Seminar

Milestones and Advances in Image Analysis

Winter Term 2021/2022


(Main) Seminar: Milestones and Advances in Image Analysis

Karl Schrader, Prof. Joachim Weickert

Winter Term 2021

(Main) Seminar (2 h)

Notice for bachelor/master students of mathematics: This is a »Hauptseminar« in the sense of these study programs.

From left to right:
T. Brox, A. Bruhn, P. Papenberg, J. Weickert: High Accuracy Optical Flow Estimation Based on a Theory for Warping.
A. Buades, B. Coll, J. Morel: A Non-local Algorithm for Image Denoising.
D. Terzopoulos: Regularization of Inverse Visual Problems Involving Discontinuities.


NEWS:

October 22, 2021:
The introductory meeting will take place on Tuesday, October 26, 2021, 16:15 p.m., via Teams.

July 19, 2021:
The seminar will be fully online.
All students will be made members of a Microsoft Teams Group after registration is closed. All communication will commence there.



Important DatesDescriptionRegistrationRequirementsIntroductory MeetingOverview of Topics



Introductory meeting (mandatory):
The introductory meeting will take place on Tuesday, October 26, 2021, 16:15 p.m., via Teams.
In this meeting, we will assign the topics to the participants. Attendance is mandatory for all participants. You are expected to turn on your camera during the meeting. Do not forget to register first (see below).
All registered participants will be added to the Team prior to the meeting.

Regular meetings during the winter term 2021:
Every Tuesday at 16:15, starting Tuesday, November 23, web meetings via Teams.

Contents: Image processing and computer vision have benefitted from a number of key ideas that have fertilised the subsequent develepment enormously. The first goal of this seminar is to study a number of publications that have played a fundamental role in this context and that are cited very often. In addition, we will cover some of the most interesting publications from recent conferences.

Prerequisites: The seminar is for advanced bachelor or master students in Visual Computing, Mathematics, or Computer Science. Basic mathematical knowledge (e.g. Mathematik für Informatiker I-III) and some knowledge in image processing and computer vision is required.

Language: All papers are written in English, and English is the language of presentation.


The registration for this course is closed.

Regular attendance: You must attend all virtual seminar meetings. You are expected to turn on your camera during the meetings. If you are sick, please send a medical certificate via mail to Karl Schrader. If you have technical difficulties, let us know as soon as possible.

Talk: Your talk will consist of a 20min prerecorded video which is divided into 3-4 parts. You or your supervisor will stream them live during the virtual seminar meeting. After each part, there will be room for questions. After the talk, there will be a final discussion. Your presentation must be delivered in English. Your slides and your write-up, too, have to be in English. Send your video files in mp4 format and your presentation slides in pdf format to Karl Schrader at least 2h before the seminar meeting.

Write-up: The write-up has to be handed in three weeks after the lecture period ends. The deadline is Sunday, March 13, 23:59. The write-up should summarise your talk and has to consist of 5 pages per speaker. Please adhere to the guidelines for write-ups posted in our Teams group. Submit your write-up in pdf format directly in the corresponding assignment in Teams.

Plagiarism: Adhere to the standards of scientific referencing and avoid plagiarism: Quotations and copied material (such as images) must be clearly marked as such, and a bibliography is required. Otherwise the seminar counts as failed. See the write-up guidelines for a detailed explanation on how to cite correctly.

Mandatory consultation: Talk preparation (including a preliminary video and presentation slides) has to be presented to your seminar supervisor no later than one week before the talk is given. It is your responsibility to approach us in a timely manner and make your appointment for a video call.

No-shows: No-shows are unfair to your fellow students: Some talks are based on previous talks, and your seminar place might have prevented the participation of another student. Thus, in case you do not appear to your scheduled talk (except for reasons beyond your control), we reserve the right to exclude you from future seminars of our group.

Participation in discussions: The discussions after the presentations are a vital part of this seminar. This means that the audience (i.e. all paricipants) poses questions and tries to find positive and negative aspects of the proposed idea.

Being in time: To avoid interrupting the seminar, all participants have to be logged into the web meeting in time. Please make sure to log in early, in case there are technical difficulties. Participants that turn out to be regularly late must expect a negative influence on their grade.


The slides of the introductory meeting will be uploaded in Teams. They contain important information for preparing a good talk.



No.   Date   Speaker Paper
1 23/11 Jonas Wagner A. Witkin:
Scale-Space Filtering.
2 23/11 Harishanth Sivakumaran H. Horn, B Schunck:
Determining Optical Flow.
3 30/11 Madukkolil Geo James A. Bruhn, J. Weickert, C. Schnörr:
Lucas/Kanade Meets Horn/Schunck: Combining Local and Global Optic Flow Methods
4 30/11 Beste Ekmen T. Brox, A. Bruhn, N. Papenberg, J. Weickert:
High Accuracy Optical Flow Estimation Based on a Theory for Warping.
5 07/12 Matthias Jost K. Ikeuchi, B. Horn:
Numerical Shape from Shading and Occluding Boundaries.
6 07/12 Vadim Farutin L. Rudin, S. Osher, E. Fatemi:
Nonlinear Total Variation Based Noise Removal Algorithms.
7 14/12 Brlal Alshilh Ali A. Buades, B. Coll, J. Morel:
A Non-local Algorithm for Image Denoising.
8 14/12 Shravan Swaminathan A. Efros, T. Leung:
Texture Synthesis by Non-parametric Sampling.
09 04/01 Moritz van Recum D. Mumford, J. Shah:
Boundary Detection by Minimizing Functionals, I.
10 04/01 Lukas Auer T. Chan, L. Vese:
Active Contours without Edges.
11 11/01 Tom Georg Fischer M. Arjovsky, S. Chintala, L. Bottou:
Wasserstein GAN.
12 11/01 S. Chen, Y. Eldar:
Time-varying Graph Signal Inpainting via Unrolling Networks.
13 18/01 T. Giraudon, V. Gripon, M. Löwe, F. Vermet:
Towards an Intrinsic Definition of Robustness for a Classifier.
14 18/01 Tim Bruxmeier D. Lopes, J. Ascenso, C. Brites, F. Pereira:
Image Coding with Neural Network-based Corlorization.
15 25/01 Kushagra Sharma A. Golts, D. Freedman, M. Elad:
Deep-Energy: Unsupervised Training of Deep Neural Networks.
16 25/01 Fabian Thomas P. Getreuer , P. Milanfar, X. Luo:
Solving Image PDEs with a Shallow Network.


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