2024
J. Paplham, V. Franc. A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024. (PDF,Bibtex)
P. Daniel, V. Franc. Constrained Binary Decision Making. In Advances in Neural Information Processing Systems (NeurIPS), 2024. (PDF,Bibtex)
V. Franc, J. Paplham, D. Prusa. SCOD: From Heuristics to Theory. arXiv, 2024. (PDF,Bibtex)
V. Franc, J. Paplham, D. Prusa. SCOD: From Heuristics to Theory. In The 18th European Conference on Computer Vision (ECCV), 2024. (PDF,Bibtex)
2023
J. Paplham, V. Franc. Unraveling the Age Estimation Puzzle: Comparative Analysis of Deep Learning Approaches for Facial Age Estimation. arXiv, 2023. (PDF,Bibtex)
V. Franc, D. Prusa, J. Paplham. Reject option models comprising out-of-distribution detection. arXiv, 2023. (PDF,Bibtex)
J. Paplham, V. Franc. Detection of Microscopic Fungi and Yeast in Clinical Samples Using Fluorescence Microscopy and Deep Learning. In Proc. of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2023. (PDF,Bibtex)
V. Franc, D. Prusa, V. Voracek. Optimal Strategies for Reject Option Classifiers. Journal of Machine Learning Research, 2023. (PDF,Bibtex)
2022
V. Franc, P. Daniel, A. Yermakov. Consistent and Tractable Algorithm for Markov Network Learning. In Proc. of European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), 2022. (PDF,Bibtex)
2021
A. Yermakov, V. Franc. CNN Based Predictor of Face Image Quality. In Pattern Recognition. ICPR International Workshops and Challenges, 2021. (PDF,Bibtex)
V. Franc, A. Yermakov. Learning Maximum Margin Markov Networks from examples with missing labels. In Proceedings of The 13th Asian Conference on Machine Learning, 2021. (PDF,Bibtex)
A. Subrtova, J. Cech, V. Franc. Hairstyle Transfer between Face Images. In 16th IEEE International Conference on Automatic Face and Gesture Recognition, 2021. (PDF,Bibtex)
V. Franc, D. Prusa, V. Voracek. Optimal strategies for reject option classifiers. arXiv, 2021. (PDF,Bibtex)
V. Franc, A. Yermakov. Dominant subject recognition by Bayesian learning. In 16th IEEE International Conference on Automatic Face and Gesture Recognition, 2021. (PDF,Bibtex)
2020
J. Brabec, T. Komarek, V. Franc, L. Machlica. On Model Evaluation Under Non-constant Class Imbalance. In Computational Science -- ICCS 2020, 2020. (PDF,Bibtex)
J. Brabec, T. Komarek, V. Franc, L. Machlica. On Model Evaluation under Non-constant Class Imbalance. arXiv, 2020. (PDF,Bibtex)
2019
V. Franc, D. Prusa. On Discriminative Learning of Prediction Uncertainty. In Proc. of Machine Learning Research -- International Conference on Machine Learning, 2019. (PDF,Bibtex)
2018
V. Vasek, V. Franc, M. Urban. License Plate Recognition and Super-resolution from Low-Resolution Videos by Convolutional Neural Networks. In Proc. of British Machine Vision Conference, 2018. (PDF,Bibtex)
V. Franc, J. Cech. Learning CNNs from Weakly Annotated Facial Images. Image and Vision Computing, 2018. (PDF,Bibtex)
V. Franc, O. Fikar, K. Bartos, M. Sofka. Learning data discretization via convex optimization. Machine Learning, 2018. (PDF,Bibtex)
R. Spetlik, V. Franc, J. Cech, J. Matas. Visual Heart Rate Estimation with Convolutional Neural Network. In Proc. of British Machine Vision Conference, 2018. (PDF,Bibtex)
2017
R. Spetlik, J. Cech, V. Franc, J. Matas. Visual Language Identification from Facial Landmarks. In Proc. of Scandinavian Conference on Image Analysis, 2017. (PDF,Bibtex)
V. Franc, J. Cech. Learning CNNs for face recognition from weakly annotated images. In Proc. of International Conference on Automatic Face and Gesture Recognition Workshops, Biometrics in the Wild (BWILD), 2017. (PDF,Bibtex)
2016
V. Franc, O. Fikar, K. Bartos, M. Sofka. Learning data discretization via convex optimization. Research report, Center for Machine Perception, K13133 FEE Czech Technical University, 2016. (PDF,Bibtex)
J. Cech, V. Franc, M. Uricar, J. Matas. Multi-view facial landmark detection by using a 3D shape model. Image and Vision Computing, 2016. (PDF,Bibtex)
K. Bartos, M. Sofka, V. Franc. Optimized Invariant Representation of Network Traffic for Detecting Unseen Malware Variants. In USENIX security symposium, 2016. (PDF,Bibtex)
M. Uricar, V. Franc, D. Thomas, A. Sugimoto, V. Hlavac. Multi-view facial landmark detector learned by the Structured Output SVM. Image and Vision Computing, 2016. (PDF,Bibtex)
2015
V. Franc, M. Sofka, K. Bartos. Learning Detector of Malicious Network Traffic from Weak Labels. In Proc. of European Conference on Machine Learning and Practice of Knowledge Discovery in Databases (ECML PKDD), 2015. (PDF,Bibtex)
K. Antoniuk, V. Franc, V. Hlavac. Consistency of structured output learning with missing labels. In Proc. of Asian Conference on Machine Learning (ACML), 2015. (PDF,Bibtex) BEST STUDENT PAPER + FIRST RUNNER UP
M. Uricar, V. Franc, D. Tomas, A. Sugimoto, V. Hlavac. Real-time Multi-view Facial Landmark Detector Learned by the Structured Output SVM. In Proc. of International Conference on Automatic Face and Gesture Recognition Workshops, Biometrics in the Wild (BWILD), 2015. (PDF,Bibtex)
2014
V. Franc, K. Bartos, M. Sofka, P. Somol, J. Matas. Learning detector of malicious network communication from data. Research report, Center for Machine Perception, K13133 FEE Czech Technical University, 2014. (Bibtex)
J. Cech, V. Franc, J. Matas. A 3D Approach to Facial Landmarks: Detection, Refinement, and Tracking. In Proc. of International Conference on Pattern Recognition (ICPR), 2014. (PDF,Bibtex)
K. Antoniuk, V. Franc, V. Hlavac. Interval Insensitive Loss for Ordinal Classification. In Proc. of Asian Conference on Machine Learning (ACML), 2014. (PDF,Bibtex)
V. Franc. FASOLE: Fast Algorithm for Structured Output LEarning. In Proc. of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2014. (PDF,Bibtex)
2013
K. Antoniuk, V. Franc, V. Hlavac. MORD: Multi-class Classifier for Ordinal Regression. In Proc. of European Conference on Machine Learning and Practice of Knowledge Discovery in Databases (ECML PKDD), 2013. (PDF,Bibtex)
H. Cevikalp, B. Triggs, V. Franc. Face and Landmark Detection by Using Cascade of Classifiers. In Proc. of IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2013. (PDF,Bibtex)
X. Alameda-Pineda, J. Sanchez-Riera, J. Wienke, V. Franc, J. Cech, K. Kulkarni, A. Delaforge, R. Horaud. RAVEL: an annotated corpus for training robots with audiovisual abilities. Journal on Multimodal User Inteface, 2013. (PDF,Bibtex)
R. Sara, M. Matousek, V. Franc. RANSACing Optical Image Sequences for GEO and near-GEO Objects. In Proc. of the Advanced Maui Optical and Space Surveillance Technologies Conference (AMOS), 2013. (PDF,Bibtex)
M. Uricar, V. Franc, V. Hlavac. Facial Landmarks Detector Learned by the Structured Output SVM. Computer Vision, Imaging and Computer Graphics. Theory and Application, 2013. (PDF,Bibtex)
M. Uricar, V. Franc, V. Hlavac. Bundle Methods for Structured Output Learning --- Back to the Roots. In Proc. of Scandinavian Conference on Image Analysis (SCIA), 2013. (PDF,Bibtex)
2012
V. Franc, S. Sonnenburg, T. Werner. Cutting-Plane Methods in Machine Learning. The MIT Press, Optimization for Machine Learning, 2012. (PDF,Bibtex)
M. Uricar, V. Franc. Efficient Algorithm for Regularized Risk Minimization. In Proc. of the Computer Vision Winter Workshop (CVWW), 2012. (PDF,Bibtex)
V. Franc, K. Antoniuk, M. Uricar. Discriminative structured output learning from partially annotated examples. Research report, Center for Machine Perception, K13133 FEE Czech Technical University, 2012. (PDF,Bibtex)
K. Antoniuk, V. Franc, V. Hlavac. Learning Markov Networks by Analytic Center Cutting Plane Method. In Proc. of International Conference on Pattern Recognition (ICPR), 2012. (PDF,Bibtex)
M. Uricar, V. Franc. Bundle Method for Structured Output Learning. Research report, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University, 2012. (PDF,Bibtex)
X. Alameda-Pineda, J. Sanchez-Riera, J. Wienke, V. Franc, J. Cech, K. Kulkarni, A. Deleforge, R. Horaud. RAVEL: An Annotated Corpus for Training Robots with Audiovisual Abilities. Research report, INRIA Rhone-Alpes, 2012. (PDF,Bibtex)
M. Uricar, V. Franc, V. Hlavac. Detector of Facial Landmarks Learned by the Structured Output SVM. In Proc. of the International Conference on Computer Vision Theory and Applications (VISAPP), 2012. (PDF,Bibtex) BEST STUDENT PAPER
2011
V. Franc, P. Laskov. Learning Maximal Margin Markov Networks via Tractable Convex Optimization. Control Systems and Computers, 2011. (PDF,Bibtex)
V. Franc, A. Zien, B. Schoelkopf. Support Vector Machines as Probabilistic Models. In Proc. of the International Conference on Machine Learning (ICML), 2011. (PDF,Bibtex)
2010
S. Sonnenburg, V. Franc. COFFIN: A Computational Framework for Linear SVMs. In Proc. of the Annual International Conference on Machine Learning (ICML), 2010. (PDF,Bibtex)
S. Sonnenburg, G. Raetsch, S. Henschel, C. Widmer, J. Behr, A. Zien, F. de~Bona, A. Binder, C. Gehl, V. Franc. The SHOGUN Machine Learning Toolbox. Journal of Machine Learning Research, 2010. (PDF,Bibtex)
V. Franc. Algoritmus pro minimalizaci regularizovan\' eho rizika. In Anal\' yza dat 2010/II, Statistick\' e metody pro technologii a v\' yzkum, 2010. (Bibtex)
2009
S. Sonnenburg, V. Franc. COFFIN: A Computational Framework for Linear SVMs. Research report, Center for Machine Perception, K13133 FEE Czech Technical University, 2009. (PDF,Bibtex)
V. Franc, S. Sonneburg. Optimized Cutting Plane Algorithm for Large-Scale Risk Minimization. Journal of Machine Learning Research, 2009. (PDF,Bibtex)
2008
V.Franc, S. Sonnenburg. Optimized cutting plane algorithm for support vector machines. In Proc. of the International Conference on Machine Learning (ICML), 2008. (PDF,Bibtex)
J. Rathousky, M. Urban, V. Franc. Recognition of Text with Known Geometric and Grammatical Structure. In Proc. of the International Conference on Computer Vision Theory and Applications (VISAPP), 2008. (PDF,Bibtex)
V.Franc, P. Laskov, K. Mueller. Stopping conditions for exact computation of leave-one-out error in support vector machines. In Proc. of the International Conference on Machine Learning (ICML), 2008. (PDF,Bibtex)
V. Franc, B. Savchynskyy. Discriminative Learning of Max-Sum Classifiers. Journal of Machine Learning Research, 2008. (PDF,Bibtex)
2006
V. Franc, V. Hlavac. Greedy Kernel Principal Component Analysis. In Cognitive Vision Systems, 2006. (Bibtex)
V. Franc, V. Hlavac. A Novel Algorithm for Learning Support Vector Machines with Structured Output Spaces. Research report, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University, 2006. (PDF,Bibtex)
2005
V. Franc, V. Hlavac, M. Navara. Sequential Coordinate-Wise Algorithm for the Non-negative Least Squares Problem. In Proc. of the International Conference on Computer Analysis of Images and Patterns (CAIP), 2005. (PDF,Bibtex)
V. Franc, V. Hlavac. Simple Solvers for Large Quadratic Programming Tasks. In Proc. of the Deutsche Arbeitsgemeinschaft fur Mustererkennung (DAGM), 2005. (PDF,Bibtex)
V. Franc, M. Navara, V. Hlavac. Sequential Coordinate-wise Algorithm for Non-negative Least Squares Problem. Research report, Center for Machine Perception, K13133 FEE Czech Technical University, 2005. (PDF,Bibtex)
V. Franc, V. Hlavac. License Plate Character Segmentation Usint Hidden Markov Chains. In Proc. of the Deutsche Arbeitsgemeinschaft fur Mustererkennung (DAGM), 2005. (PDF,Bibtex)
V. Franc. Optimization Algorithms for Kernel Methods. PhD thesis, Center for Machine Perception, K13133 FEE Czech Technical University, 2005 (PDF,Bibtex)
2004
V. Franc, V. Hlavac. Statistical Pattern Recognition Toolbox for Matlab. Research report, Center for Machine Perception, K13133 FEE Czech Technical University, 2004. (PDF,Bibtex)
2003
D. De Ridder, V. Franc. Robust Manifold Learning. Research report, Center for Machine Perception, K13133 FEE Czech Technical University, 2003. (PDF,Bibtex)
V. Franc, V. Hlavac. An iterative algorithm learning the maximal margin classifier. Pattern recognition, 2003. (PDF,Bibtex)
D. De Ridder, V. Franc. Rubust subspace mixture models using \(t\)-distributions. In Proc. of the British Machine Vision Conference (BMVC), 2003. (Bibtex)
V. Franc, V. Hlavac. Training Set Approximation for Kernel Methods. In Proc. of the Computer Vision Winter Workshop (CVWW), 2003. (PDF,Bibtex)
V. Franc, V. Hlavac. Greedy Algorithm for a Training Set Reduction in the Kernel Methods. In Computer Analysis of Images and Patterns (CAIP), 2003. (PDF,Bibtex)
2002
V. Franc, J. Matas. An extension of the component-based LDA descriptor by the Generalized Discriminant Analysis. Research report, ISO/IEC JTC 1/SC 29/WG 11 Moving Picture Experts Group, 2002. (Bibtex)
V. Franc, V. Hlavac. Multi-class Support Vector Machine. In Proc. of the International Conference on Pattern Recognition (ICPR), 2002. (PDF,Bibtex)
V. Franc, V. Hlavac. Kernel representation of the Kesler construction for Multi-class SVM classification. In Proc. of the Computer Vision Winter Workshop (CVWW), 2002. (PDF,Bibtex)
V. Franc, V. Hlavac, M. Navara. Global convergence of the EM algorithm for a conditionally independent statistical model and two hidden states. Research report, Center for Machine Perception, K333 FEE Czech Technical University, 2002. (Bibtex)
2001
V. Franc, V. Hlavac. A Simple Learning Algorithm for Maximal Margin Classifier. In Proc. of Kernel and Subspace Methods for Computer Vision Workshop, 2001. (PDF,Bibtex)
V. Franc, V. Hlavac. A new feature of the Statistical Pattern Recognition Toolbox. In Computer Vision, Computer Graphics and Photogrammetry -- a Common Viewpoint, 2001. (PDF,Bibtex)
V.Franc, V.Hlavac. A new feature of the Statistical Pattern Recognition Toolbox. Telematik, 2001. (Bibtex)
V. Franc, V. Hlavac. A Contribution to the Schlesinger's Algorithm Separating Mixtures of Gaussians. In Proc of. the International Conference on Computer Analysis of Images and Patterns (CAIP), 2001. (PDF,Bibtex) BEST STUDENT PAPER
2000
V.Franc. Programove nastroje pro rozpoznavani (Pattern Recognition Programming Tools, In Czech). MSc thesis, Center for Machine Perception, K13133 FEE Czech Technical University, 2000 (PDF,Bibtex)
V.Franc, V.Hlavac, M. Schlesinger. Linear and quadratic classification toollbox for Matlab. In Proc. of the Czech Pattern Recognition Workshop, 2000. (PDF,Bibtex)
1998
J.Fojtik, J.Cada, J.Dostal, V.Franc, L.Rothkrantz, V.Hlavac. Profile Face Analysis Based on Edge Detection. Research report, TU Delft, 1998. (Bibtex)