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PRODID:-//SGP 2026//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:SGP 2026
NAME:SGP 2026
BEGIN:VTIMEZONE
TZID:Europe/Zurich
BEGIN:DAYLIGHT
DTSTART:19810329T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
TZNAME:GMT+2
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
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BEGIN:STANDARD
DTSTART:19961027T030000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
TZNAME:GMT+1
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
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END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260702T093000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260702T103000
SUMMARY:Keynote: Computational Optimal Transport: From Low to High Dimension and Back
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Speaker: Justin Solomon\n\nThe *optimal transport* problem asks a simple geometric question:  What is the most efficient way to transform one probability distribution into another along a piece of geometry?  Beyond its mathematical interest\, optimal transport underlies a variety of applications\, from supply chains to mesh processing\, statistics\, and even generative AI.  Over the past two decades\, research in geometry processing has played a central role in shaping algorithms for optimal transport\, with foundational advances emerging from the SGP community.  At the same time\, popular problems in applied optimal transport have shifted from low-dimensional settings in graphics and imaging to high-dimensional settings in machine learning.\n\nIn this retrospective keynote\, I will trace how my team's work in computational optimal transport was shaped by studying its applications to geometry processing---even as the landscape of research in this area shifted in dimensionality and application.  Ultimately\, this journey illustrates the broader value of "Geometric Data Processing" as a discipline: identifying shared geometric and variational principles across domains that differ dramatically in dimension\, scale\, and data fidelity.\n
UID:computational-optimal-transport-20260702T093000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#computational-optimal-transport
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260701T093000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260701T103000
SUMMARY:Keynote: Geometric not-so-deep learning
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Speaker: Julie Digne\n\nOver the past decade\, deep learning for geometric data processing has advanced significantly\, with numerous methods proposed to handle irregular\, non-Euclidean data. However\, 3D objects databases are scarce and only partially cover the variety of shapes practitioners want to analyze. As a consequence many shapes fall out-of-distribution. \nHowever\, many tasks\, such as compression\, denoising or resampling\, can already benefit from leveraging statistical geometric features\, without requiring shape space priors.\nIn this talk\, I will focus on lightweight methods that are computationally efficient\, run on standard hardware by operating directly on individual shapes. Through a series of projects\, I will show how modern optimization techniques\, with or without neural networks\, can address geometric challenges effectively\, without relying on large datasets or heavy computational resources.\n
UID:geometric-not-so-deep-learning-20260701T093000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#geometric-not-so-deep-learning
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260703T093000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260703T103000
SUMMARY:Keynote: Resource-Efficient Visual Computing – Frontiers and Applications of Real-Time Visual AI
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Speaker: Bernhard Kerbl\n\nModern visual computing is transforming the means and ways by which we map\, understand and interact with the physical world. 3D and 4D reconstructions of real artefacts are now viable from just a handful of casual camera observations\; object recognition and classification can be done with unprecedented accuracy and reliability. However\, a key requirement for the overall usefulness of these methods is their efficiency: Efficiency dictates whether a solution can run in real-time\; it governs the hardware requirements for execution\, and wether it can be used without requiring massive\, industry-grade infrastructure. Real-time performance enables crucial emerging trends\, such as robots interacting with the real world\, or visual AI providing on-line assistance in medical treatments on patients. Resource-efficiency\, on the other hand\, ensures that these breakthrough technologies can be employed by almost anyone. In this talk\, Dr. Kerbl will discuss key challenges and opportunities of real-time\, resource-efficient visual computing and AI\, focusing on open tasks in fundamental research and applied fields\, including biomedicine and robotics.\n
UID:resource-efficient-visual-computing-20260703T093000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#resource-efficient-visual-computing
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260630T090000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260630T103000
SUMMARY:Directional Fields
LOCATION:Room 201\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Speaker: Amir Vaxman\n\nI will discuss classic and state-of-the-art methods to design directional fields on discrete surfaces\, with applications to meshing\, solving PDEs\, and visualization.\n
UID:directional-fields-20260630T090000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#directional-fields
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260630T110000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260630T123000
SUMMARY:Differentiable Geometry Processing in Python
LOCATION:Room 201\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Speakers: Ana Dodik\, Ahmed Mahmoud\n\nInverse problems have a long history in computer graphics with applications ranging from fabrication to computer vision. While existing software packages such as Taichi\, Mitsuba\, Warp\, and PyTorch3D focus primarily on differentiating through simulations of physical systems such as elasticity or light transport\, differentiating through geometry processing algorithms is relatively underexplored. Existing geometry-processing-focused libraries for gradient computation (e.g.\, TinyAD) have poor operability with machine learning frameworks and no GPU support\, limiting their practicality. This course explores how PyTorch\, with its automatic differentiation and GPU acceleration capabilities\, can be leveraged for differentiable geometry processing. We begin with the fundamentals of PyTorch\, covering its computational model and automatic differentiation mechanisms\, before introducing key optimization techniques for geometric data\, focusing on meshes and other common representations. The course will include real-world applications of these concepts such as mesh smoothing and parameterization\, meta-optimization\, as well as machine-learning workflows. By the end of the session\, attendees will have a practical understanding of how to integrate PyTorch into their own differentiable geometry processing workflows.\n
UID:differentiable-geometry-processing-in-python-20260630T110000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#differentiable-geometry-processing-in-python
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260629T160000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260629T173000
SUMMARY:Geometry Processing from 2D Image Priors
LOCATION:Room 201\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Speakers: Dale Decatur\, Richard Liu\, Nam Anh Dinh\n\n2D foundation models have exploded in popularity in recent years. While text-to-image generative models\, image feature encoders\, and VLMs (vision-language models) are widely used in 2D contexts such as image processing\, they also facilitate numerous applications to traditionally 3D domains such as robotics\, self-driving\, and 3D generation. This course explores how 3D understanding can emerge from 2D priors\, and how we can leverage these priors towards tasks in geometry processing. We summarize the literature on lifting 2D supervision to 3D tasks\, covering both optimization and back projection methods. In doing so\, we address common challenges in this field and discuss several applications: stylization\, localization\, and deformation.\n
UID:geometry-processing-from-2d-image-priors-20260629T160000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#geometry-processing-from-2d-image-priors
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260629T090000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260629T103000
SUMMARY:Shape Spaces
LOCATION:Room 201\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Speakers: Josua Sassen\, Florine Hartwig\n\nIn applications such as animation or shape analysis\, we are interested in processing multiple shapes at once and\, hence\, in a mathematical model for collections of shapes yielding flexible numerical tools.\n[1] proposed to consider Riemannian shape spaces in this context\, i.e. possibly infinite-dimensional Riemannian manifolds where points are geometric objects such as surfaces. These (Riemannian) shape spaces have found usage in a lot of areas of applied mathematical research such as computational anatomy\, computer graphics\, shape optimization\, and image processing.\nIn this course\, we will give an overview of different types of shape spaces interesting for geometry processing and will discuss concrete algorithms resulting from their theory.\n\n[1] Kendall\, David G. "Shape manifolds\, procrustean metrics\, and complex projective spaces." Bulletin of the London mathematical society 16.2 (1984): 81-121.\n
UID:shape-spaces-20260629T090000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#shape-spaces
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260629T140000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260629T153000
SUMMARY:Cone-Nets: Theory and Interactive Design
LOCATION:Room 201\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Speakers: Klara Mundilova\, Michele Vidulis\n\nSheet-material structures provide practical and aesthetic advantages and play an important role across architecture\, design\, and engineering. Consequently\, the development of geometric methods and computational tools for their design remains an active research direction.\n\nThis lecture focuses on cone-nets as a class of surface parameterizations and on their semi-discrete and discrete counterparts\, which form special classes of structures composed of developable strips and regular planar quad meshes\, respectively. We discuss the theoretical framework underlying these structures and present a novel construction method implemented as interactive design tools for Grasshopper / Rhinoceros 3D\, the CNets and C-tubes plugins. These tools enable real-time exploration of the design space with intuitive controls and support form-finding optimization to meet user-specified objectives. \n\nBy the end of the lecture\, attendees will understand the theoretical foundations of cone-nets and be equipped to explore their design space using the presented tools.\n
UID:cone-nets-theory-and-interactive-design-20260629T140000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#cone-nets-theory-and-interactive-design
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260630T160000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260630T173000
SUMMARY:Spatial acceleration structures: Bounding Volume Hierarchies
LOCATION:Room 201\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Speaker: Markus Billeter\n\nSpatial acceleration structures play an important role in many high-performance graphics applications. They enable logarithmic time spatial queries (intersections\, in-range\, ...)\, which is crucial for performance with ever larger data sets. A prominent example is ray tracing\, where they are used to find intersections between view rays and geometry. However\, to get the benefits from a spatial data structure\, one must first obtain such\, an O(N log(N)) process.\n\nThis course provides a practical introduction to spatial acceleration structures. It first introduces different types of spatial data structures\, but then specifically focuses on bounding volume hierarchies (BVHs)\, which are a very common choice. It covers their use -performing spatial queries- and their construction. We will discuss different challenges\, including dynamic data. We will then focus on the practical implementation\, including considerations for GPUs. At the end of the course\, we will have covered the full pipeline: from construction of a BVH to performing spatial queries.\n
UID:spatial-acceleration-structures-bounding-volume-hierarchies-20260630T160000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#spatial-acceleration-structures-bounding-volume-hierarchies
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260630T140000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260630T153000
SUMMARY:Closest Point Geometry Processing
LOCATION:Room 201\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Speaker: Nathan King\n\nObjects can be represented in various forms\, including meshes\, point clouds\, level sets\, and neural implicits. Traditionally\, many algorithms are limited to a single specific representation. This course focuses on geometry processing techniques designed for any representation supporting closest-point queries.\n\nBy requiring only closest points\, these methods become universally applicable across the above representations and more. Furthermore\, objects can be manifold or nonmanifold\, open or closed\, orientable or not\, and of any codimension or even mixed codimension. We provide an introduction to the closest point method (CPM) for solving PDEs and discuss extensions for applications commonly encountered in geometry processing.\n
UID:closest-point-geometry-processing-20260630T140000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#closest-point-geometry-processing
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260629T110000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260629T123000
SUMMARY:Computational Geometric Fluid Mechanics
LOCATION:Room 201\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Speakers: Sina Nabizadeh\, Hesper Yin\n\nModern fluid simulation increasingly relies on geometric formulations. Prominent examples include Lie-advection-based methods that preserve energy and geometric invariants more faithfully than approaches that directly approximate the governing PDEs\, showcasing geometric fluid mechanics as an impactful framework for fluid simulation.\nThis course develops geometric fluid mechanics from first principles. We first introduce the geometric formulation following Arnold’s interpretation of the Euler equations\, in which fluid motion is described as geodesic flow on the infinite-dimensional Riemannian manifold of volume-preserving diffeomorphisms. We present the necessary background\, ranging from Lie groups and variational principles to Lagrangian and Hamiltonian mechanics\, and elucidate the invariant structures that arise from this geometric perspective.\nWe then discuss how smooth geometric structures can be translated into discrete settings\, where fluid motion becomes a constrained geodesic flow on a sub-Riemannian manifold induced by discretization. Finally\, we will analyze modern methods grounded in these principles from computer graphics and computational fluid mechanics.\n
UID:computational-geometric-fluid-mechanics-20260629T110000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#computational-geometric-fluid-mechanics
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260629T083000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260629T090000
SUMMARY:Registration
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:registration-20260629T083000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260630T083000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260630T090000
SUMMARY:Registration
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:registration-20260630T083000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260629T103000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260629T110000
SUMMARY:Coffee break
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:coffee-break-20260629T103000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260629T153000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260629T160000
SUMMARY:Coffee break
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:coffee-break-20260629T153000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260630T103000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260630T110000
SUMMARY:Coffee break
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:coffee-break-20260630T103000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260630T153000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260630T160000
SUMMARY:Coffee break
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:coffee-break-20260630T153000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260701T103000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260701T110000
SUMMARY:Coffee break
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:coffee-break-20260701T103000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260701T153000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260701T160000
SUMMARY:Coffee break
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:coffee-break-20260701T153000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260702T103000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260702T110000
SUMMARY:Coffee break
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:coffee-break-20260702T103000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260702T153000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260702T160000
SUMMARY:Coffee break
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:coffee-break-20260702T153000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260703T103000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260703T110000
SUMMARY:Coffee break
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:coffee-break-20260703T103000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260629T123000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260629T140000
SUMMARY:Lunch
LOCATION:Restaurant "Grosse Schanze"\, Parkterrasse 10\, 3012 Bern
UID:lunch-20260629T123000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260630T123000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260630T140000
SUMMARY:Lunch
LOCATION:Restaurant "Grosse Schanze"\, Parkterrasse 10\, 3012 Bern
UID:lunch-20260630T123000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260701T123000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260701T140000
SUMMARY:Lunch
LOCATION:Restaurant "Grosse Schanze"\, Parkterrasse 10\, 3012 Bern
UID:lunch-20260701T123000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260702T123000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260702T124000
SUMMARY:Group Photo
LOCATION:To be announced
UID:group-photo-20260702T123000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260702T124000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260702T140000
SUMMARY:Lunch
LOCATION:Restaurant "Grosse Schanze"\, Parkterrasse 10\, 3012 Bern
UID:lunch-20260702T124000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260703T123000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260703T140000
SUMMARY:Lunch
LOCATION:Restaurant "Grosse Schanze"\, Parkterrasse 10\, 3012 Bern
UID:lunch-20260703T123000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260701T083000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260701T091500
SUMMARY:Welcome Coffee & Registration
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:welcome-coffee-registration-20260701T083000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260701T091500
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260701T093000
SUMMARY:Opening Session
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
UID:opening-session-20260701T091500@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260702T083000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260702T093000
SUMMARY:Welcome Coffee & Registration
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:welcome-coffee-registration-20260702T083000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260703T083000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260703T093000
SUMMARY:Welcome Coffee & Registration
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:welcome-coffee-registration-20260703T083000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260701T110000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260701T123000
SUMMARY:Geometric Solvers
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Papers:\n- Single Line Drawing Generation via Semantics-Driven Optimization (T. Magne\, A. Binninger\, R. Wiersma\, O. Sorkine-Hornung)\n- Differentiable Randers-Finsler Eikonal Solvers (B. Gahtan\, J. Shpund\, A. M. Bronstein)\n- Surface Multigrid via Global Parametric Domain Simplification (Anyu Zhao\, Qing Fang\, Ligang Liu)\n- Circles of Confidence for Multi-Label Geometry Completion (Z. Wei\, C. Hafner\, A. Kalinov\, P. Heiss Synak\, C. Wojtan)
UID:geometric-solvers-20260701T110000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#geometric-solvers
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260701T140000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260701T153000
SUMMARY:Deformation and Registration
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Papers:\n- As-Rigid-As-Possible Regularization for Implicit Surfaces (T. Djuren\, M. Worchel\, U. Finnendahl\, M. Alexa)\n- On Bending in the As-Rigid-As-Possible Deformation Energy (U. Finnendahl\, M. Alexa)\n- Spatial Eigenanalysis of 2D Deformation Energies (H. Wu\, K. Wu\, T. Kim)\n- Attention Based Optimization for 3D Shape Registration (A. Riva\, L. Olearo\, S. Melzi)
UID:deformation-and-registration-20260701T140000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#deformation-and-registration
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260701T160000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260701T170000
SUMMARY:Industry Session
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
UID:industry-session-20260701T160000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260701T170000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260701T172000
SUMMARY:Poster fast forward
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Papers:\n- TiGL 3.5 – An Open Source Parametric Geometry Library for Virtual Aircraft Design (O. Albers\, S. Goldberg\, J. Kleinert\, A. Reiswich)\n- Exact 3D Elastica for Interactive Geometry Processing and Fabrication-Aware Design (M. Isern)\n- Topology and Combinatorics: Generalization in Deep Learning (J.S. Schmidt\, M. Carrasco\, E. Röell\, G. Wolf\, N. Blaser\, B. Rieck)\n- Learning to Build Shapes by Extrusions (T. Christiansen\, K. Pandey\, A. Reinders\, K. Singh\, M. Hannemose\, J. A. Bærentzen)\n- Neural Field-Based Sequence Planning for Additive-Subtractive Hybrid Manufacturing (S. Guo\, F. Zhong\, L. Wang\, H. Zhao)\n- A Bayesian Approach to Ill-posed Geometric Primitive Fitting from Point Clouds Using Prior Knowledge (P. Schiller\, P. Raumonen\, J. Peltonen\, S. Ali-Löytyy)\n- Geometry-Aware Edge Pooling for Graph Neural Networks (K. Limbeck\, L. Mezrag\, G. Wolf\, B. Rieck)\n- Boundary-Aware Mesh Deformations (F. Protais\, G. Cherchi\, M. Livesu)\n- Stackability of architectural freeform surfaces (A. Chocarro \, K. Gavriil)\n- Generalizable Dynamics Models for Deformable Objects: Tool-Agnostic Model for Tool Geometry Design (N. Cugito\, K. Allen)
UID:posters-20260701T170000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#posters
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260701T172000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260701T190000
SUMMARY:Poster Apéro – Wine & Cheese (Foyer)
LOCATION:Foyer\, Hochschulstrasse 4\, 3012 Bern
UID:posters-20260701T172000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#posters
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260702T110000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260702T123000
SUMMARY:Meshing and Vector Field Processing
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Papers:\n- Surface Quadrilateral Meshing from Integrable Odeco Fields (M. Couplet \, A. Chemin\, D. Bommes \, E. Chien)\n- Meshing Unsigned Distance Fields with Regular Triangulations (M. Kohlbrenner\, M. Alexa)\n- Phong-Rodrigues Extrinsic Vector-Field Processing (H. Liu\, O. Stein\, A. Vaxman\, M. Ben-Chen\, M. Kazhdan)\n- Tangent Blow-Ups for Processing Non-Manifold Geometry (A. Petrov\, M. Nabizadeh\, A. Dodik\, J. Solomon)
UID:meshing-and-vector-field-processing-20260702T110000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#meshing-and-vector-field-processing
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260702T140000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260702T153000
SUMMARY:Distance Fields
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Papers:\n- Strictly Conservative Neural Distance Fields (I. Ludwig\, M. Campen)\n- SDFs from Unoriented Point Clouds using Neural Variational Heat Distances (S. Weidemaier\, F. Hartwig\, J. Sassen\, S. Conti\, M. Ben-Chen\, M. Rumpf)\n- Medial Axis Aware Learning of Signed Distance Functions (S. Weidemaier\, C. Norden-Smoch\, M. Rumpf)\n- Compactly supported detail field for high quality neural implicit surfaces (G. Coiffier\, J. Basselin)
UID:distance-fields-20260702T140000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#distance-fields
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260702T160000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260702T164500
SUMMARY:Hulls
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Papers:\n- Progressive Convex Hull Simplification (A. Jacobson)\n- A practical algorithm for weighted k-hulls (N. Look\, H. Meyer\, M. Alexa)
UID:hulls-20260702T160000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#hulls
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260702T170000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260702T180000
SUMMARY:City Tour
LOCATION:Meeting point: In front of Foyer
UID:city-tour-20260702T170000@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260702T190000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260702T230000
SUMMARY:Conference Dinner
LOCATION:Rooftop Grill\, Kursaal Bern\, Kornhausstrasse 3\, 3013 Bern
UID:conference-dinner-20260702T190000@sgp26.org
URL;VALUE=URI:https://sgp26.org/venue/#social_events
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260703T110000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260703T123000
SUMMARY:Fabrication and Verification
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Papers:\n- Design and analysis of smooth geometry-conforming lattices via Generalized Bézier patches (J. C. Pareja-Corcho \, T. Hirschler \, R. Bouclier \, G. Elber \, M. Barton)\n- Wave-Guided Field-Aligned Volume-Filling Curves (G. Cocco\, X. Chermain)\n- Taking a Moment to Characterize the Bending Response of Thin Sheet Materials (P. Xie\, J. S. Montes Maestre\, S. Coros\, B. Thomaszewski)\n- UniGRe-3D: Unified Geometric Reconstruction for Multi-category 3D Anomaly Detection (D. Han\, Z. Zhang\, Y. Gao\, J. Li\, M. Li\, M. Zhou)
UID:fabrication-and-verification-20260703T110000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#fabrication-and-verification
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260703T140000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260703T144500
SUMMARY:Datasets and Analysis
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
DESCRIPTION:Papers:\n- Arti4D: Statistical Analysis and Modelling of the Spatio-temporal Variability in Articulated 4D Shapes (Z. Li\, A. Amrani\, S. Rai\, H. Laga)\n- MM-CAD: A Multi-Modal CAD Dataset and Benchmark for Cross-Modal Geometric Learning (A. Bharathi\, A. Aravindakshan\, R. Muthuganapathy)
UID:datasets-and-analysis-20260703T140000@sgp26.org
URL;VALUE=URI:https://sgp26.org/program/#datasets-and-analysis
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260703T144500
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260703T153000
SUMMARY:Town Hall Meeting
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
UID:town-hall-meeting-20260703T144500@sgp26.org
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260703T000000Z
DTSTART;TZID=Europe/Zurich:20260703T153000
SEQUENCE:42
DTEND;TZID=Europe/Zurich:20260703T160000
SUMMARY:Awards & Closing
LOCATION:Room 210 / Aula\, Hochschulstrasse 4\, 3012 Bern
UID:awards-closing-20260703T153000@sgp26.org
END:VEVENT
END:VCALENDAR