2015
H. Abu Alhaija, Sellent, A., Kondermann, D., and Rother, C.,
“Graphflow—6D large displacement scene flow via graph matching”, in
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9358, pp. 285–296.
M. Schiegg, Hanslovsky, P., Haubold, C., Köthe, U., Hufnagel, L., and Hamprecht, F. A.,
“Graphical Model for Joint Segmentation and Tracking of Multiple Dividing Cell”,
Bioinformatics, vol. 31, no. 6, pp. 948-956, 2015.
Technical Report (534.29 KB) N. Krasowski, Beier, T., Knott, G. W., Köthe, U., Hamprecht, F. A., and Kreshuk, A.,
“Improving 3D EM Data Segmentation by Joint Optimization over Boundary Evidence and Biological Priors”, in
12th {IEEE} International Symposium on Biomedical Imaging, {ISBI} 2015, Brooklyn, NY, USA, April 16-19, 2015, 2015, pp. 536-539.
Technical Report (2.25 MB) N. Krasowski, Beier, T., Knott, G. W., Köthe, U., Hamprecht, F. A., and Kreshuk, A.,
“Improving 3D EM Data Segmentation by Joint Optimization over Boundary Evidence and Biological Priors”, in
12th {IEEE} International Symposium on Biomedical Imaging, {ISBI} 2015, Brooklyn, NY, USA, April 16-19, 2015, 2015, pp. 536-539.
Technical Report (2.25 MB) N. Krasowski, Beier, T., Knott, G. W., Köthe, U., Hamprecht, F. A., and Kreshuk, A.,
“Improving 3D EM Data Segmentation by Joint Optimization over Boundary Evidence and Biological Priors”, in
12th {IEEE} International Symposium on Biomedical Imaging, {ISBI} 2015, Brooklyn, NY, USA, April 16-19, 2015, 2015, pp. 536-539.
Technical Report (2.25 MB) N. Krasowski, Beier, T., Knott, G. W., Köthe, U., Hamprecht, F. A., and Kreshuk, A.,
“Improving 3D EM Data Segmentation by Joint Optimization over Boundary Evidence and Biological Priors”, in
12th {IEEE} International Symposium on Biomedical Imaging, {ISBI} 2015, Brooklyn, NY, USA, April 16-19, 2015, 2015, pp. 536-539.
Technical Report (2.25 MB) A. Kirillov, Savchynskyy, B., Schlesinger, D., Vetrov, D., and Rother, C.,
“Inferring M-best diverse labelings in a single one”, in
Proceedings of the IEEE International Conference on Computer Vision, 2015, vol. 2015 Inter, pp. 1814–1822.
A. Krull, Brachmann, E., Michel, F., Yang, M. Ying, Gumhold, S., and Rother, C.,
“Learning analysis-by-synthesis for 6d pose estimation in RGB-D images”, in
Proceedings of the IEEE International Conference on Computer Vision, 2015, vol. 2015 Inter, pp. 954–962.
B. Krolla, Diebold, M., and Stricker, D.,
“Light Field from Smartphone-Based Dual Video”, in
Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part II, Cham: Springer International Publishing, 2015, pp. 600–610.
A. Kirillov, Schlesinger, D., Vetrov, D., Rother, C., and Savchynskyy, B.,
“M-best-diverse labelings for submodular energies and beyond”, in
Advances in Neural Information Processing Systems, 2015, vol. 2015-Janua, pp. 613–621.
E. Mesarchaki, Kräuter, C., Krall, K. Ellen, Bopp, M., Helleis, F., Williams, J., and Jähne, B.,
“Measuring air–sea gas-exchange velocities in a large-scale annular wind–wave tank”,
Ocean Sci., vol. 11, p. 121--138, 2015.
E. Mesarchaki, Kräuter, C., Krall, K. Ellen, Bopp, M., Helleis, F., Williams, J., and Jähne, B.,
“Measuring air–sea gas-exchange velocities in a large-scale annular wind–wave tank”,
Ocean Sci., vol. 11, p. 121--138, 2015.
F. Michel, Krull, A., Brachmann, E., Yang, M. Ying, Gumhold, S., and Rother, C.,
“Pose Estimation of Kinematic Chain Instances via Object Coordinate Regression”, 2015, pp. 181.1–181.11.
J. H. Kappes, Swoboda, P., Savchynskyy, B., Hazan, T., and Schnörr, C.,
“Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts”, in
Proc.~SSVM, 2015.
Technical Report (1.1 MB) J. Kappes, Swoboda, P., Savchynskyy, B., Hazan, T., and Schnörr, C.,
“Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts”, in
Proc. SSVM, 2015.
J. Hendrik Kappes, Swoboda, P., Savchynskyy, B., Hazan, T., and Schnörr, C.,
“Probabilistic correlation clustering and image partitioning using perturbed Multicuts”, in
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9087, pp. 231–242.
M. Schiegg, Heuer, B., Haubold, C., Wolf, S., Köthe, U., and Hamprecht, F. A.,
“Proof-reading Guidance in Cell Tracking by Sampling from Tracking-by-assignment Models”, in
ISBI. Proceedings, 2015, pp. 394-398.
Technical Report (648.55 KB) R. Nair, Fitzgibbon, A., Kondermann, D., and Rother, C.,
“Reflection modeling for passive stereo”, in
Proceedings of the IEEE International Conference on Computer Vision, 2015, vol. 2015 Inter, pp. 2291–2299.
D. Kondermann, Nair, R., Meister, S., Mischler, W., Güssefeld, B., Honauer, K., Hofmann, S., Brenner, C., and Jähne, B.,
“Stereo Ground Truth with Error Bars”, in
Computer Vision – ACCV 2014: 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part V, Cham: Springer International Publishing, 2015, pp. 595–610.
C. Cali, Baghabra, J., Boges, D. J., Holst, G. R., Kreshuk, A., Hamprecht, F. A., Srinivasan, M., Lehväslaiho, H., and Magistretti, P. J.,
“Three-dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues”,
Journal of Comparative Neurology, vol. 524, pp. 23-38, 2015.
J. P. Kauppi, Kandemir, M., Saarinen, V. M., Hirvenkari, L., Parkkonen, L., Klami, A., Hari, R., and Kaski, S.,
“Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals”,
NeuroImage, vol. 112, pp. 288-298, 2015.
Technical Report (2.39 MB) J. P. Kauppi, Kandemir, M., Saarinen, V. M., Hirvenkari, L., Parkkonen, L., Klami, A., Hari, R., and Kaski, S.,
“Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals”,
NeuroImage, vol. 112, pp. 288-298, 2015.
Technical Report (2.39 MB) J. P. Kauppi, Kandemir, M., Saarinen, V. M., Hirvenkari, L., Parkkonen, L., Klami, A., Hari, R., and Kaski, S.,
“Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals”,
NeuroImage, vol. 112, pp. 288-298, 2015.
Technical Report (2.39 MB) J. P. Kauppi, Kandemir, M., Saarinen, V. M., Hirvenkari, L., Parkkonen, L., Klami, A., Hari, R., and Kaski, S.,
“Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals”,
NeuroImage, vol. 112, pp. 288-298, 2015.
Technical Report (2.39 MB) D. Richmond, Kainmueller, D., Glocker, B., Rother, C., and Myers, G.,
“Uncertainty-driven forest predictors for vertebra localization and segmentation”,
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9349. pp. 653–660, 2015.
C. Kräuter,
“Visualization of air-water gas exchange”, vol. Dissertation. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2015.
D. Kiefhaber, Caulliez, G., Zappa, C. J., Schaper, J., and Jähne, B.,
“Water wave measurement from stereo images of specular reflections”, vol. 26, p. 115401, 2015.
A. Kreshuk, Funke, J., Cardona, A., and Hamprecht, F. A.,
“Who is talking to whom: synaptic partner detection in anisotropic volumes of insect brain”,
MICCAI. Proceedings, vol. LNCS 9349. Springer, pp. 661-668, 2015.
Technical Report (2.14 MB) 
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