CIBSS - Centre for integrative Biological Signalling StudiesCIBSS

Principal Investigators

Prof. Dr. Thomas Brox

Prof. Dr. Thomas Brox


Prof. Dr. Thomas Brox
Department of Computer Science (Faculty of Engineering)
University of Freiburg

T +49 761 203 8261

Weitere Informationen

CIBSS Research Projekt:

The team of Thomas Brox is working on computer vision and deep learning with focus on visual representation learning, video analysis, and learned 3D representations. In particular, they explore ways to train deep networks with less data and less human supervision, which is today the bottleneck for most application domains. They are also investigating the robustness of learned models to data variation



computer vision, machine learning, deep learning, motion estimation

10 selected publications:

  • U-Net: deep learning for cell counting, detection, and morphometry.
    Falk T, Mai D, Bensch R, Çiçek Ö, Abdulkadir A, Marrakchi Y, Böhm A, Deubner J, Jäckel Z, Seiwald K, Dovzhenko A, Tietz O, Dal Bosco C, Walsh S, Saltukoglu D, Tay TL, Prinz M, Palme K, Simons M, Diester I, Brox T, Ronneberger O (2019).
    Nat Methods. 16(1):67-70.
  • An objective comparison of cell-tracking algorithms.
    Ulman V, Maška M, Magnusson KEG, Ronneberger O, Haubold C, Harder N, Matula P, Matula P, Svoboda D, Radojevic M, Smal I, Rohr K, Jaldén J, Blau HM, Dzyubachyk O, Lelieveldt B, Xiao P, Li Y, Cho SY, Dufour AC, Olivo-Marin JC, Reyes-Aldasoro CC, Solis-Lemus JA, Bensch R, Brox T, Stegmaier J, Mikut R, Wolf S, Hamprecht FA, Esteves T, Quelhas P, Demirel Ö, Malmström L, Jug F, Tomancak P, Meijering E, Muñoz-Barrutia A, Kozubek M, Ortiz-de-Solorzano C (2017).
    Nat Methods 14, 1141-52.
  • Learning to Generate Chairs, Tables and Cars with Convolutional Networks.
    Dosovitskiy A, Springenberg J, Tatarchenko M, Brox T (2017).
    IEEE Trans Pattern Anal Mach Intell. 39, 692-705.
  • Spatiotemporal deformable prototypes for motion anomaly detection.
    Bensch R, Scherf N, Huisken J, Brox T, Ronneberger O (2017).
    International Journal of Computer Vision 122(3), 502-23.
  • Discriminative unsupervised feature learning with exemplar convolutional neural networks.
    Dosovitskiy A, Fischer P, Springenberg JT, Riedmiller M, Brox T (2016).
    IEEE Trans. Pattern. Anal. Mach. Intell. 38, 1734-47.
  • FlowNet: learning optical flow with convolutional networks.
    Dosovitskiy A, Fischer P, Ilg E, Häusser P, Hazirbas C, Golkov V, Smagt P, Cremers D, Brox T (2015).
    IEEE International Conference on Computer Vision (ICCV)
  • Segmentation of Moving Objects by Long Term Video Analysis.
    Ochs P, Malik J, Brox T (2014).
    IEEE Trans Pattern Anal Mach Intell. 36, 1187-200.
  • ViBE-Z: a framework for 3D virtual colocalization analysis in zebrafish larval brains.
    Ronneberger O, Liu K, Rath M, Rueβ D, Mueller T, Skibbe H, Drayer B, Schmidt T, Filippi A, Nitschke R, Brox T, Burkhardt H, Driever W (2012).
    Nat Methods 9, 735-42.
  • Large displacement optical flow: descriptor matching in variational motion estimation.
    Brox T, Malik J (2011).
    IEEE Trans Pattern Anal Mach. Intell. 33, 500-13.
  • Inversin relays Frizzled-8 signals to promote proximal pronephros development.
    Lienkamp S, Ganner A, Boehlke C, Schmidt T, Arnold SJ, Schäfer T, Romaker D, Schuler J, Hoff S, Powelske C, Eifler A, Krönig C, Bullerkotte A, Nitschke R, Kuehn EW, Kim E, Burkhardt H, Brox T, Ronneberger O, Gloy J, Walz G (2010).
    Proc Natl Acad Sci U S A. 107, 20388-93.