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ORCIDChristoph H. Lampert
Christoph Lampert
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- affiliation: Institute of Science and Technology Austria, Klosterneuburg, Austria
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2020 – today
- 2023
[c82]Alexandra Peste, Adrian Vladu, Eldar Kurtic, Christoph H. Lampert, Dan Alistarh:
CrAM: A Compression-Aware Minimizer. ICLR 2023- [i48]Kateryna Lutsai, Christoph H. Lampert:
Geolocation Predicting of Tweets Using BERT-Based Models. CoRR abs/2303.07865 (2023) - [i47]Peter Súkeník, Marco Mondelli, Christoph Lampert:
Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model. CoRR abs/2305.13165 (2023) - [i46]Jonathan Scott, Hossein Zakerinia, Christoph H. Lampert:
PeFLL: A Lifelong Learning Approach to Personalized Federated Learning. CoRR abs/2306.05515 (2023) - 2022
- [j18]Nikola Konstantinov, Christoph H. Lampert:
Fairness-Aware PAC Learning from Corrupted Data. J. Mach. Learn. Res. 23: 160:1-160:60 (2022) - [j17]Eugenia Iofinova, Nikola Konstantinov, Christoph H. Lampert:
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data. Trans. Mach. Learn. Res. 2022 (2022) - [c81]Bernd Prach, Christoph H. Lampert:
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks. ECCV (21) 2022: 350-365 - [c80]Paulina Tomaszewska, Christoph H. Lampert:
Lightweight Conditional Model Extrapolation for Streaming Data under Class-Prior Shift. ICPR 2022: 2128-2134 - [c79]Paulina Tomaszewska
, Christoph H. Lampert:
On the Implementation of Baselines and Lightweight Conditional Model Extrapolation (LIMES) Under Class-Prior Shift. RRPR 2022: 67-73 - [i45]Paulina Tomaszewska, Christoph H. Lampert:
Lightweight Conditional Model Extrapolation for Streaming Data under Class-Prior Shift. CoRR abs/2206.05181 (2022) - [i44]Alexandra Peste, Adrian Vladu, Dan Alistarh, Christoph H. Lampert:
CrAM: A Compression-Aware Minimizer. CoRR abs/2207.14200 (2022) - [i43]Bernd Prach, Christoph H. Lampert:
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks. CoRR abs/2208.03160 (2022) - [i42]Peter Súkeník, Christoph H. Lampert:
Generalization In Multi-Objective Machine Learning. CoRR abs/2208.13499 (2022) - [i41]Jonathan Scott, Michelle Yeo, Christoph H. Lampert:
FedProp: Cross-client Label Propagation for Federated Semi-supervised Learning. CoRR abs/2210.06434 (2022) - 2021
- [c78]Nikola Konstantinov, Christoph H. Lampert:
On the Impossibility of Fairness-Aware Learning from Corrupted Data. AFCR 2021: 59-83 - [c77]Jasmin Lampert, Christoph H. Lampert:
Overcoming Rare-Language Discrimination in Multi-Lingual Sentiment Analysis. IEEE BigData 2021: 5185-5192 - [c76]Mary Phuong, Christoph H. Lampert:
The inductive bias of ReLU networks on orthogonally separable data. ICLR 2021 - [i40]Nikola Konstantinov, Christoph H. Lampert:
Fairness Through Regularization for Learning to Rank. CoRR abs/2102.05996 (2021) - [i39]Nikola Konstantinov, Christoph H. Lampert:
Fairness-Aware Learning from Corrupted Data. CoRR abs/2102.06004 (2021) - [i38]Mary Phuong, Christoph H. Lampert:
Towards Understanding Knowledge Distillation. CoRR abs/2105.13093 (2021) - [i37]Paul Henderson, Christoph H. Lampert, Bernd Bickel:
Unsupervised Video Prediction from a Single Frame by Estimating 3D Dynamic Scene Structure. CoRR abs/2106.09051 (2021) - [i36]Eugenia Iofinova, Nikola Konstantinov, Christoph H. Lampert:
FLEA: Provably Fair Multisource Learning from Unreliable Training Data. CoRR abs/2106.11732 (2021) - [i35]Alexandra Peste, Dan Alistarh, Christoph H. Lampert:
SSSE: Efficiently Erasing Samples from Trained Machine Learning Models. CoRR abs/2107.03860 (2021) - 2020
- [j16]Rémy Sun, Christoph H. Lampert:
KS(conf): A Light-Weight Test if a Multiclass Classifier Operates Outside of Its Specifications. Int. J. Comput. Vis. 128(4): 970-995 (2020) - [j15]Rémy Sun, Christoph H. Lampert:
Correction to: KS(conf): A Light-Weight Test if a Multiclass Classifier Operates Outside of Its Specifications. Int. J. Comput. Vis. 128(4): 996 (2020) - [c75]Paul Henderson, Vagia Tsiminaki, Christoph H. Lampert:
Leveraging 2D Data to Learn Textured 3D Mesh Generation. CVPR 2020: 7495-7504 - [c74]Václav Volhejn, Christoph Lampert:
Does SGD Implicitly Optimize for Smoothness? GCPR 2020: 246-259 - [c73]Mary Phuong, Christoph H. Lampert:
Functional vs. parametric equivalence of ReLU networks. ICLR 2020 - [c72]Nikola Konstantinov, Elias Frantar, Dan Alistarh, Christoph Lampert:
On the Sample Complexity of Adversarial Multi-Source PAC Learning. ICML 2020: 5416-5425 - [c71]Paul Henderson, Christoph H. Lampert:
Unsupervised object-centric video generation and decomposition in 3D. NeurIPS 2020 - [c70]Amélie Royer, Christoph H. Lampert:
Localizing Grouped Instances for Efficient Detection in Low-Resource Scenarios. WACV 2020: 1716-1725 - [c69]Amélie Royer, Christoph H. Lampert:
A Flexible Selection Scheme for Minimum-Effort Transfer Learning. WACV 2020: 2180-2189 - [i34]Nikola Konstantinov, Elias Frantar, Dan Alistarh, Christoph H. Lampert:
On the Sample Complexity of Adversarial Multi-Source PAC Learning. CoRR abs/2002.10384 (2020) - [i33]Titas Anciukevicius, Christoph H. Lampert, Paul Henderson:
Object-Centric Image Generation with Factored Depths, Locations, and Appearances. CoRR abs/2004.00642 (2020) - [i32]Paul Henderson, Vagia Tsiminaki, Christoph H. Lampert:
Leveraging 2D Data to Learn Textured 3D Mesh Generation. CoRR abs/2004.04180 (2020) - [i31]Amelie Royer, Christoph H. Lampert:
Localizing Grouped Instances for Efficient Detection in Low-Resource Scenarios. CoRR abs/2004.12623 (2020) - [i30]Paul Henderson, Christoph H. Lampert:
Unsupervised object-centric video generation and decomposition in 3D. CoRR abs/2007.06705 (2020) - [i29]Amelie Royer, Christoph H. Lampert:
A Flexible Selection Scheme for Minimum-Effort Transfer Learning. CoRR abs/2008.11995 (2020)
2010 – 2019
- 2019
- [j14]Yongqin Xian, Christoph H. Lampert, Bernt Schiele, Zeynep Akata:
Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly. IEEE Trans. Pattern Anal. Mach. Intell. 41(9): 2251-2265 (2019) - [c68]Mary Phuong, Christoph Lampert:
Distillation-Based Training for Multi-Exit Architectures. ICCV 2019: 1355-1364 - [c67]Alexander Kolesnikov, Alina Kuznetsova, Christoph Lampert, Vittorio Ferrari:
Detecting Visual Relationships Using Box Attention. ICCV Workshops 2019: 1749-1753 - [c66]Nikola Konstantinov, Christoph Lampert:
Robust Learning from Untrusted Sources. ICML 2019: 3488-3498 - [c65]Mary Phuong, Christoph Lampert:
Towards Understanding Knowledge Distillation. ICML 2019: 5142-5151 - [c64]Pranav Ashok, Tomás Brázdil, Krishnendu Chatterjee, Jan Kretínský, Christoph H. Lampert, Viktor Toman:
Strategy Representation by Decision Trees with Linear Classifiers. QEST 2019: 109-128 - [i28]Nikola Konstantinov, Christoph Lampert:
Robust Learning from Untrusted Sources. CoRR abs/1901.10310 (2019) - [i27]Pranav Ashok, Tomás Brázdil, Krishnendu Chatterjee, Jan Kretínský, Christoph H. Lampert, Viktor Toman:
Strategy Representation by Decision Trees with Linear Classifiers. CoRR abs/1906.08178 (2019) - 2018
- [j13]Trevor Darrell, Christoph Lampert, Nicu Sebe, Ying Wu, Yan Yan:
Guest Editors' Introduction to the Special Section on Learning with Shared Information for Computer Vision and Multimedia Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 40(5): 1029-1031 (2018) - [c63]Ksenia Konyushkova, Jasper R. R. Uijlings, Christoph H. Lampert, Vittorio Ferrari:
Learning Intelligent Dialogs for Bounding Box Annotation. CVPR 2018: 9175-9184 - [c62]Rémy Sun, Christoph H. Lampert:
KS(conf): A Light-Weight Test if a ConvNet Operates Outside of Its Specifications. GCPR 2018: 244-259 - [c61]Ilja Kuzborskij, Christoph H. Lampert:
Data-Dependent Stability of Stochastic Gradient Descent. ICML 2018: 2820-2829 - [c60]Subham S. Sahoo, Christoph H. Lampert, Georg Martius:
Learning Equations for Extrapolation and Control. ICML 2018: 4439-4447 - [i26]Alexander Zimin, Christoph H. Lampert:
Towards Practical Conditional Risk Minimization. CoRR abs/1801.00507 (2018) - [i25]Rémy Sun, Christoph H. Lampert:
KS(conf ): A Light-Weight Test if a ConvNet Operates Outside of Its Specifications. CoRR abs/1804.04171 (2018) - [i24]Subham S. Sahoo, Christoph H. Lampert, Georg Martius:
Learning Equations for Extrapolation and Control. CoRR abs/1806.07259 (2018) - [i23]Alexander Kolesnikov, Christoph H. Lampert, Vittorio Ferrari:
Detecting Visual Relationships Using Box Attention. CoRR abs/1807.02136 (2018) - [i22]Ehsan Pajouheshgar, Christoph H. Lampert:
Back to square one: probabilistic trajectory forecasting without bells and whistles. CoRR abs/1812.02984 (2018) - 2017
- [c59]Alexander Zimin, Christoph H. Lampert:
Learning Theory for Conditional Risk Minimization. AISTATS 2017: 213-222 - [c58]Jasmin Pielorz, Matthias Prandtstetter, Markus Straub, Christoph H. Lampert:
Optimal geospatial volunteer allocation needs realistic distances. IEEE BigData 2017: 3760-3763 - [c57]Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert:
Probabilistic Image Colorization. BMVC 2017 - [c56]Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, Christoph H. Lampert:
iCaRL: Incremental Classifier and Representation Learning. CVPR 2017: 5533-5542 - [c55]Georg Martius, Christoph H. Lampert:
Extrapolation and learning equations. ICLR (Workshop) 2017 - [c54]Alexander Kolesnikov, Christoph H. Lampert:
PixelCNN Models with Auxiliary Variables for Natural Image Modeling. ICML 2017: 1905-1914 - [c53]Anastasia Pentina, Christoph H. Lampert:
Multi-task Learning with Labeled and Unlabeled Tasks. ICML 2017: 2807-2816 - [i21]Ilja Kuzborskij, Christoph H. Lampert:
Data-Dependent Stability of Stochastic Gradient Descent. CoRR abs/1703.01678 (2017) - [i20]Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert:
Probabilistic Image Colorization. CoRR abs/1705.04258 (2017) - [i19]Yongqin Xian, Christoph H. Lampert, Bernt Schiele, Zeynep Akata:
Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly. CoRR abs/1707.00600 (2017) - [i18]Ksenia Konyushkova, Jasper R. R. Uijlings, Christoph H. Lampert, Vittorio Ferrari:
Learning Intelligent Dialogs for Bounding Box Annotation. CoRR abs/1712.08087 (2017) - 2016
- [c52]Alexander Kolesnikov, Christoph H. Lampert:
Improving Weakly-Supervised Object Localization By Micro-Annotation. BMVC 2016 - [c51]Alexander Kolesnikov, Christoph H. Lampert:
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. ECCV (4) 2016: 695-711 - [i17]Anastasia Pentina, Christoph H. Lampert:
Active Task Selection for Multi-Task Learning. CoRR abs/1602.06518 (2016) - [i16]Alexander Kolesnikov, Christoph H. Lampert:
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. CoRR abs/1603.06098 (2016) - [i15]Alexander Kolesnikov, Christoph H. Lampert:
Improving Weakly-Supervised Object Localization By Micro-Annotation. CoRR abs/1605.05538 (2016) - [i14]Georg Martius, Christoph H. Lampert:
Extrapolation and learning equations. CoRR abs/1610.02995 (2016) - [i13]Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Christoph H. Lampert:
iCaRL: Incremental Classifier and Representation Learning. CoRR abs/1611.07725 (2016) - [i12]Alexander Kolesnikov, Christoph H. Lampert:
Deep Probabilistic Modeling of Natural Images using a Pyramid Decomposition. CoRR abs/1612.08185 (2016) - 2015
- [c50]Christoph H. Lampert:
Predicting the future behavior of a time-varying probability distribution. CVPR 2015: 942-950 - [c49]Amelie Royer, Christoph H. Lampert:
Classifier adaptation at prediction time. CVPR 2015: 1401-1409 - [c48]Neel Shah, Vladimir Kolmogorov, Christoph H. Lampert:
A multi-plane block-coordinate frank-wolfe algorithm for training structural SVMs with a costly max-oracle. CVPR 2015: 2737-2745 - [c47]Anastasia Pentina, Viktoriia Sharmanska, Christoph H. Lampert:
Curriculum learning of multiple tasks. CVPR 2015: 5492-5500 - [c46]Jasmin Pielorz, Christoph H. Lampert:
Optimal geospatial allocation of volunteers for crisis management. ICT-DM 2015: 152-158 - [c45]Anastasia Pentina, Christoph H. Lampert:
Lifelong Learning with Non-i.i.d. Tasks. NIPS 2015: 1540-1548 - [i11]Alexander Kolesnikov, Christoph H. Lampert:
Identifying Reliable Annotations for Large Scale Image Segmentation. CoRR abs/1504.07460 (2015) - [i10]Alexander Zimin, Christoph H. Lampert:
Conditional Risk Minimization for Stochastic Processes. CoRR abs/1510.02706 (2015) - 2014
- [j12]Christoph H. Lampert, Hannes Nickisch, Stefan Harmeling:
Attribute-Based Classification for Zero-Shot Visual Object Categorization. IEEE Trans. Pattern Anal. Mach. Intell. 36(3): 453-465 (2014) - [c44]Sameh Khamis, Christoph H. Lampert:
CoConut: Co-Classification with Output Space Regularization. BMVC 2014 - [c43]Vladyslav Sydorov, Mayu Sakurada, Christoph H. Lampert:
Deep Fisher Kernels - End to End Learning of the Fisher Kernel GMM Parameters. CVPR 2014: 1402-1409 - [c42]Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert:
Closed-Form Approximate CRF Training for Scalable Image Segmentation. ECCV (3) 2014: 550-565 - [c41]Anastasia Pentina, Christoph H. Lampert:
A PAC-Bayesian bound for Lifelong Learning. ICML 2014: 991-999 - [c40]Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto:
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. NIPS 2014: 837-845 - [i9]Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert:
Closed-Form Training of Conditional Random Fields for Large Scale Image Segmentation. CoRR abs/1403.7057 (2014) - [i8]Vladimir Kolmogorov, Christoph H. Lampert, Emilie Morvant, Rustem Takhanov:
Proceedings of The 38th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM), 2014. CoRR abs/1404.3538 (2014) - [i7]Christoph H. Lampert:
Blind Domain Adaptation: An RKHS Approach. CoRR abs/1406.5362 (2014) - [i6]Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto:
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. CoRR abs/1407.0179 (2014) - [i5]Neel Shah, Vladimir Kolmogorov, Christoph H. Lampert:
A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Structural SVMs with a Costly max-Oracle. CoRR abs/1408.6804 (2014) - [i4]Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert:
Learning to Transfer Privileged Information. CoRR abs/1410.0389 (2014) - [i3]Anastasia Pentina, Viktoriia Sharmanska, Christoph H. Lampert:
Curriculum Learning of Multiple Tasks. CoRR abs/1412.1353 (2014) - 2013
- [c39]Chao Chen, Vladimir Kolmogorov, Yan Zhu, Dimitris N. Metaxas, Christoph H. Lampert:
Computing the M Most Probable Modes of a Graphical Model. AISTATS 2013: 161-169 - [c38]Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert:
Learning to Rank Using Privileged Information. ICCV 2013: 825-832 - [c37]Tomas Kazmar, Evgeny Z. Kvon, Alexander Stark, Christoph H. Lampert:
Drosophila Embryo Stage Annotation Using Label Propagation. ICCV 2013: 1089-1096 - [i2]Anastasia Pentina, Christoph H. Lampert:
A PAC-Bayesian bound for Lifelong Learning. CoRR abs/1311.2838 (2013) - 2012
- [j11]Matthew B. Blaschko, Christoph H. Lampert:
Guest Editorial: Special Issue on Structured Prediction and Inference. Int. J. Comput. Vis. 99(3): 257-258 (2012) - [j10]Christoph H. Lampert, Jan Peters:
Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components. J. Real Time Image Process. 7(1): 31-41 (2012) - [c36]Tatiana Tommasi, Novi Quadrianto, Barbara Caputo, Christoph H. Lampert:
Beyond Dataset Bias: Multi-task Unaligned Shared Knowledge Transfer. ACCV (1) 2012: 1-15 - [c35]Andreas C. Müller, Sebastian Nowozin, Christoph H. Lampert:
Information Theoretic Clustering Using Minimum Spanning Trees. DAGM/OAGM Symposium 2012: 205-215 - [c34]Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert:
Augmented Attribute Representations. ECCV (5) 2012: 242-255 - [c33]Novi Quadrianto, Chao Chen, Christoph H. Lampert:
The Most Persistent Soft-Clique in a Set of Sampled Graphs. ICML 2012 - [c32]Christoph H. Lampert:
Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction. NIPS 2012: 82-90 - [i1]Novi Quadrianto, Chao Chen, Christoph H. Lampert:
The Most Persistent Soft-Clique in a Set of Sampled Graphs. CoRR abs/1206.4652 (2012) - 2011
- [j9]Sebastian Nowozin, Christoph H. Lampert:
Structured Learning and Prediction in Computer Vision. Found. Trends Comput. Graph. Vis. 6(3-4): 185-365 (2011) - [j8]Matthew B. Blaschko, Jacquelyn A. Shelton, Andreas M. Bartels, Christoph H. Lampert, Arthur Gretton:
Semi-supervised kernel canonical correlation analysis with application to human fMRI. Pattern Recognit. Lett. 32(11): 1572-1583 (2011) - [j7]Oliver Kroemer, Christoph H. Lampert, Jan Peters:
Learning Dynamic Tactile Sensing With Robust Vision-Based Training. IEEE Trans. Robotics 27(3): 545-557 (2011) - [c31]Chao Chen, Daniel Freedman, Christoph H. Lampert:
Enforcing topological constraints in random field image segmentation. CVPR 2011: 2089-2096 - [c30]Novi Quadrianto, Christoph H. Lampert:
Learning Multi-View Neighborhood Preserving Projections. ICML 2011: 425-432 - [c29]Zhikun Wang, Christoph H. Lampert, Katharina Mülling, Bernhard Schölkopf, Jan Peters:
Learning anticipation policies for robot table tennis. IROS 2011: 332-337 - [c28]Christoph H. Lampert:
Maximum Margin Multi-Label Structured Prediction. NIPS 2011: 289-297 - 2010
- [j6]Tinne Tuytelaars, Christoph H. Lampert, Matthew B. Blaschko, Wray L. Buntine:
Unsupervised Object Discovery: A Comparison. Int. J. Comput. Vis. 88(2): 284-302 (2010) - [j5]Sebastian Nowozin, Christoph H. Lampert:
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness. SIAM J. Imaging Sci. 3(4): 1048-1074 (2010) - [c27]Christoph H. Lampert:
An efficient divide-and-conquer cascade for nonlinear object detection. CVPR 2010: 1022-1029 - [c26]Kevin D. Tang, Marshall F. Tappen, Rahul Sukthankar, Christoph H. Lampert:
Optimizing one-shot recognition with micro-set learning. CVPR 2010: 3027-3034 - [c25]Sebastian Nowozin, Peter V. Gehler, Christoph H. Lampert:
On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation. ECCV (6) 2010: 98-111 - [c24]Christoph H. Lampert, Oliver Krömer:
Weakly-Paired Maximum Covariance Analysis for Multimodal Dimensionality Reduction and Transfer Learning. ECCV (2) 2010: 566-579 - [c23]Jens Kober, Katharina Mülling, Oliver Kroemer, Christoph H. Lampert, Bernhard Schölkopf, Jan Peters:
Movement templates for learning of hitting and batting. ICRA 2010: 853-858 - [c22]Jörn Wanke, Adrian Ulges, Christoph H. Lampert, Thomas M. Breuel:
Topic models for semantics-preserving video compression. Multimedia Information Retrieval 2010: 275-284
2000 – 2009
- 2009
- [j4]Christoph H. Lampert:
Kernel Methods in Computer Vision. Found. Trends Comput. Graph. Vis. 4(3): 193-285 (2009) - [j3]Christoph H. Lampert, Matthew B. Blaschko:
Structured prediction by joint kernel support estimation. Mach. Learn. 77(2-3): 249-269 (2009) - [j2]Christoph H. Lampert, Matthew B. Blaschko, Thomas Hofmann:
Efficient Subwindow Search: A Branch and Bound Framework for Object Localization. IEEE Trans. Pattern Anal. Mach. Intell. 31(12): 2129-2142 (2009) - [c21]Matthew B. Blaschko, Christoph H. Lampert:
Object Localization with Global and Local Context Kernels. BMVC 2009: 1-11 - [c20]Paramveer S. Dhillon, Sebastian Nowozin, Christoph H. Lampert:
Combining appearance and motion for human action classification in videos. CVPR Workshops 2009: 22-29 - [c19]Sebastian Nowozin, Christoph H. Lampert:
Global connectivity potentials for random field models. CVPR 2009: 818-825 - [c18]Christoph H. Lampert, Hannes Nickisch, Stefan Harmeling:
Learning to detect unseen object classes by