FaceBlit: Instant Real-time Example-based Style Transfer to Facial Videos

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00349942" target="_blank" >RIV/68407700:21230/21:00349942 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1145/3451270" target="_blank" >https://doi.org/10.1145/3451270</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3451270" target="_blank" >10.1145/3451270</a>

Jazyk výsledku

angličtina

Název v původním jazyce

FaceBlit: Instant Real-time Example-based Style Transfer to Facial Videos

Popis výsledku v původním jazyce

We present FaceBlit—a system for real-time example-based face video stylization that retains textural details of the style in a semantically meaningful manner, i.e., strokes used to depict specific features in the style are present at the appropriate locations in the target image. As compared to previous techniques, our system preserves the identity of the target subject and runs in real-time without the need for large datasets nor lengthy training phase. To achieve this, we modify the existing face stylization pipeline of Fišer et al. [2017] so that it can quickly generate a set of guiding channels that handle identity preservation of the target subject while are still compatible with a faster variant of patch-based synthesis algorithm of Sýkora et al. [2019]. Thanks to these improvements we demonstrate a first face stylization pipeline that can instantly transfer artistic style from a single portrait to the target video at interactive rates even on mobile devices.

Název v anglickém jazyce

FaceBlit: Instant Real-time Example-based Style Transfer to Facial Videos

Popis výsledku anglicky

We present FaceBlit—a system for real-time example-based face video stylization that retains textural details of the style in a semantically meaningful manner, i.e., strokes used to depict specific features in the style are present at the appropriate locations in the target image. As compared to previous techniques, our system preserves the identity of the target subject and runs in real-time without the need for large datasets nor lengthy training phase. To achieve this, we modify the existing face stylization pipeline of Fišer et al. [2017] so that it can quickly generate a set of guiding channels that handle identity preservation of the target subject while are still compatible with a faster variant of patch-based synthesis algorithm of Sýkora et al. [2019]. Thanks to these improvements we demonstrate a first face stylization pipeline that can instantly transfer artistic style from a single portrait to the target video at interactive rates even on mobile devices.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Výzkumné centrum informatiky</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Proceedings of the ACM on Computer Graphics and Interactive Techniques

ISSN

2577-6193

e-ISSN

—

Svazek periodika

4

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

17

Strana od-do

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Kód UT WoS článku

000691057800015

EID výsledku v databázi Scopus

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