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Max Paik

dblp:367/7064 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0000-0003-3599-2161ORCID · reported

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

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

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
1 paper
Computer animation and physical simulation · 50% Geometric modeling and processing · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer animation and physical simulation
contact modeling
0.912025
Geometric Contact Potential · ACM Trans. Graph. 2025
Geometric modeling and processing
shape modeling
0.912025
Geometric Contact Potential · ACM Trans. Graph. 2025

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

incremental potential contact · 0.9discretization · 0.9continuum potential derivation · 0.9
YearPublicationVenuePosition
2025 Geometric Contact Potential
abstract
Barrier potentials gained popularity as a means for robust contact handling in physical modeling and for modeling self-avoiding shapes. The key to the success of these approaches is adherence to geometric constraints, i.e., avoiding intersections, which are the cause of most robustness problems in complex deformation simulation with contact. However, existing barrier-potential methods may lead to spurious forces and imperfect satisfaction of the geometric constraints. They may have strong resolution dependence, requiring careful adaptation of the potential parameters to the object discretizations. We present a systematic derivation of a continuum potential defined for smooth and piecewise smooth surfaces, starting from identifying a set of natural requirements for contact potentials, including the barrier property, locality, differentiable dependence on shape, and absence of forces in rest configurations. Our potential is formulated independently of surface discretization and addresses the shortcomings of existing potential-based methods while retaining their advantages. We present a discretization of our potential that is a drop-in replacement for the potential used in the incremental potential contact formulation [Li et al. 2020], and compare its behavior to other potential formulations, demonstrating that it has the expected behavior. The presented formulation connects existing barrier approaches, as all recent existing methods can be viewed as a variation of the presented potential, and lays a foundation for developing alternative (e.g., higher-order) versions.
Zizhou Huang, Max Paik, Zachary Ferguson, Daniele Panozzo, Denis Zorin
ACM Trans. Graph.2