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Eduardo Rinaldi

dblp:364/4212 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 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
Geometric modeling and processing · 100%
Software engineering, system software, and programming languages
1 paper
Software maintenance and evolution · 100%

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

TopicWeightPapersLastEvidence papers
Geometric modeling and processing
procedural modeling
0.712023
NodeGit: Diffing and Merging Node Graphs · ACM Trans. Graph. 2023
Software maintenance and evolution › software configuration management
version control
0.212023
NodeGit: Diffing and Merging Node Graphs · ACM Trans. Graph. 2023

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

approximate graph edit distance · 1.3
YearPublicationVenuePosition
2023 NodeGit: Diffing and Merging Node Graphs
abstract
The use of version control is pervasive in collaborative software projects. Version control systems are based on two primary operations: diffing two versions to compute the change between them and merging two versions edited concurrently. Recent works provide solutions to diff and merge graphics assets such as images, meshes and scenes. In this work, we present a practical algorithm to diff and merge procedural programs written as node graphs. To obtain more precise diffs, we version the graphs directly rather than their textual representations. Diffing graphs is equivalent to computing the graph edit distance, which is known to be computationally infeasible. Following prior work, we propose an approximate algorithm tailored to our problem domain. We validate the proposed algorithm by applying it both to manual edits and to a large set of randomized modifications of procedural shapes and materials. We compared our method with existing state-of-the-art algorithms, showing that our approach is the only one that reliably detects user edits.
Eduardo Rinaldi, Davide Sforza, Fabio Pellacini
ACM Trans. Graph.1