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Innovative Volumetric Capture and Editing Tools for Ubiquitous Storytelling

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

D4.4 Creative XR Productions and Evaluation Report 2 (si apre in una nuova finestra)

We will perform final experimental XR productions to evaluate the final achievements of the INVICTUS project

D1.1 Report on architecture for volumetric motion capture, tracking, and database generation (si apre in una nuova finestra)

Workpackage 1 addresses the development of algorithms necessary to create interactive representations of volumetric content This deliverable specifies the architecture of software components for the processing pipeline This includes algorithms for geometry reconstruction temporal registration automatic rigging animation and hybrid content creation

D3.1 Collaborative VR scene editing tool (si apre in una nuova finestra)

Report on the implemented features of the Collaborative VR scene editing tool typically Scene Layout Lighting and cinematography

D5.1 First Plan for the Exploitation and Dissemination of the Results (si apre in una nuova finestra)

A detailed report presenting a first plan for the dissemination and exploitation of the results within a the different scientific communities and b the targeted industries specified within the INVICTUS project ie VFX CG and animation and interactive industries

D5.3 Final Plan for the Exploitation and Dissemination of the Results (si apre in una nuova finestra)

A final report presenting a detailed plan for the dissemination of the results within a the different scientific communities and b the targeted industries specified within the project ie VFX CG and animation and interactive industries In addition to that the report will contain a strategy for commercializing the knowledge that was generated within the project in alignment with the exploitation plan driven by the Innovation Board and will include a the management of IPR issues b ownership of the results and c licencing of the scientific outcomes

D5.2 Communication material to promote the project's results (si apre in una nuova finestra)

A report presenting the communication material prepared for promoting the projects results including a projects website design and content description b official project templates c enewsletters d social media channels e press releases e project film content 35 minutes long subcontracted

D4.3 Creative XR Productions and Evaluation Report 1 (si apre in una nuova finestra)

We will carry a first experimental XR production to evaluate the first iteration of the achievements of the INVICTUS project

D1.2 First software package for animatable volumetric video generation (si apre in una nuova finestra)

This deliverables provides first software components for the creation of interactive volumetric content together with a description of implemented algorithms THis includes modules for reconstruction registration and animation With these components first demonstration of volumetric video that can be animated and modified will be showcased

D4.2 Evaluation Plan (si apre in una nuova finestra)

We will have two XR productions to evaluate the achievements of this project This document is the Evaluation Plan of those XR productions We will make sure to design the best scenario to cover all the achievement off the different work packages

D2.3 First Motion adaptation and style transfer (si apre in una nuova finestra)

This first demonstrator will display the implementation of morphology-and-style character adaptation applied to volumetric motion-captured data. Typically we will show how characteristics of the motions need to be adapted to match the morphology and style of the given character (e.g. heaviness, strength, “cartoon animation style” motions, etc.).

D3.3 Volumetric spatio-temporal avatar manipulators (si apre in una nuova finestra)

Demonstration of dedicated features for re-animating volumetric motion captured data by extending spatio-temporal animators to specifics of volumetric motion.

D2.6 Final Motion adaptation and style transfer (si apre in una nuova finestra)

This final demonstrator will display the implementation of morphology-and-style character adaptation applied to volumetric motion-captured data. Typically we will show how characteristics of the motions need to be adapted to match the morphology and style of the given character (e.g. heaviness, strength, “cartoon animation style” motions, etc.).

Pubblicazioni

Preserving Memories of Contemporary Witnesses Using Volumetric Video (si apre in una nuova finestra)

Autori: Oliver Schreer, Markus Worchel, Rodrigo Diaz, Sylvain Renault, Wieland Morgenstern, Ingo Feldmann, Marcus Zepp, Anna Hilsmann, Peter Eisert
Pubblicato in: Journal of Interactive Media, Numero Volume 21 Numero 1, 2022, Pagina/e 71-82, ISSN 2196-6826
Editore: Oldenbourg Wissenschaftsverlag
DOI: 10.1515/icom-2022-0015

Imposing Temporal Consistency on Deep Monocular Body Shape and Pose Estimation (si apre in una nuova finestra)

Autori: A. Zimmer, A. Hilsmann, W. Morgenstern, P. Eisert
Pubblicato in: Comp. Visual Media, Numero 9, 2022, Pagina/e 123–139, ISSN 2096-0662
Editore: Tsinghua University Press and Springer
DOI: 10.48550/arxiv.2202.03074

Study on Automatic 3D Facial Caricaturization: from Rules to Deep Learning (si apre in una nuova finestra)

Autori: Nicolas Olivier, Glenn Kerbiriou, Ferran Argelaguet, Quentin Avril, Fabien Danieau, Philippe Guillotel, Ludovic Hoyet and Franck Multon
Pubblicato in: Frontiers in Virtual Reality, 2022, ISSN 2673-4192
Editore: Frontiers in Virtual Reality
DOI: 10.3389/frvir.2021.785104

Example-Based Facial Animation of Virtual Reality Avatars using Auto-Regressive Neural Networks (si apre in una nuova finestra)

Autori: Wolfgang Paier, Anna Hilsmann, Peter Eisert
Pubblicato in: IEEE Computer Graphics and Applications, 2021, Pagina/e 1-1, ISSN 0272-1716
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/mcg.2021.3068035

FaceTuneGAN: Face Autoencoder for Convolutional Expression Transfer Using Neural Generative Adversarial Networks (si apre in una nuova finestra)

Autori: N. Olivier, K. Baert, F. Danieau, F. Multon, Q. Avril
Pubblicato in: Computers & Graphics Volume, Numero 110, 2022, Pagina/e Pages 69-85, ISSN 0097-8493
Editore: Pergamon Press Ltd.
DOI: 10.48550/arxiv.2112.00532

Neural Face Models for Example-Based Visual Speech Synthesis (si apre in una nuova finestra)

Autori: Wolfgang Paier, Anna Hilsmann, Peter Eisert
Pubblicato in: European Conference on Visual Media Production, 2020, Pagina/e 1-10, ISBN 9781450381987
Editore: ACM
DOI: 10.1145/3429341.3429356

Temporal Shape Transfer Network for 3D Human Motion

Autori: J. Regateiro and E. Boyer
Pubblicato in: International Conference on 3D Vision (3DV), 2022
Editore: 3DV2022

Smart Motion Trails for Animating in VR

Autori: J-B. Bordier, A. Mirabile, R. Courant, M. Christie
Pubblicato in: IEEE Conference on AIVR 2022, 2022, ISBN 978-1-6654-5725-5
Editore: IEEE

Recovering Fine Details for Neural Implicit Surface Reconstruction (si apre in una nuova finestra)

Autori: D. Chen, P. Zhang, I. Feldmann, O. Schreer, P. Eisert
Pubblicato in: IEEE/CVF Winter Conference on Applications of Computer Vision, 2023
Editore: IEEE
DOI: 10.48550/arxiv.2211.11320

Model-Based Deep Portrait Relighting (si apre in una nuova finestra)

Autori: F. Schreiber, A. Hilsmann, P. Eisert
Pubblicato in: European Conference on Visual Media Production, 2022
Editore: ACM
DOI: 10.1145/3565516.3565526

Detailed Eye Region Capture and Animation (si apre in una nuova finestra)

Autori: G. Kerbiriou, M. Marchal, Q. Avril
Pubblicato in: CM SIGGRAPH / Eurographics Symposium on Computer Animation 2022, Numero Volume 41 (2022), Number 8, 2022
Editore: The Eurographics Association and John Wiley & Sons Ltd.
DOI: 10.1111/cgf.14642

Neural Human Deformation Transfer (si apre in una nuova finestra)

Autori: Basset, Jean; Boukhayma, Adnane; Wuhrer, Stefanie; Multon, Franck; Boyer, Edmond
Pubblicato in: 3DV 2021 - 9th International Conference on 3D Vision, Dec 2021, London (on line event), United Kingdom., 2021, Pagina/e pp.1-12
Editore: IEEE
DOI: 10.1109/3dv53792.2021.00064

Multi-View Mesh Reconstruction with Neural Deferred Shading (si apre in una nuova finestra)

Autori: M. Worchel, R. Diaz, W. Hu, O. Schreer, I. Feldmann, P. Eisert
Pubblicato in: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, ISBN 978-1-6654-6946-3
Editore: IEEE
DOI: 10.1109/cvpr52688.2022.00609

Measuring the benefits of VR animation tools over traditional interfaces

Autori: Jean-Baptiste Bordier, Anthony Mirabile, Robin Courant, Marc Christie
Pubblicato in: ACM Motion in Games, 2022
Editore: ACM Motion in Games

Volograms & V-SENSE Volumetric Video Dataset (si apre in una nuova finestra)

Autori: Pagés, Rafael; Amplianitis, Konstantinos; Ondrej, Jan; Zerman, Emin; Aljosa Smolic
Pubblicato in: 2022
Editore: ResearchGate
DOI: 10.13140/rg.2.2.24235.31529/1

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