The 6th ITG/VDE Graduate Summer School on Video Compression and Processing aims at providing a forum for informal knowledge exchange and discussion of innovative research ideas among doctoral students working in the field of image and video communication and image signal processing. The atmosphere of the summer school is intended to be very informal and less restrictive than a typical workshop or conference, thus stimulating discussions and inspiring joint research among the participating PhD students. Topics of interest include but are not limited to:
- Techniques for next generation image and video coding
- Machine learning for image, video and data processing and compression
- Compression algorithms for 2D, 3D, 360-degree and multi-view video and images
- Coding and processing of multispectral data
- Image and video signal analysis
- Quality assessment/Quality of experience
- Virtual, mixed and augmented reality
- Technology for video transmission and networked systems
- Architecture and implementation aspects
Contributions should focus on novel research aspects, but do not have to provide unpublished material. Presentations, posters, or demos should rather give an overview of the participant’s research fields including challenges, open topics, and problems in current research. The aim is to bring together young researchers with similar topics and provide a basis for fruitful scientific discussions, motivating future cooperation.
Machine learning methods for video compression
The basic principle of video compression is to exploit redundancies in the underlying signals. On the other hand, powerful methods in the field of machine learning have been developed to discover hidden patterns in large sets of data. Therefore, a central direction of current research in video compression is to investigate if and how machine-learning methods can be used to improve state of the art video coding technologies. In this lecture, we will describe some recent approaches to this problem in more detail. First, we plan to give an overview on some “end-to-end” compression systems, which aim to completely replace block-based codecs by trained convolutional neural networks. Then, we want to describe some research works that aim to improve only specific building blocks of modern hybrid video codecs like in-loop filtering or prediction.
How to participate
- The summer school is open for PhD and advanced master students, for post docs, and academic advisors working in the research areas listed. The working language at the summer school will be English. Participants are encouraged to present and discuss their research in oral and poster presentations.
- To apply for a presentation, submit your title, a short abstract (approximately 200 words), and preference oral/poster. Upon acceptance, you need to register for the summer school.
- Participants without a presentation are welcome and requested to register.
- See Submission/Registration/Payment and Important Dates for details.
- April 16, 2021 Submission of proposal for presentation (title/abstract)
- April 29, 2021 Notification of acceptance
- May 14, 2021 End of Registration for Summer School
- May 21, 2021 Payment of registration fee (including accommodation)
- July 25-27, 2021 Summer School takes place
Note: If the Event should be canceled due to ongoing restrictions in relation to the Covid-19, the full amount of the registration fee will be reimbursed.
- André Kaup, Friedrich-Alexander-University Erlangen-Nürnberg, Germany
- Jens-Rainer Ohm, RWTH Aachen University, Germany
- Dietmar Saupe, University of Konstanz, Germany
- Ralf Schäfer, Fraunhofer Heinrich Hertz Institute – Berlin, Germany
The summer school will take place at the Fraunhofer Heinrich Hertz Institute`s CINIQ Center and 3IT. The two Centers stand for technology and information transfer in the triangle of innovation, science and economy in Berlin. The facilities offer a unique and stimulating environment for scientific discussions and joint research.
The CINIQ Center is a networking platform and exhibition space for selected research projects and innovations in the field of digital technologies from Germany and promotes exchange and knowledge transfer both nationally and internationally. Currently, it serves as the home of the Forum Digital Technologies which is funded by the German Federal Ministry for Economic Affairs and Energy (BMWi).
The 3IT – Innovation Center for Immersive Imaging Technologies is an event venue and showroom but also a marketing platform and networking nexus. On a regular basis experts come together and exchange their know-how, test and present their innovations, and develop business models and marketing strategies.
Fraunhofer Heinrich Hertz Institute
The number of participants is limited to 40 persons maximum and we have blocked a corresponding number of hotel rooms. Therefore it is recommended to register as early as possible.
All summer school participants will stay at
B&B Hotel Berlin-Tiergarten
Englische Straße 1-4
which is in walking distance to the CINIQ Center.
If you prefer to book your own hotel, please contact us before March 10th.
Lab-Tours & Get-Together
Spree Boat Tour
Participants of the Summer School will be taken on an evening boat tour on the river Spree in Berlin, where they will be treated to a delicious barbecue. The relaxed atmosphere will give them the chance to further exchange ideas after a day of fruitful discussions and to get to know each other even more, while enjoying a beautiful trip through the center of the city.
Date: 26 July
Time: 7pm – 11pm
Location: Caprivibrücke, Berlin
To submit a proposal for a presentation please send an E-mail until 16 April, 2021.
Re: SVCP 2021 – Proposal for presentation
Template for Submission:
Name (last, first): _____________
Title of talk/poster: _____________
Abstract (~200 words): _____________
Preference talk/poster: _____________
The registration has been closed.
- Ralf Schäfer, Fraunhofer Heinrich Hertz Institute, Germany
- Maria Ott, Fraunhofer Heinrich Hertz Institute, Germany
- Marc Reznicek, Fraunhofer Heinrich Hertz Institute, Germany
- Gabriela Thiele, Fraunhofer Heinrich Hertz Institute, Germany