Publications

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2019
Haußmann, M, Hamprecht, F A and Kandemir, M (2019). Deep Active Learning with Adaptive Acquisition. IJCAI. Proceedings. 2470-2476PDF icon Technical Report (137.6 KB)
Li, W, Hosseini Jafari, O and Rother, C (2019). Deep Object Co-segmentation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11363 LNCS 638–653
Savchynskyy, B (2019). Discrete Graphical Models — An Optimization Perspective. Foundations and Trends® in Computer Graphics and Vision. Now Publishers. 11 160–429
Sanakoyeu, A, Tschernezki, V, Büchler, U and Ommer, B (2019). Divide and Conquer the Embedding Space for Metric Learning. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://github.com/CompVis/metric-learning-divide-and-conquer
2016
Honauer, K, Johannsen, O, Kondermann, D and Goldlücke, B (2016). A Dataset and Evaluation Methodology for Depth Estimation on 4D Light Fields. Computer Vision - ACCV 2016 : 13th Asian Conference on Computer Vision, Taipei, Taiwan, November 20-24, 2016, Revised Selected Papers, Part III. Springer, Cham
Schmidt, P (2016). Deep Learning For Bioimage Analysis. University of Heidelberg
Balles, L (2016). Deep Learning For Diabetic Retinopathy Diagnostics. University of Heidelberg
Kleesiek, J, Urban, G, Hubert, A, Schwarz, D, Maier-Hein, K, Bendszus, M and Biller, A (2016). Deep MRI brain extraction: A 3D convolutional neural network for skull stripping.. NeuroImage. 129 460-469PDF icon Technical Report (1.14 MB)
Bell, P and Ommer, B (2016). Digital Connoisseur? How Computer Vision Supports Art History. Connoisseurship nel XXI secolo. Approcci, Limiti, Prospettive, A. Aggujaro & S. Albl (ed.). Artemide, Rome
Zisler, M, Petra, S, Schnörr, C and Schnörr, C (2016). Discrete Tomography by Continuous Multilabeling Subject to Projection Constraints. Proc. GCPR
Aström, F and Schnörr, C (2016). Double-Opponent Vectorial Total Variation. Proc. ECCV
Swoboda, P, Kuske, J and Savchynskyy, B (2016). A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems. arXiv, preprint. https://arxiv.org/pdf/1612.05460.pdf
2013
Wanner, S, Meister, S and Goldlücke, B (2013). Datasets and Benchmarks for Densely Sampled 4D Light Fields. Vision, Modeling & Visualization. 225--226
Lenzen, F, Kim, K In, Schäfer, H, Nair, R, Meister, S, Becker, F and Garbe, C S (2013). Denoising Strategies for Time-of-Flight Data. Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications. Springer. 8200 25-45PDF icon Technical Report (961.62 KB)
Lenzen, F, Kim, K I, Schäfer, H, Nair, R, Meister, S, Becker, F and Garbe, C S (2013). Denoising Strategies for Time-of-Flight Data. Time-of-Flight Imaging: Algorithms, Sensors and Applications. Springer. 8200 24-25
Schäfer, H, Lenzen, F and Garbe, C S (2013). Depth and Intensity Based Edge Detection in Time-of-Flight Images. 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), 2013 International Conference on. IEEE. 111-118
Schäfer, H, Lenzen, F and Garbe, C S (2013). Depth and Intensity Based Edge Detection in Time-of-Flight Images. 3DV-Conference, 2013 International Conference on. 111-118PDF icon Technical Report (1.85 MB)

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