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Zi-Ye Zhou

dblp:165/9759 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
2 papers
Geometric modeling and processing · 64% Computational photography and imaging · 28% Visual content generation and editing · 8%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational photography and imaging › light field imaging
light field editing
0.312017
PlenoPatch: Patch-Based Plenoptic Image Manipulation · IEEE Trans. Vis. Comput. Graph. 2017
Geometric modeling and processing › shape modeling › human modeling
anatomical modeling
0.212015
Computational bodybuilding: anatomically-based modeling of human bodies · ACM Trans. Graph. 2015
Geometric modeling and processing › shape modeling
human body modeling
0.212015
Computational bodybuilding: anatomically-based modeling of human bodies · ACM Trans. Graph. 2015
Geometric modeling and processing › deformation modeling
physics-based deformation
0.212015
Computational bodybuilding: anatomically-based modeling of human bodies · ACM Trans. Graph. 2015
Visual content generation and editing › example-based synthesis
patch-based synthesis
0.112017
PlenoPatch: Patch-Based Plenoptic Image Manipulation · IEEE Trans. Vis. Comput. Graph. 2017

Methods — techniques the papers use, named apart from their topics

patch-based synthesis · 0.3depth layer decomposition · 0.3volumetric discretization · 0.2quasi-statics solver · 0.2projective dynamics · 0.2
YearPublicationVenuePosition
2017 PlenoPatch: Patch-Based Plenoptic Image Manipulation
abstract
Patch-based image synthesis methods have been successfully applied for various editing tasks on still images, videos and stereo pairs. In this work we extend patch-based synthesis to plenoptic images captured by consumer-level lenselet-based devices for interactive, efficient light field editing. In our method the light field is represented as a set of images captured from different viewpoints. We decompose the central view into different depth layers, and present it to the user for specifying the editing goals. Given an editing task, our method performs patch-based image synthesis on all affected layers of the central view, and then propagates the edits to all other views. Interaction is done through a conventional 2D image editing user interface that is familiar to novice users. Our method correctly handles object boundary occlusion with semi-transparency, thus can generate more realistic results than previous methods. We demonstrate compelling results on a wide range of applications such as hole-filling, object reshuffling and resizing, changing object depth, light field upscaling and parallax magnification.
Jue Wang 0001, Eli Shechtman, Zi-Ye Zhou, Jiaxin Shi, Shi-Min Hu 0001
IEEE Trans. Vis. Comput. Graph.4
2015 Computational bodybuilding: anatomically-based modeling of human bodies
abstract
We propose a method to create a wide range of human body shapes from a single input 3D anatomy template. Our approach is inspired by biological processes responsible for human body growth. In particular, we simulate growth of skeletal muscles and subcutaneous fat using physics-based models which combine growth and elasticity. Together with a tool to edit proportions of the bones, our method allows us to achieve a desired shape of the human body by directly controlling hypertrophy (or atrophy) of every muscle and enlargement of fat tissues. We achieve near-interactive run times by utilizing a special quasi-statics solver (Projective Dynamics) and by crafting a volumetric discretization which results in accurate deformations without an excessive number of degrees of freedom. Our system is intuitive to use and the resulting human body models are ready for simulation using existing physics-based animation methods, because we deform not only the surface, but also the entire volumetric model.
Shunsuke Saito, Zi-Ye Zhou, Ladislav Kavan
ACM Trans. Graph.2