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Conference Paper
F. Lenzen, Kim, K. I., Schäfer, H., Nair, R., Meister, S., Becker, F., and Garbe, C. S., “Denoising Strategies for Time-of-Flight Data”, in Time-of-Flight Imaging: Algorithms, Sensors and Applications, 2013, vol. 8200, pp. 24-25.
F. Lenzen, Schäfer, H., and Garbe, C. S., “Denoising Time-Of-Flight Data with Adaptive Total Variation”, in Proceedings ISVC, 2011, pp. 337-346.
H. Spies and Garbe, C. S., “Dense parameter fields from total least squares”, in Proceedings of the 24th DAGM Symposium on Pattern Recognition, 2002, vol. LNCS 2449, p. 379--386.
H. Spies, Kirchgeßner, N., Scharr, H., and Jähne, B., “Dense structure estimation via regularised optical flow”, in VMV 2000, 2000, p. 57--64.
H. Spies, Kirchgeßner, N., Scharr, H., and Jähne, B., “Dense structure estimation via regularised optical flow”, in VMV 2000, 2000, p. 57--64.
H. Schäfer, Lenzen, F., and Garbe, C. S., “Depth and Intensity Based Edge Detection in Time-of-Flight Images”, in 3DV-Conference, 2013 International Conference on, 2013, pp. 111-118.PDF icon Technical Report (1.85 MB)
H. Schäfer, Lenzen, F., and Garbe, C. S., “Depth and Intensity Based Edge Detection in Time-of-Flight Images”, in 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), 2013 International Conference on, 2013, pp. 111-118.
B. Jähne and Geißler, P., “Depth from focus with one image”, in Proc. Conference on Computer Vision and Pattern Recognition (CVPR '94), Seattle, 20.-23. June 1994, 1994, p. 713--717.
M. Hornáček, Rhemann, C., Gelautz, M., and Rother, C., “Depth super resolution by rigid body self-similarity in 3D”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2013, pp. 1123–1130.
P. Geißler, Scholz, T., Jähne, B., Schmidt, C., Suhr, H., and Wehnert, G., “Depth-from-Focus Verfahren zur absoluten Größen- und Konzentrationsbestimmung kleiner Teilchen”, in Bildverarbeitung'95 - Forschen, Entwickeln, Anwenden, 1995, p. 365--380.
P. Geißler, Jähne, B., and Pöppl, S. J., “Depth-from-focus zur Bestimmung der Konzentration und Größe von Gasblasen”, in Proc. 15. DAGM-Symposium Mustererkennung, 1993, p. 560--567.
S. Ramos, Gehrig, S., Pinggera, P., Franke, U., and Rother, C., “Detecting unexpected obstacles for self-driving cars: Fusing deep learning and geometric modeling”, in IEEE Intelligent Vehicles Symposium, Proceedings, 2017, pp. 1025–1032.
J. Scholz, Wiersbinski, T., Ruhnau, P., Kondermann, D., Garbe, C. S., Hain, R., and Beushausen, V., “Double-pulse planar-LIF investigations using fluorescence motion analysis for mixture formation investigation”, in 7th International Symposium on Particle Image Velocimetry Rome, 11. - 14.Sept., 2007.
E. Brachmann, Krull, A., Nowozin, S., Shotton, J., Michel, F., Gumhold, S., and Rother, C., “DSAC - Differentiable RANSAC for camera localization”, in Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017, vol. 2017-Janua, pp. 2492–2500.
K. Wiehler, Grigat, R. –R., Heers, J., Schnörr, C., and Stiehl, H. S., “Dynamic Circular Cellular Networks for Adaptive Smoothing of Multi–Dimensional Signals”, in Proc. 5th IEEE Int. Workshop on Cellular Neural Networks and their Applications, London, 1998.
H. Schäfer, Lenzen, F., Meister, S., and Garbe, C. S., “Edge Detection in Time-of-Flight Images”, in submitted to ECCV, 2nd Workshop on Consumer Depth Cameras for Computer Vision, 2012.
M. Diebold and Goldlücke, B., “Epipolar Plane Image Refocusing for Improved Depth Estimation and Occlusion Handling.”, in VMV, 2013.
B. Andres, Kondermann, C., Kondermann, D., Hamprecht, F. A., and Garbe, C. S., “On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation”, in IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, 2008, p. 1--6.
T. Hara, Wendelbo, J., Garbe, C. S., Schimpf, U., and Frew, N. M., “Estimation of air-sea gas and heat fluxes from infrared imagery and surface wave measurements”, in Presented at: International Liège Colloquium on Ocean Dynamics, Gas Transfer at Water Surfaces, 2005.
C. S. Garbe and Jähne, B., “Estimation of motion and parameters of heat transport from thermography”, in Quantitative Infrared Thermography, 2004.
B. Jähne, Schimpf, U., Popp, C., and Garbe, C. S., “Exchange processes at the ocean surface: their role in coupling atmosphere and ocean, a contribution to the SOLAS project”, in Verhandlungen der Deutschen Physikalischen Gesellschaft, Spring Conference, Munich, 22.-26.03.2004, 2004.
C. S. Garbe, Schnörr, C., and Jähne, B., “Fluid flow estimation through integration of physical flow configurations”, in Proceedings of the 29th DAGM Symposium on Pattern Recognition, 2007, p. 92--101.
B. Jähne, “From mean fluxes to a detailed experimental investigation of the gas transfer process”, in 2nd International Symposium on Gas Transfer at Water Surfaces - Air--Water Mass Transfer, Minneapolis 1990, 1991, p. 244--256.
V. Gulshan, Rother, C., Criminisi, A., Blake, A., and Zisserman, A., “Geodesic star convexity for interactive image segmentation”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, pp. 3129–3136.
H. Abu Alhaija, Mustikovela, S. Karthik, Geiger, A., and Rother, C., “Geometric Image Synthesis”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11366 LNCS, pp. 85–100.
F. Michel, Kirillov, A., Brachmann, E., Krull, A., Gumhold, S., Savchynskyy, B., and Rother, C., “Global hypothesis generation for 6D object pose estimation”, in Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017, vol. 2017-Janua, pp. 115–124.
C. Schnörr, Stiehl, H. - S., and Grigat, R. - R., “On Globally Asymptotically Stable Continuous-Time CNNs for Adaptive Smoothing of Multidimensional Signals”, in Proc. 4th IEEE Int. Workshop on Cellular Neural Networks and their Applications, Seville, Spain, 1996.
S. Wanner and Goldlücke, B., “Globally Consistent Depth Labeling of 4D Light Fields”, in CVPR. Proceedings, 2012, pp. 41-48.
S. Wanner and Goldlücke, B., “Globally Consistent Depth Labeling of 4D Lightfields”, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012.
S. Wanner, Straehle, C. N., and Goldlücke, B., “Globally consistent multi-label assignment on the ray space of 4D light fields”, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013.
D. Kondermann, Nair, R., Honauer, K., Krispin, K., Andrulis, J., Brock, A., Güssefeld, B., Rahimimoghaddam, M., Hofmann, S., Brenner, C., and Jähne, B., “The HCI Benchmark Suite: Stereo and Flow Ground Truth With Uncertainties for Urban Autonomous Driving”, in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2016.
B. Jähne, Schimpf, U., Garbe, C. S., and Degreif, K., “The Heidelberg Aeolotron: new perspectives for laboratory investigations of small-scale air-sea interaction”, in Poster presented at: International Liege Colloquium on Ocean Dynamics, Gas Transfer at Water Surfaces, 2005.
M. Diebold, Gatto, A., and Jähne, B., “Heterogeneous Light Fields”, in 2016 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2016, Las Vegas, NV, USA, June 27-30, 2016, 2016.
R. Nair, Lenzen, F., Meister, S., Schäfer, H., Garbe, C. S., and Kondermann, D., “High accuracy TOF and stereo sensor fusion at interactive rates”, in Computer Vision–ECCV 2012. Workshops and Demonstrations, 2012, pp. 1–11.
R. Nair, Lenzen, F., Meister, S., Schäfer, H., Garbe, C. S., and Kondermann, D., “High accuracy TOF and stereo sensor fusion at interactive rates”, in Computer Vision--ECCV 2012. Workshops and Demonstrations, 2012, p. 1--11.PDF icon Technical Report (7.29 MB)

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