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Seminar Inverse Problems in Image Processing and Computer Vision [SemInvProb]

An inverse problem refers to the inference of latent model parameters from a set of noisy measurements under a generative model that explains the causal relationship between both. Despite the broad field of applications, this typically leads to optimization problems that can be tackled by common mathematical tools. In computer vision and image processing, many tasks of practical relevance can be formulated as inverse problems ranging from low-level vision to image analysis and scene understanding. This seminar focuses on theory along with some of the classical applications of inverse problems in image processing and computer vision. The topics covered by the seminar include but are not limited to: - image filtering and denoising - blind image restoration, upsampling and super-resolution - motion estimation - inpainting - image segmentation - shape-from-X and 3-D reconstruction

Dates & Rooms:
Monday, 8:00 - 10:00; Room: KH 1.021


  • The kick-off meeting for this seminar will take place on Monday, October 17th, 8:15 am
  • Please register for this course via Opens external link in new windowStudOn (registration deadline: 26.10.2016). We will use StudOn to distribute papers and presentation slides.
  • An introductory lecture on inverse problems will take place on Monday, October 24th, 8:15 am


  • We will assign current research papers as topics to the participants. A list of topics is available Initiates file downloadhere
  • The grade is composed to 50 % of an oral presentation and 50 % of a 6-pages seminar paper (IEEE double-column style) that is due at the end of the lecture period (Deadline: February 12th, 2017, 23:59)