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Valentin Vasiliu

dblp:255/8213 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2019
—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-authorHuman-computer interaction and ubiquitous computing · 1 · 1 first-author

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
Rendering · 44% Visual content generation and editing · 44% Virtual and augmented reality · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Rendering › physically based rendering › wave optics rendering
coherent rendering
0.412019
Coherent Rendering of Virtual Smile Previews with Fast Neural Style Transfer · ISMAR 2019
Visual content generation and editing › style transfer
neural style transfer
0.412019
Coherent Rendering of Virtual Smile Previews with Fast Neural Style Transfer · ISMAR 2019

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

temporal consistency · 0.4neural style transfer · 0.4autoencoder · 0.4
YearPublicationVenuePosition
2019 Coherent Rendering of Virtual Smile Previews with Fast Neural Style Transfer
abstract
Coherent rendering in augmented reality deals with synthesizing virtual content that seamlessly blends in with the real content. Unfortunately, capturing or modeling every real aspect in the virtual rendering process is often unfeasible or too expensive. We present a post-processing method that improves the look of rendered overlays in a dental virtual try-on application. We combine the original frame and the default rendered frame in an autoencoder neural network in order to obtain a more natural output, inspired by artistic style transfer research. Specifically, we apply the original frame as style on the rendered frame as content, repeating the process with each new pair of frames. Our method requires only a single forward pass, our shallow architecture ensures fast execution, and our internal feedback loop inherently enforces temporal consistency.
Valentin Vasiliu, Gábor Sörös
ISMAR1