activity
20162022
most citedFast Color-guided Depth Denoising for RGB-D Images by Graph Filtering

7 citations · 22 across the 21 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

eess.IV2019★ 7 cited

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…

eess.SP2019★ 1 cited

Bayesian Design of Sampling Set for Bandlimited Graph Signals

Xuan Xie, Junhao Yu, Hui Feng +1

The design of sampling set (DoS) for bandlimited graph signals (GS) has been extensively studied in recent years, but few of them exploit the benefits of the stochastic prior of GS…

eess.SP2019★ 1 cited

On Critical Sampling of Time-Vertex Graph Signals

Junhao Yu, Xuan Xie, Hui Feng +1

Joint time-vertex graph signals are pervasive in real-world. This paper focuses on the fundamental problem of sampling and reconstruction of joint time-vertex graph signals. We pro…

cs.CV2019★ 7 cited

Locality-constrained Spatial Transformer Network for Video Crowd Counting

Yanyan Fang, Biyun Zhan, Wandi Cai +2

Compared with single image based crowd counting, video provides the spatial-temporal information of the crowd that would help improve the robustness of crowd counting. But translat…

cs.IT2019

Learning for Matching Game in Cooperative D2D Communication with Incomplete Information

Yiling Yuan, Tao Yang, Hui Feng +1

This paper considers a cooperative device-to-device (D2D) communication system, where the D2D transmitters (DTs) act as relays to assist cellular users (CUs) in exchange for the op…

eess.SP2019★ 1 cited

Active Sampling for Approximately Bandlimited Graph Signals

Sijie Lin, Xuan Xie, Hui Feng +1

This paper investigates the active sampling for estimation of approximately bandlimited graph signals. With the assistance of a graph filter, an approximately bandlimited graph sig…