Deng Yu

Dr. Deng Yu


Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 June 2018 in Neurocomputing
Verified
Journal Article
Closed access
DYDeng Yu
Deng Yu
YLYujie Liu
Yujie Liu
YPYunping Pang
Yunping Pang
ZLZongmin Li
Zongmin Li
HLHua Li
Hua Li

26 March 2018 in The Visual Computer
Verified
Journal Article
Closed access
PDF file
YLYujie Liu
Yujie Liu
DYDeng Yu
Deng Yu
XCXiaoming Chen
Xiaoming Chen
ZLZongmin Li
Zongmin Li
JFJianping Fan
Jianping Fan

1 May 2021 in IEEE Transactions on Circuits and Systems for Video Technology
Verified
Journal Article
Closed access
DYDeng Yu
Deng Yu
LLLei Li
Lei Li
YZYouyi Zheng
Youyi Zheng
MLManfred Lau
Manfred Lau
YSYi-Zhe Song
Yi-Zhe Song
HFHongbo Fu
Hongbo Fu

25 December 2023 in IEEE Transactions on Visualization and Computer Graphics
Verified
Journal Article
Closed access
DYDeng Yu
Deng Yu
MLManfred Lau
Manfred Lau
LGLin Gao
Lin Gao
HFHongbo Fu
Hongbo Fu
We present a novel freehand sketch beautification method, which takes as input a freely drawn sketch of a man-made object and automatically beautifies it both geometrically and structurally. Beautifying a sketch is challenging because of its highly abstract and heavily diverse drawing manner. Existing methods are usually confined to their limited training samples and thus cannot beautify freely drawn sketches with both geometric and structural variations. To address this challenge, we adopt a divide-and-combine strategy. Specifically, we first parse an input sketch into semantic components, beautify individual components by a learned part beautification module based on part-level implicit manifolds, and then reassemble the beautified components through a structure beautification module. With this strategy, our method can go beyond the training samples and handle novel freehand sketches. We demonstrate the effectiveness of our system with extensive experiments and a perceptual study.

13 December 2023 in IEEE Transactions on Visualization and Computer Graphics
Verified
Journal Article
Closed access
DYDeng Yu
Deng Yu
CXChufeng Xiao
Chufeng Xiao
MLManfred Lau
Manfred Lau
HFHongbo Fu
Hongbo Fu
In the process of product design and digital fabrication, the structural analysis of a designed prototype is a fundamental and essential step. However, such a step is usually invisible or inaccessible to designers at the early sketching phase. This limits the user's ability to consider a shape's physical properties and structural soundness. To bridge this gap, we introduce a novel approach Sketch2Stress that allows users to perform structural analysis of desired objects at the sketching stage. This method takes as input a 2D freehand sketch and one or multiple locations of user-assigned external forces. With the specially-designed two-branch generative-adversarial framework, it automatically predicts a normal map and a corresponding structural stress map distributed over the user-sketched underlying object. In this way, our method empowers designers to easily examine the stress sustained everywhere and identify potential problematic regions of their sketched object. Furthermore, combined with the predicted normal map, users are able to conduct a region- wise structural analysis efficiently by aggregating the stress effects of multiple forces in the same direction. Finally, we demonstrate the effectiveness and practicality of our system with extensive experiments and user studies.

27 October 2025
Verified
Conference Paper
Open access
Zheyun QinZheyun Qin
Zheyun Qin
DYDeng Yu
Deng Yu
YSYang Shi
Yang Shi
QWQiangchang Wang
Qiangchang Wang
ZCZhumin Chen
Zhumin Chen