Conference proceedings

The proceedings are now available online, in Springer LNCS 12679 : 


Temporary access to the flash presentations are available here

Call for papers

We invite you to participate in the Eighth International Conference on Scale Space and Variational Methods in Computer Vision (SSVM). The conference will be held in Cabourg, France, from Sunday May 16 evening to Thursday May 20 2021, at the Sweet-Home Hotel


Registration and Attendance

The next SSVM 2021 will take place entirely virtually under zoom.

The conference is free but registration is mandatory before May 9th 2021.

The link and the password to the conference will be sent only to registered participants.


Situation of the pandemic

Update (march 2021): Given the number of uncertainties surrounding the situation of the pandemic, and after much deliberation with the steering committee of SSVM:

** We have decided that SSVM 2021 will take place entirely virtually. **

It is difficult to predict how the current restrictions all across Europe and the world will evolve in May, and our first priority is the safety, health, and well-being of SSVM participants.

Running a virtual conference introduces a few challenges, but we're enthusiastic that we will be able to provide a useful, meaningful, and intellectually stimulating conference experience, and in particular for the poster sessions.

As a consequence, we have also decided that no registration fees will be charged to the registered participants.

So far, we are planning to maintain the SSVM conference live, provided the progress of the outbreak situation continues to improve. However, our first priority is the safety, health, and well-being of SSVM participants.We are closely monitoring the situation through official channels and will provide updates with any developments. If the situation next spring does not improve enough, then we will consider turning the event completely virtual. For participants with health issues and risks, who will have their work accepted but cannot attend, we will also consider possibilities for remote participation. In any event, we would like to encourage the community to submit excellent research work.



Important dates

  • Paper submission : Monday, February 1st 2021, 23:59 CET
  • Notification of acceptance: Monday, March 15, 2021

  • Final Version due: Sunday March 28, 2021 (see instructions on the camera ready submission page)

  • Conference: May 16 - May 20, 2021


Plenary speakers

Daniel Cremers (Professor, Technische Universität München)

Julie Delon (Professor at MAP5, Université Paris Descartes)

‪Carola-Bibiane Schönlieb (Professor and head of the Cambridge Image Analysis, University of Cambridge)

Jean-Luc Starck (Director of CosmoStat, CEA) 


Organizing Committee

Abderrahim Elmoataz, Univ. of Caen Normandy (GREYC)

Jalal FadiliUniv. of Caen Normandy (GREYC)

Yvain Quéau, CNRS (GREYC)

Julien RabinUniv. of Caen Normandy (GREYC)

Loïc Simon, Univ. of Caen Normandy (GREYC)



CMT submission webpage :

Contributions are in the form of full papers, 12 pages in Springer LNCS format including bibliography.

Papers accepted for the conference will appear in the conference proceedings that will be published in Springer's Lecture Notes in Computer Science series. The proceedings will be available at the conference. Prospective authors are invited to submit a full-length twelve-page paper electronically via the SSVM'21 Paper Submission Web Page. All papers will undergo a double-blind peer-review procedure. At the conference the papers will be presented as posters or talks.

The conference will award a best student paper prize.





SSVM logo design by Maria Hänel.

Affiliated Organisations and Sponsors

Conference topics

SSVM is a biannual meeting within the area of Computer Vision and Image Analysis. SSVM focuses especially on multiscale analysis of image content, partial differential equations, geometric and level-set methods, variational methods, and optimization.

Conference topics include the following areas:

  • 3D vision 
  • Approximation methods in imaging
  • Compressed sensing
  • Convex and non-convex variational models
  • Cross-scale structure 
  • Differential geometry and invariants 
  • Image- and feature analysis 
  • Imaging modalities 
  • Implicit surfaces 
  • Inverse problems in imaging 
  • Machine learning in imaging
  • Manifold data processing 
  • Mathematics of novel imaging methods 
  • Medical imaging and other applications 
  • Motion estimation and tracking 
  • Multi-orientation and multi-scale modelling and analysis 
  • Optical flow 
  • Optimization methods in imaging 
  • PDEs in data processing 
  • Perceptual grouping 
  • Registration 
  • Restoration and reconstruction 
  • Scale-space methods 
  • Segmentation 
  • Selection of salient scales 
  • Shape from X 
  • Stereo and multi-view reconstruction 
  • (Sub-)Riemannian geometry in imaging
  • Surface and shape modelling and analysis
  • Variational methods 
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