J. H.  Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., ?A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems?, International Journal of Computer Vision, pp. 1-30, 2015.

J. H.  Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., ?A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems?, Int.~J.~Comp.~Vision, 2015.

T.  Beier, Hamprecht, F. A., and Kappes, J. H., ?Fusion Moves for Correlation Clustering?, in CVPR. Proceedings, 2015, pp. 3507-3516.

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.

J. H.  Kappes, Petra, S., Schnörr, C., and Zisler, M., ?TomoGC: Binary Tomography by Constrained Graph Cuts?, in Proc.~GCPR, 2015.

T.  Kröger, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., ?Asymmetric Cuts: Joint Image Labeling and Partitioning?, in Pattern Recognition - 36th German Conference, {GCPR} 2014, Münster, Germany, September 2-5, 2014, Proceedings, 2014.

J. H.  Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., ?A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems?, CoRR, vol. abs/1404.0533, 2014.

J. H.  Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., ?A Comparative Study of Modern Inference Techniques for StructuredDiscrete Energy Minimization Problems?, CoRR, 2014.

T.  Beier, Kröger, T., Kappes, J. H., Köthe, U., and Hamprecht, F. A., ?Cut, Glue and Cut: A Fast, Approximate Solver for Multicut Partitioning?, in 2014 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2014, Columbus, OH, USA, June 23-28, 2014, 2014.

J. H.  Kappes, Beier, T., and Schnörr, C., ?MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves?, in Computer Vision - {ECCV} 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part {II}, 2014.

P.  Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., ?Partial Optimality by Pruning for MAP-inference with General Graphical Models?, in IEEE Conference on Computer Vision and Pattern Recognition 2014, 2014.

P.  Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., ?Partial Optimality by Pruning for MAP-inference with General GraphicalModels?, CVPR. Proceedings. pp. 1170-1177, 2014.

J. H.  Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Sungwoong, K., Kausler, B. X., Lellmann, J., Komodakis, N., and Rother, C., ?A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems?, in CVPR 2013. Proceedings, 2013.

J. H.  Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Lellmann, J., Komodakis, N., and Rother, C., ?A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problem?, in CVPR, 2013.

B.  Savchynskyy, Kappes, J. H., Swoboda, P., and Schnörr, C., ?Global MAP-Optimality by Shrinking the Combinatorial Search Areawith Convex Relaxation?, in NIPS. Proceedings, 2013, pp. 1950-1958.

B.  Savchynskyy, Kappes, J. H., Swoboda, P., and Schnörr, C., ?Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation?, in NIPS, 2013.

J. H.  Kappes, Speth, M., Reinelt, G., and Schnörr, C., ?Higher-order Segmentation via Multicuts?, ArXiv e-prints. 2013.

P.  Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., ?Partial Optimality via Iterative Pruning for the Potts Model?, in Scale Space and Variational Methods (SSVM 2013), 2013.

P.  Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., ?Partial Optimality via Iterative Pruning for the Potts Model?, in Scale Space and Variational Methods (SSVM 2013), 2013.

P.  Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., ?Partial Optimality via Iterative Pruning for the Potts Model?, in Proceedings of the 4th International Conference on Scale Space andVariational Methods in Computer Vision SSVM, 2013, pp. 477-488.

P.  Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., ?Persistency by Pruning for General Graphical Models?, in submitted to NIPS 2013., 2013.

J. H.  Kappes, Speth, M., Reinelt, G., and Schnörr, C., ?Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization?, in CVPR, 2013.

J. H.  Kappes, Speth, M., Reinelt, G., and Schnörr, C., ?Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization?, in CVPR, 2013.

F.  Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., ?Variational Recursive Joint Estimation of Dense Scene Structure andCamera Motion from Monocular High Speed Traffic Sequences?, International Journal of Computer Vision, vol. 105 (3), pp. 269-297, 2013.

F.  Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., ?Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences?, International Journal of Computer Vision, vol. 105, no. 3, p. 269--297, 2013.

J. H.  Kappes, Savchynskyy, B., and Schnörr, C., ?A Bundle Approach To Efficient MAP-Inference by Lagrangian Relaxation?, in CVPR, 2012.

J. H.  Kappes, Savchynskyy, B., and Schnörr, C., ?A Bundle Approach To Efficient MAP-Inference by Lagrangian Relaxation?, in CVPR. Proceedings, 2012, pp. 1688-1695.

B.  Savchynskyy, Schmidt, S., Kappes, J. H., and Schnörr, C., ?Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing?, UAI. Proceedings, pp. 746-755, 2012.

B.  Savchynskyy, Schmidt, S., Kappes, J. H., and Schnörr, C., ?Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing?, in UAI 2012, 2012.

B.  Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., ?The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models?, in ECCV 2012, 2012.

B.  Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., ?The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models?, in Computer Vision - {ECCV} 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part {VII}, 2012.

S.  Schmidt, Savchynskyy, B., Kappes, J. H., and Schnörr, C., ?Evaluation of a First-Order Primal-Dual Algorithm for MRF Energy Minimization?, in EMMCVPR, 2011, vol. 6819, pp. 89-103.

S.  Schmidt, Savchynskyy, B., Kappes, J. H., and Schnörr, C., ?Evaluation of a First-Order Primal-Dual Algorithm for MRF EnergyMinimization?, in EMMCVPR 2011, 2011, vol. 6819, pp. 89-103.

J. H.  Kappes, Speth, M., Andres, B., Reinelt, G., and Schnörr, C., ?Globally Optimal Image Partitioning by Multicuts?, in EMMCVPR, 2011.

J. H.  Kappes, Speth, M., Andres, B., Reinelt, G., and Schnörr, C., ?Globally Optimal Image Partitioning by Multicuts?, in EMMCVPR, 2011, pp. 31-44.

B.  Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., ?Probabilistic Image Segmentation with Closedness Constraints?, in Proceedings of ICCV, 2011.

B.  Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., ?Probabilistic Image Segmentation with Closedness Constraints?, in Proceedings of ICCV, 2011.

B.  Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., ?Probabilistic Image Segmentation with Closedness Constraints?, in ICCV, Proceedings, 2011, pp. 2611 - 2618.

B.  Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., ?A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling?, in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2011.

B.  Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., ?A Study of Nesterov's Scheme for Lagrangian Decomposition and MAPLabeling?, IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), accepted as oral presentation, pp. 1817 - 1823, 2011.

F.  Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., ?Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences?, in 2011 IEEE International Conference on Computer Vision (ICCV), 2011, p. 1692 -- 1699.

F.  Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., ?Variational Recursive Joint Estimation of Dense Scene Structure andCamera Motion from Monocular High Speed Traffic Sequences?, in 2011 IEEE International Conference on Computer Vision ICCV, 2011, pp. 1692-1699.

B.  Andres, Kappes, J. H., Köthe, U., Schnörr, C., and Hamprecht, F. A., ?An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM?, in Pattern Recognition, Proc.~32th DAGM Symposium, 2010.

B.  Andres, Kappes, J. H., Köthe, U., Schnörr, C., and Hamprecht, F. A., ?An Empirical Comparison of Inference Algorithms for Graphical Modelswith Higher Order Factors Using OpenGM?, in Pattern Recognition, Proc.~32th DAGM Symposium, 2010, pp. 353-362.

B.  Andres, Kappes, J. H., Köthe, U., and Hamprecht, F. A., ?The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search?, ArXiv e-prints, 2010.

J. H.  Kappes, Schmidt, S., and Schnörr, C., ?MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation?, in European Conference on Computer Vision (ECCV), 2010, vol. 6313, p. 735--747.

J. H.  Kappes, Schmidt, S., and Schnörr, C., ?MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation?, in European Conference on Computer Vision (ECCV), 2010, vol. 6313, p. 735--747.

M.  Bergtholdt, Kappes, J. H., Schmidt, S., and Schnörr, C., ?A Study of Parts-Based Object Class Detection Using Complete Graphs?, Int.~J.~Comp.~Vision, vol. 87, pp. 93-117, 2010.

J.  Lellmann, Kappes, J. H., Yuan, J., Becker, F., Schnörr, C., Mórken, K., and Lysaker, M., ?Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation?, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.

J.  Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., ?Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation?, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.

J.  Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., ?Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation?, IWR, University of Heidelberg, 2008.

J. H.  Kappes and Schnörr, C., ?MAP-Inference for Highly-Connected Graphs with DC-Programming?, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 1--10.

R.  Karim, Bergtholdt, M., Kappes, J. H., and Schnörr, C., ?Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification?, in Pattern Recognition -- 29th DAGM Symposium, 2007, vol. 4713, pp. 395-404.

S.  Schmidt, Kappes, J. H., Bergtholdt, M., Pekar, V., Dries, S., Bystrov, D., and Schnörr, C., ?Spine Detection and Labeling Using a Parts-Based Graphical Model?, in Proc. 20th International Conference on Information Processing in Medical Imaging (IPMI 2007), 2007, vol. 4584, pp. 122-133.