AI-based video compression for emerging technologies

Project Information

AISTREAM

Grant agreement ID: 965502

DOI 10.3030/965502

Project closed

EC signature date 24 November 2020

Start date 1 January 2021

End date 31 December 2022

Funded under

• Horizon 2020 Framework Programme

Total cost € 4 139 897,50

EU contribution € 2 999 928,00

Coordinated by

TECHNISCHE UNIVERSITAET WIEN
Austria

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Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Documents, reports (1)

Open-source License for Container

Opensource license for our AIbased streaming container

Other (1)

Conference Presentations

Deep Render and TU Wien to attend CVPR Conference (or similar) in 2021 and 2022, present in both years.

Publications

Conference proceedings (6)

Impact of Learned Domain Specific Compression on Satellite Image Object Classification

Author(s): Alexander Bayerl, Manuel Keglevic, Matthias Woedlinger, Robert Sablatnig
Published in: Proceedings of the 26th Computer Vision Winter Workshop (CVWW 2023), Issue 26th, 2023
Publisher: CEUR Workshop Proceedings

Learned Lossy Image Compression for Volumetric Medical Data

Author(s): Jan Kotera, Matthias Woedlinger, Manuel Keglevic
Published in: Proceedings of the 26th Computer Vision Winter Workshop (CVWW 2023), Issue 26th, 2023
Publisher: CEUR Workshop Proceedings

Conditional Image Generation with Score-Based Diffusion Models

Author(s): Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
Published in: 2021
Publisher: arXiv (for now, under conference submission)
DOI: 10.48550/arxiv.2111.13606

Perceptually-Guided Lossy Image Compression

Author(s): Alexander Lytchier, Jan Xu, Christopher Finlay, Ciro Cursio, Vira Koshkina, Christian Besenbruch, Arsalan Zafar
Published in: 4th Challenge on Learned Image Compression, 2021, 2021
Publisher: CVPR - CLIC 2021

SASIC: Stereo Image Compression With Latent Shifts and Stereo Attention

Author(s): Wödlinger, Matthias and Kotera, Jan and Xu, Jan and Sablatnig, Robert
Published in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Issue 2022, 2022, Page(s) 661--670
Publisher: IEEE

Three Gaps for Quantisation in Learned Image Compression

Author(s): Shi Pan, Christopher Finlay, Christian Besenbruch, William Knottenbelt
Published in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2021., 2021, Page(s) 720-726
Publisher: CVF - Computer Vision Foundation