DAGM German Conference on Pattern Recognition, September 28 - October 1, 2021
Welcome to the 43rd DAGM German Conference on Pattern Recognition, the annual symposium of the German Association for Pattern Recognition (DAGM). The conference is an international premier venue for recent advances in pattern recognition including image processing, machine learning, and computer vision and welcomes submissions from all areas of pattern recognition. It features special tracks, nectar tracks, a special session on Unsolved Problems in Pattern Recognition, the German Pattern Recognition Award for outstanding research in the fields of pattern recognition, computer vision, and machine learning, the DAGM MVTec Dissertation Award, and the Young Researchers' Forum with an award for the best Master thesis.
The best papers will be invited to contribute to a special issue of the International Journal of Computer Vision (IJCV).
The program includes four keynotes by David Forsyth (University of Illinois at Urbana-Champaign), Kristen Grauman (University of Texas at Austin, Facebook AI Research), Thorsten Joachims (Cornell University), and Jiri Matas (Czech Technical University, Prague).
A tutorial on Geometric Deep Learning will be given by Emanuele Rodolà (Sapienza University of Rome) and a workshop on Scene Understanding in Unstructured Environments will be organized on September 28.
We monitor the current situation and we will decide end of May if the conference will be organized as a hybrid or virtual conference.
If you have questions, please contact us per email to dagm-gcpr@googlegroups.com.
The DAGM German Conference on Pattern Recognition (DAGM GCPR) 2021 is the 43rd annual symposium of the German Association for Pattern Recognition (DAGM). It is an international premier venue for recent advances in pattern recognition including image processing, machine learning, and computer vision and welcomes submissions from all areas of pattern recognition. Authors are invited to submit high-quality papers presenting original research. Submitted papers will be reviewed based on the criteria of originality, soundness, empirical evaluation, and presentation. Accepted papers will be published by Springer as a proceeding of the Lecture Notes in Computer Science (LNCS). The best papers will be invited to contribute to a special issue of the International Journal of Computer Vision (IJCV).
Topics of interest include, but are not limited to, the following:
We especially invite submissions for these Special Tracks, which are chaired and reviewed explicitly by experts from the respective fields:
Computer vision systems and applications
Chairs: Bodo Rosenhahn (Leibniz University Hannover),
Carsten Steger (MVTec Software GmbH, Technical University of Munich)
The computer vision systems and applications track invites papers on systems and applications with significant, interesting vision and machine learning components. The track provides a forum for researchers working on industrial applications to share their latest developments. The reviewing criteria will be slightly different for this track: The focus is not on state-of-the-art research novelties, but the system and applied papers have to stand out in the successful transfer and application of research results to industry with measurable success indicators, such as performance, robustness, memory or energy consumption, big data, the systems-level innovation or the adaptation of existing methods to a complete novel domain while satisfying industrial requirements. These review criteria will be explicitly communicated to the reviewers to ensure clear quality expectations and interesting contributions.
Pattern recognition in the life and natural sciences
Chairs: Joachim Denzler (University of Jena), Xiaoyi Jiang (University of Münster)
Pattern recognition and machine learning already became a major driver in the sciences, for example, for data driven analysis or understanding of processes. This special track asks for original work that demonstrates successful development and application of pattern recognition methods tailored to the specific domain from the life- and natural sciences.
Photogrammetry and remote sensing
Chairs: Helmut Mayer (Bundeswehr University Munich), Uwe Sörgel (University of Stuttgart)
The photogrammetry and remote sensing track invites papers on theory and applications in photogrammetry and remote sensing with significant computer vision or machine learning components. The track provides a forum for researchers developing approaches from image classification and segmentation to high-precision photogrammetry to share their latest developments. The reviewing criteria will be slightly different for this track: Besides based on state-of-the-art research novelties papers will also be considered if they present interesting, complex applications possibly in unexpected domains or with novel extensive data sets. These review criteria will be explicitly communicated to the reviewers to ensure clear quality expectations and interesting contributions.
Robot vision
Chairs: Friedrich Fraundorfer (Graz University of Technology), Jörg Stückler (Max Planck Institute for Intelligent Systems)
The robot vision track invites papers on state-of-the-art research in computer vision approaches for robotics. The papers in the track will be reviewed by experts in the field and judged by criteria of technical merit, quality, originality, and scientific novelty. The track provides a forum for researchers on robotics-related methods for computer vision and machine learning at the conference.
Papers are submitted through Microsoft CMT (https://cmt3.research.microsoft.com/DAGMGCPR2021).The DAGM GCPR 2021 proceedings to be published in the Springer LNCS series will include all accepted papers under the condition that at least one of the authors completes a regular registration to the conference. In case of a virtual conference, the registration will be free of charge, but a paper processing fee needs to be paid for each accepted paper. Authors should take into account the following rules:
Papers that do not conform with the above guidelines will be rejected without reviewing.
If you are a Master student you might be eligible for the Best Master's Thesis Award or a travel grant of the Young Researchers Forum. Students who received a Master's degree from a university in Austria, Germany, or Switzerland after July 10, 2020 can apply for the best Master's Thesis Award. Please visit the DAGM Young Researcher Forum website for more information. The submission instructions are the same as for regular papers, but the submission needs to be marked in the template as well as in CMT as a YRF submission. After the submission, a link will be provided in order to submit until the supplementary material deadline additionally:
The goals of DAGM GCPR are to publish exciting new work for the first time and to avoid duplicating the effort of reviewers.
By submitting a manuscript to DAGM GCPR, authors acknowledge that it has not been previously published or accepted for publication in substantially similar form in any peer-reviewed venue including journal, conference or workshop, or archival forum. Furthermore, no publication substantially similar in content has been or will be submitted to this or another conference, workshop, or journal during the review period. Violation of any of these conditions will lead to rejection, and will be reported to the other venue to which the submission was sent.
A publication, for the purposes of this policy, does not consider an arXiv.org paper as a publication because it cannot be rejected. It also excludes technical reports which are not peer reviewed.
By submitting a paper, the authors agree that the paper is processed by the Toronto Paper Matching System to match each manuscript to the best possible reviewers.
If you have questions, please contact us per email to dagm-gcpr@googlegroups.com.
An author kit will be provided.
Papers are submitted through Microsoft CMT (https://cmt3.research.microsoft.com/DAGMGCPR2021).
We invite to a Special Session on "Unsolved Problems in Pattern Recognition" as part of the DAGM German Conference on Pattern Recognition (DAGM GCPR) 2021. The session provides a platform for discussing the major challenges of pattern recognition, computer vision, and machine learning in the next years. The event is an opportunity to take a step back from the daily business and debate about the currently most relevant problems in the field and emphasize the most promising future research directions. Participants are kindly requested to submit an extended abstract of not more than two pages, which sketches an open problem in the respective field or in related application areas. The proposal should contain:
A committee will select a small number of proposals to be presented in talks. The goal of the talks is to spark a (possibly controversial) discussion rather than presenting paper-ready solutions to the depicted problem. Please submit your proposal as single PDF per email to dagm-gcpr@googlegroups.com. If you have questions, please contact us per email as well.
Keynote speakers of this Special Session are David Forsyth and Jiri Matas.The conference will be held from September 28 to October 1, 2021. On September 28, there will be a tutorial on Geometric Deep Learning, a workshop on Scene Understanding in Unstructured Environments, and two Nectar Tracks for Machine Learning and Pattern Recognition. The Nectar Tracks offer the opportunity to present and discuss the latest works that have been published at top-tier machine learning or pattern recognition conferences and journals.
The special session on Unsolved Problems in Pattern Recognition on September 29 provides a unique venue for discussing the major challenges of pattern recognition in the next years. The event is an opportunity to take a step back from the daily business and debate about the currently most relevant problems in the field and emphasize the most promising future research directions.
The workshop is organized by Abhinav Valada (University of Freiburg), Peter Mortimer (Bundeswehr University Munich), Nina Heide (Fraunhofer IOSB), and Jens Behley (University of Bonn). The workshop includes a challenge on Outdoor Semantic Segmentation. For more details including submission deadlines for the challenge as well as extended abstracts please visit Workshop on Scene Understanding in Unstructured Environments.
The conference will be held either as a virtual conference or at the Campus Poppelsdorf, Friedrich-Hirzebruch-Allee 5 & 6, 53115 Bonn.
The conference dinner will be held at the Rheinhotel Dreesen.
Bonn is a green city in the heart of Europe, beautifully situated on the banks of the river Rhine. With its idyllic green surroundings, it waits to be explored by nature-lovers, hikers and cyclists. Here, at the gateway to the Upper Middle Rhine Valley - a UNESCO World Heritage site - visitors encounter a hospitable place with rich history, many cultural offerings, a cosmopolitan flair and open-minded citizens. Bonn is a multicultural city where people from around 180 nationalities live peacefully together. The city features a rich history and a great number of cultural events throughout the year. The Museum Mile and several other museums, including the birthplace of Ludwig van Beethoven, are located in and around the city center. Visitors come from all around the world to enjoy various events and festivals and to go to the theatre and the opera. An overview of places of interest can be found at bonn-region.de. The following videos give some authentic impressions of Bonn:
The DAGM German Conference on Pattern Recognition is the annual symposium of the German Association for Pattern Recognition (DAGM). The conference is an international premier venue for recent advances in pattern recognition including image processing, machine learning, and computer vision. As a sponsor, you have the following benefits:
If you are interested in supporting DAGM GCPR but none of the above options fits your needs, please contact us. The scope and extent for options to sponsor designated parts of the conference program, such as the conference dinner or reception, are up to negotiation.
Prof. Dr. Juergen Gall
gall@iai.uni-bonn.de, Phone: +49 228 73 69600
Heidi Georges-Hecking
gehe@iai.uni-bonn.de, Phone: +49 228 73 4382
Prof. Dr. Juergen Gall
Department of Information Systems and Artificial Intelligence
Friedrich-Hirzebruch-Allee 8, 53115 Bonn, Germany
gall@iai.uni-bonn.de, Phone: +49 228 73 69600
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