Convex Optimization in Computer Graphics

Simple item page
dc.contributor.authorMattos Da Silva, Leticia
dc.date.accessioned2026-04-22T08:21:04Z
dc.date.available2026-04-22T08:21:04Z
dc.date.issued2026
dc.description.abstractA number of tasks in computer graphics can be conceived as critical point conditions for an optimization problem. These optimization problems, however, often involve nonlinear or nonconvex formulations that cannot be solved easily with standard tools. In this course, we will go over how convex relaxation techniques can make solving these optimization problems more efficient. In particular, we will explore how convex optimization is used to solve for shape matching, contour models, geodesic distances, PDEs, and optimal transport tasks in computer graphics. We will also cover modern convex optimization software tools. The goal of the course is to equip students with a beginner’s toolkit to apply convex optimization strategies to problems that they might encounter in their own research. All course materials will be available at https://convex-optimization-graphics.github.io/.
dc.description.sectionheadersTutorials
dc.description.seriesinformationEurographics 2026 - Tutorials
dc.identifier.doi10.2312/egt.20261005
dc.identifier.isbn978-3-03868-267-7
dc.identifier.issn1017-4656
dc.identifier.pages4 pages
dc.identifier.urihttps://doi.org/10.2312/egt.20261005
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/egt20261005
dc.publisherThe Eurographics Association
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectComputer graphics
dc.subjectConvex optimization
dc.subjectSolvers
dc.titleConvex Optimization in Computer Graphics
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
egt20261005.pdf
Size:
303.73 KB
Format:
Adobe Portable Document Format
Download
Collections
EG 2026 - Tutorials