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Interactive Video Stylization Using Few-Shot Patch-Based Training

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00341658" target="_blank" >RIV/68407700:21230/20:00341658 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1145/3386569.3392453" target="_blank" >https://doi.org/10.1145/3386569.3392453</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1145/3386569.3392453" target="_blank" >10.1145/3386569.3392453</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Interactive Video Stylization Using Few-Shot Patch-Based Training

  • Original language description

    We present a learning-based method to the keyframe-based video stylization that allows an artist to propagate the style from a few selected keyframes to the rest of the sequence. Its key advantage is that the resulting stylization is semantically meaningful, i.e., specific parts of moving objects are stylized according to the artist’s intention. In contrast to previous style transfer techniques, our approach does not require any lengthy pre-training process nor a large training dataset. We demonstrate how to train an appearance translation network from scratch using only a few stylized exemplars while implicitly preserving temporal consistency. This leads to a video stylization framework that supports real-time inference, parallel processing, and random access to an arbitrary output frame. It can also merge the content from multiple keyframes without the need to perform an explicit blending operation. We demonstrate its practical utility in various interactive scenarios, where the user paints over a selected keyframe and sees her style transferred to an existing recorded sequence or a live video stream.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

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

Result continuities

  • Project

    <a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>

  • Continuities

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

Others

  • Publication year

    2020

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    ACM Transactions on Graphics (TOG)

  • ISSN

    0730-0301

  • e-ISSN

    1557-7368

  • Volume of the periodical

    39

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    11

  • Pages from-to

  • UT code for WoS article

    000583700300046

  • EID of the result in the Scopus database

    2-s2.0-85088243439