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Diego Sagredo

dblp:440/0406 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2026
0009-0006-3082-3456ORCID · reported

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 · 61% Rendering · 30% Computational photography and imaging · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Rendering
inverse rendering
1.012026
Surface Estimation of Translucent Materials: An Application to Fabric Digitization · IEEE Trans. Vis. Comput. Graph. 2026
Geometric modeling and processing
surface reconstruction
1.012026
Surface Estimation of Translucent Materials: An Application to Fabric Digitization · IEEE Trans. Vis. Comput. Graph. 2026
Geometric modeling and processing › 3d reconstruction
volumetric reconstruction
1.012026
Surface Estimation of Translucent Materials: An Application to Fabric Digitization · IEEE Trans. Vis. Comput. Graph. 2026
Computational photography and imaging › image acquisition
image digitization
0.312026
Surface Estimation of Translucent Materials: An Application to Fabric Digitization · IEEE Trans. Vis. Comput. Graph. 2026

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

photometric capture · 1.0inverse rendering · 1.0
YearPublicationVenuePosition
2026 Surface Estimation of Translucent Materials: An Application to Fabric Digitization
abstract
Estimating the surface of translucent objects from photometric data poses significant challenges due to complex internal light scattering. We introduce a novel method that computes a depth map from single-viewpoint photographs of a material sample, captured under multiple illuminations. Our approach leverages inverse rendering to derive a volumetric representation, including density, albedo, and phase function, from which a surface mesh is reconstructed. Beyond validation with synthetic and 3D-printed physical models, we illustrate our technique's power by successfully applying it to the digitization of fabrics, a notoriously difficult material due to its intricate translucent structure. This work advances the state-of-the-art texture stack acquisition via enhanced surface reconstruction.
Diego Sagredo, Javier Fabre, Jorge Lopez-Moreno
IEEE Trans. Vis. Comput. Graph.1