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B
Balschbach, G (2000). Untersuchungen statistischer und geometrischer Eigenschaften von Windwellen und ihrer Wechselwirkung mit der wasserseitigen Grenzschicht. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/2473/
Balschbach, G (1994). Verschiedene Verfahren Zur Visualisierung Und Größenbestimmung Von Gasblasen In Wasser. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Balschbach, G, Klinke, J and Jähne, B (1998). Multichannel shape from shading techniques for moving specular surfaces. ECCV 1998. Springer, Berlin. 1407 170--184
Balschbach, G, Klinke, J and Jähne, B (1997). Multichannel shape from shading techniques for reconstruction of specular surfaces. Tagungsband Herbsttagung des Graduiertenkollegs "3D Bildanalyse und -synthese". H.-P. Seidel, B. Girod, H. Niemann (Hrsg.)
Balschbach, G, Menzel, M and Jähne, B (1995). A new instrument to measure steep wind-waves. IAPSO Proceedings, XXI General Assembly, Honolulu, Hawai, August 1995, PS-10 Spatial Structure of Short Ocean Waves. 387
Balluff, B, Hanselmann, M and Heeren, R M A (2017). Mass spectrometry imaging for the investigation of intratumor heterogeneity. Advances in Cancer Research. Elsevier. 134 201-230
Balles, L (2016). Deep Learning For Diabetic Retinopathy Diagnostics. University of Heidelberg
Bailoni, A, Pape, C, Wolf, S, Kreshuk, A and Hamprecht, F A (2020). Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks. GCPR. Springer. 12544 331-344
Bailoni, A (2021). Deep Learning for Graph-Based Image Instance Segmentation. Heidelberg University
Bähnisch, C, Stelldinger, P and Köthe, U (2009). Fast and Accurate 3D Edge Detection for Surface Reconstruction. Pattern Recognition. Springer. 5748 111-120
A
Álvarez, J M, Gevers, T, Diego, F and López, A M (2012). Road Geometry Classification by Adaptive Shape Models. IEEE Transactions on Intelligent Transportation Systems (ITS). 99 1-10
Atif, M (2013). Optimal Depth Estimation and Extended Depth of Field from Single Images by Computational Imaging using Chromatic Aberrations. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/15594
Atif, M and Jähne, B (2012). Optimal Depth Estimation from a Single Image by Computational Imaging using Chromatic Aberrations. Forum Bildverarbeitung. KIT Scientific Publishing. 23--34. http://digbib.ubka.uni-karlsruhe.de/volltexte/1000030440
Atif, M and Jähne, B (2013). Optimal Depth Estimation from a Single Image by Computational Imaging Using Chromatic Aberrations. tm --- Technisches Messen. 80 343--348
Atif, M, Zimmermann, K and Jähne, B (2010). A space-variant (3D) image simulation tool for computational cameras. International Conference on Computational Photography (ICCP) 2010
Atif, M (2013). Optimal Depth Estimation and Extended Depth of Field from Single Images by Computational Imaging using Chromatic Aberrations. IWR, Univ. Heidelberg. Dissertation
Aström, F and Schnörr, C (2017). A Geometric Approach for Color Image Regularization. Comp. Vision Image Understanding. 165 43–59. https://doi.org/10.1016/j.cviu.2017.10.013
Aström, F, Hühnerbein, R, Savarino, F, Recknagel, J and Schnörr, C (2017). MAP Image Labeling Using Wasserstein Messages and Geometric Assignment. Proc. SSVM. Springer. 10302
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2017). Image Labeling by Assignment. J. Math. Imag. Vision. 58 211–238. Papers/Astroem2017.pdf
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). A Geometric Approach to Image Labeling. Proc. ECCV
Aström, F and Schnörr, C (2016). Double-Opponent Vectorial Total Variation. Proc. ECCV
Aström, F and Schnörr, C (2016). A Geometric Approach to Color Image Regularization. https://arxiv.org/abs/1605.05977
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). The Assignment Manifold: A Smooth Model for Image Labeling. Proc. 2nd Int. Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16; oral presentation; Grenander best paper award)
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). Image Labeling by Assignment. http://arxiv.org/abs/1603.05285
Arnold, N (2015). Visualisierung Des Gasaustauschs An Der Windbewegten Wasseroberfläche Mittels Vertikaler Konzentrationsfelder Von Gelöstem Sauerstoff Quer Zur Windrichtung. Institut für Umweltphysik, Universität Heidelberg, Germany
Arnold, M, Bell, P and Ommer, B (2013). Automated Learning of Self-Similarity and Informative Structures in Architecture. Scientific Computing & Cultural Heritage
Arnab, A, Zheng, S, Jayasumana, S, Romera-paredes, B, Kirillov, A, Savchynskyy, B, Rother, C, Kahl, F and Torr, P (2018). Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation. Cvpr. XX 1–15. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.308.8889&rep=rep1&type=pdf%0Ahttp://dx.doi.org/10.1109/CVPR.2012.6248050
Arlt, H, Sui, X, Folger, B, Adams, C, Chen, X, Remme, R, Hamprecht, F A, DiMaio, F, Liao, M, Goodman, J M, Farese, R V and Walther, T C (2021). Seipin forms a flexible cage at lipid droplet formation sites. bioRxiv
Ardizzone, L, Lüth, C, Kruse, J, Rother, C and Köthe, U (2019). Guided Image Generation with Conditional Invertible Neural Networks. http://arxiv.org/abs/1907.02392
Ardizzone, L, Lüth, C, Kruse, J, Rother, C and Köthe, U (2019). Guided Image Generation with Conditional Invertible Neural Networks. http://arxiv.org/abs/1907.02392
Ardizzone, L, Mackowiak, R, Rother, C and Köthe, U (2020). Exact Information Bottleneck with Invertible Neural Networks: Getting the Best of Discriminative and Generative Modeling. http://arxiv.org/abs/2001.06448PDF icon PDF (2.87 MB)
Antic, B, Büchler, U, Wahl, A - S, Schwab, M E and Ommer, B (2015). Spatiotemporal Parsing of Motor Kinematics for Assessing Stroke Recovery. Medical Image Computing and Computer-Assisted Intervention. SpringerPDF icon Article (2.24 MB)
Antic, B and Ommer, B (2015). Per-Sample Kernel Adaptation for Visual Recognition and Grouping. Proceedings of the IEEE International Conference on Computer Vision. IEEEPDF icon Technical Report (1.58 MB)
Antic, B and Ommer, B (2015). Spatio-temporal Video Parsing for Abnormality Detection. arXiv. abs/1502.06235. http://arxiv.org/abs/1502.06235PDF icon Technical Report (4.61 MB)
Antic, B and Ommer, B (2014). Learning Latent Constituents for Recognition of Group Activities in Video. Proceedings of the European Conference on Computer Vision (ECCV) (Oral). Springer. 33--47PDF icon Technical Report (4.54 MB)

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