activity
20162021
most citedLocality-constrained Spatial Transformer Network for Video Crowd Counting

7 citations · 9 across the 8 of their papers we have counts for

collaborators

19 papers

eess.SP2021

Recovery of Graph Signals from Sign Measurements

Wenwei Liu, Hui Feng, Kaixuan Wang +2

Sampling and interpolation have been extensively studied, in order to reconstruct or estimate the entire graph signal from the signal values on a subset of vertexes, of which most…

cs.LG2021

Regularized Recovery by Multi-order Partial Hypergraph Total Variation

Ruyuan Qu, Jiaqi He, Hui Feng +2

Capturing complex high-order interactions among data is an important task in many scenarios. A common way to model high-order interactions is to use hypergraphs whose topology can…

cs.IT2021

Performance Analysis for Correlated AoI and Energy Efficiency in Heterogeneous CR-IoT System

Xiaoyu Hao, Tao Yang, Yulin Hu +1

We consider a cognitive radio based Internet of Things (CR-IoT) system where the secondary IoT device (SD) accesses the licensed channel during the transmission vacancies of the pr…

cs.IT2020

Two-Timescale Resource Allocation for Cooperative D2D Communication: A Matching Game Approach

Yiling Yuan, Tao Yang, Yulin Hu +2

In this paper, we consider a cooperative device-todevice (D2D) communication system, where the D2D transmitters (DTs) act as relays to assist the densified cellular network users (…

eess.SP2020

Sampling Policy Design for Tracking Time-Varying Graph Signals with Adaptive Budget Allocation

Xuan Xie, Hui Feng, Bo Hu

There have been many works that focus on the sampling set design for a static graph signal, but few for time-varying graph signals (GS). In this paper, we concentrate on how to sel…

eess.IV2019

Fast Color-guided Depth Denoising for RGB-D Images by Graph Filtering

Qiwei Huang, Ruikang Li, Zidong Jiang +4

Depth images captured by off-the-shelf RGB-D cameras suffer from much stronger noise than color images. In this paper, we propose a method to denoise the depth images in RGB-D imag…