Prof. Dr Carsten Rother

Head of Visual Learning Lab Heidelberg

Email: Carsten.Rother (to be completed with ‘@iwr.uni-heidelberg.de’)
Address: HCI, Universität Heidelberg Berliner Str. 43, D-69120 Heidelberg
Room: Mathematikon B 3/112
Phone: +49 (62 21) 54 14855

Background:

Carsten Rother received the diploma degree with distinction in 1999 from the University of Karlsruhe/Germany, conducting his diploma thesis with Prof. Dr. H.-H. Nagel. He received his PhD degree in 2003 from the Royal Institute of Technology Stockholm/Sweden, under the guidance of Jan-Olof Eklundh and Stefan Carlsson. From 2003 until 2013 he was researcher with Microsoft Research Cambridge/UK, and a member of the Computer Vision Group lead by Andrew Blake. From 2014 until 2017 he was full (W3) Professor at TU Dresden. Since September 2017 he is full Professor at Uni Heidelberg, heading the Visual Learning Lab Heidelberg. He is also coordinating director of the Heidelberg Collaboratory for Image Processing (HCI) 3rd phase. His research interests are in the field of computer vision and machine learning – ranging from deep learning and graphical models to smart data generation. He has been working on a broad range of applications – such as image editing (e.g. interactive image segmentation, alpha matting, and deconvolution), image matching (e.g. large displacement Scene Flow), scene understanding (e.g. 6D object pose estimation), Bio-Imaging (e.g. cell tracking). He has published over 150 articles (current H-index 60) at international conferences and journals. He won awards at BMVC ’16, ACCV ’14, CVPR ’13, BMVC ’12, ACCV ’10, CHI ’07, CVPR ’05, and Indian Conference on Computer Vision ’10. He was awarded the DAGM Olympus prize in 2009. He has co-developed two Microsoft products, GrabCut for Office 2010 and AutoCollage. He also co-authored a book on Markov Random Fields in Computer Vision and Image Processing. He serves as area chair for major conferences and he has been associated editor for T-PAMI.

My personal top-10 publications:

  • C. Rother, V. Kolmogorov, and A. Blake. GrabCut – Interactive Foreground Extraction using Iterated
    Graph Cuts. Siggraph, ACM ToG, 2004
  • U. Schmidt, J. Jancsary, S. Nowozin, S. Roth, and C. Rother, Cascades of regression tree fields for image restoration, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 2015
  • J. Shotton, J. Winn, C. Rother, and A. Criminisi. TextonBoost: Joint Appearance, Shape and
    Context Modeling for Mulit-Class Object Recognition and Segmentation. European Conference
    Computer Vision (ECCV) 2006
  • C. Rother, V. Kolmogorov, V. Lempitsky, and M. Szummer, Optimizing Binary MRFs via Extended
    Roof Duality. Computer Vision and Pattern recognition (CVPR) 2007
  • E. Brachmann, A. Krull, S. Nowozin, J. Shotton, F. Michel, S. Gumhold, C.Rother, DSAC – Diff erentiable RANSAC for Camera Localization. Computer Vision and Pattern recognition (CVPR) 2017
  • D. Kainmueller, F. Jug, C. Rother, and G. Myers, Active Graph Matching for Automatic Joint
    Segmentation and Annotation of C. elegans, Medical Image Computing and Computer Assisted
    Interventions Conferenc (MICCAI) 2014
  • V. Lempitsky, C. Rother, S. Roth, and A. Blake, Fusion Moves for Markov Random Field Optimization,
    IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 32(8), 2010
  • V. Kolmogorov, A. Criminisi, A. Blake, G. Cross, and C. Rother. Bi-layer segmentation of binocular
    stereo video. Computer Vision and Pattern recognition (CVPR) 2005
  • C. Rother, L. Bordeaux, Y. Hamadi, and A. Blake, AutoCollage. Siggraph, ACM ToG, 2006
  • M. Bleyer, C. Rhemann, and C. Rother, PatchMatch Stereo – Stereo Matching with Slanted Support Windows. British Machine Vision Conference (BMVC) 2011