Yuan Yang, Peilin Liu +2
This paper considers solving the unconstrained -norm () regularized least squares (-LS) problem for recovering sparse signals in compressive sensing. We…
Distributed Compressed Sensing off the Grid
Zhenqi Lu, Rendong Ying, Sumxin Jiang +2
This letter investigates the joint recovery of a frequency-sparse signal ensemble sharing a common frequency-sparse component from the collection of their compressed measurements.…
Spectral Compressive Sensing with Model Selection
Zhenqi Lu, Rendong Ying, Sumxin Jiang +3
The performance of existing approaches to the recovery of frequency-sparse signals from compressed measurements is limited by the coherence of required sparsity dictionaries and th…