CLASS Publications

This page lists the publications associated with CLASS. If you can't find something here, it may be available on one of the partner's web sites.

Year 1

• WP 2
• [1] Matthew B. Blaschko and Thomas Hofmann. Conformal multi-instance kernels. In NIPS 2006 Workshop on Learning to Compare Examples, 2006. [PDF]
• [2] Peter V. Gehler and Olivier Chapelle. Deterministic annealing for multiple instance learning. In Eleventh International Conference on Artificial Intelligence and Statistics, 2007.[PDF]
• [3] Koen Deschacht and Marie-Francine Moens. Efficient hierarchical entity classification using conditional random fields. In Proceedings of the 18th Belgian-Dutch Conference on Artificial Intelligence, pages 369-370, Namur, October 2006.[PDF]
• [4] Koen Deschacht and Marie-Francine Moens. Efficient hierarchical entity classification using conditional random fields. In Proceedings of the 2nd Workshop on Ontology Learning and Population, pages 33-40, Sydney, July 2006. [PDF]
• [5] K. Deschacht, M.-F. Moens, and W. Robeyns. Cross-media entity recognition in nearly parallel visual and textual documents. In 8th RIAO Conference on Large-Scale Semantic Access to Content (Text, Image, Video and Sound). CMU, 2007. [PDF]
• [6] Koen Deschacht and Marie-Francine Moens. Text analysis for automatic image annotation. Submitted to the 45th Annual Meeting of the Association for Computational Linguistics, Prague, June 2007.[PDF]
• [7] X. Tan and B. Triggs. Preprocessing and feature sets for robust face recognition. Technical report (originally submitted to CVPR 2007, December 2006). [PDF]
• [8] A. Opelt, A. Pinz, and A. Zisserman. Incremental learning of object detectors using a visual shape alphabet. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 2006. [PDF]
• [9] A. Opelt, A. Pinz, and A. Zisserman. Fusing shape and appearance information for object category detection. In Proceedings of the British Machine Vision Conference, September 2006. [PDF]
• WP 3
• [10] Till Quack, Vittorio Ferrari, and Luc Van Gool. Video mining with frequent itemset configurations. In CIVR, pages 360-369, 2006.[PDF]
• [11] Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku Kudo, and Gokhan BakIr. Weighted substructure mining for image analysis. Submitted to CVPR'07, Minneapolis, Minnesota, USA, 2007. (Not available online).
• [12] Joost van de Weijer, Cordelia Schmid, and Jacob Verbeek. Learning color names from real-world images. In CVPR'07, Minneapolis, Minnesota, USA, 2007. [PDF]
• [13] J. Verbeek and B. Triggs. Region classification with markov field aspect models. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 2007. [PDF]
• [14] B. C. Russell, A. A. Efros, J. Sivic,W. T. Freeman, and A. Zisserman. Using multiple segmentations to discover objects and their extent in image collections. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006. [PDF]
• WP 6
• [15] M. Everingham, J. Sivic, and A. Zisserman. "Hello! My name is... Buffy" - automatic naming of characters in TV video. In Proceedings of the 17th British Machine Vision Conference, Edinburgh, pages 889-908, 2006. [PDF]

Year 2

• WP 2
• [1] X. Tan and B. Triggs. Enhanced local texture feature sets for face recognition under difficult lighting conditions. In Analysis and Modelling of Faces and Gestures, volume 4778 of LNCS, pages 168-182. Springer, 2007. [PDF]
• [2] X. Tan and B. Triggs. Fusing Gabor and LBP feature sets for kernel-based face recognition. In Analysis and Modelling of Faces and Gestures, pages 235-249, October 2007. [PDF]
• [3] A. Bosch, A. Zisserman, and X. Munoz. Representing shape with a spatial pyramid kernel. In Proceedings of the International Conference on Image and Video Retrieval, 2007. [PDF]
• [4] A. Bosch, A. Zisserman, and X. Munoz. Image classification using random forests and ferns. In 11th International Conference on Computer Vision, Rio de Janeiro, Brazil, 2007. [PDF]
• [5] A. Bosch, A. Zisserman, and X. Munoz. Scene classification using a hybrid generative/discriminative approach. Submitted to IEEE Trans. Pattern Analysis and Machine Intelligence, 2007. [PDF]
• [6] Koen Deschacht and Marie-Francine Moens. Text analysis for automatic image annotation. In 19th Belgian-Dutch Conference on Artificial Intelligence (BNAIC), pages 343-344, Utrecht, The Netherlands, 2007. Abstract of the ACL paper. [PDF]
• [7] Koen Deschacht and Marie-Francine Moens. Finding the best picture: Cross-media retrieval of content. In 30th European Conference on Information Retrieval (ECIR), Glasgow, Scotland, March 2008. [PDF]
• [8] Matthew B. Blaschko and Christoph H. Lampert. Correlational Spectral Clustering. Submitted to CVPR 2008. (Not yet available online).
• [9] T. Tuytelaars and C. Schmid. Vector quantizing feature space with a regular lattice. In Proceedings of the International Conference on Computer Vision, 2007. [PDF]
• WP 3
• [10] A. Thomas, V. Ferrari, B. Leibe, T. Tuytelaars, and L. Van Gool. Depth-from-recognition: Inferring meta-data by cognitive feedback. Workshop on 3D Representation and Recognition, 2007. [PDF]
• [11] A. Thomas, T. Tuytelaars, V. Ferrari, B. Leibe, and L. Van Gool. Using recognition to guide a robot's attention. Submitted to Robotics: Science and Systems Conference, 2007. (Not yet available online).
• [12] Joost van de Weijer, Cordelia Schmid, and Jacob Verbeek. Learning color names from real-world images. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, Minnesota, USA, 2007. (Final version). [PDF]
• [13] V. Ferrari and A. Zisserman. Learning visual attributes. In Advances in Neural Information Processing Systems, 2007. [PDF]
• [14] T. Quack, V. Ferrari, B. Leibe, and L Van Gool. Efficient mining of frequent and distinctive feature configurations. In Proceedings of the International Conference on Computer Vision, 2007. [PDF]
• [15] Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku Kudo, and Gökhan H. Bakir. Weighted substructure mining for image analysis. In CVPR, 2007. [PDF]
• [16] S. Nowozin, G. Bakir, and K. Tsuda. Discriminative subsequence mining for action classification. In ICCV, pages 1-8, 2007. [PDF]
• [17] M. B. Blaschko, T. Hofmann, and C. H. Lampert. Efficient subwindow search for object localization. Technical Report 164, Max Planck Institute for Biological Cybernetics, 08/2007. [PDF]
• [18] Christoph H. Lampert, Matthew B. Blaschko, and Thomas Hofmann. Beyond Sliding Windows: Object Localization by Efficient Subwindow Search. Submitted to CVPR 2008. (Not yet available online).
• [19] J. Verbeek and B. Triggs. Region classification with Markov field aspect models. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 2007. [PDF]
• [20] J. Verbeek and B. Triggs. Scene segmentation with CRFs learned from partially labeled images. In Advances in Neural Information Processing Systems, December 2007. [PDF]
• [21] Matthew B. Blaschko and Thomas Hofmann. Conformal Multi-Instance Kernels. In NIPS Workshop on Learning to Compare Examples, 2006. [PDF]
• WP 4
• [22] Marcin Marszalek and Cordelia Schmid. Semantic hierarchies for visual object recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2007. [PDF]
• [23] Christoph H. Lampert. Partitioning of image datasets using discriminative context information. Submitted to CVPR 2008. (Not yet available online).
• [24] W. Buntine. An approach to hierarchical discrete component analysis. Internal report on work in progress, 2008. (Not yet available online).
• WP 7
• [25] Wim De Smet and Marie-Francine Moens. Multi-document event detection and summarization. Submitted to ACM SIGIR, 2008. (Not yet available online).

Year 3

• WP 2
• [1] Christoph H. Lampert, Matthew B. Blaschko, and Thomas Hofmann. Beyond sliding windows: Object localization by efficient subwindow search. In Computer Vision and Pattern Recognition (CVPR), 2008. [PDF]
• [2] Matthew B. Blaschko and Christoph H. Lampert. Learning to localize objects with structured output regression. In ECCV, 2008. [PDF]
• [3] Christoph H. Lampert and Matthew B. Blaschko. A multiple kernel learning approach to joint multi-class object detection. In Symposium of the German Pattern Recognition Society (DAGM), 2008. [PDF]
• [4] Christoph H. Lampert, Matthew B. Blaschko, and Thomas Hofmann. Efficient subwindow search: A branch and bound framework for object localization. Pattern Analysis and Machine Intelligence (PAMI), 2009. [PDF]
• [5] Matthew B. Blaschko and Christoph H. Lampert. Object localization with global and local context kernels. In British Machine Vision Conference (BMVC), 2009. [PDF]
• [6] Christoph H. Lampert and Jan Peters. Active structured learning for high-speed object detection. In Symposium of the German Pattern Recognition Society (DAGM), 2009. [PDF]
• [7] Christoph H. Lampert. Detecting objects in large image collections and videos by efficient subimage retrieval. In IEEE International Conference on Computer Vision (ICCV), 2009. [PDF]
• [8] Sebastian Nowozin and Christoph H. Lampert. Global connectivity potentials for random field models. In Computer Vision and Pattern Recognition (CVPR), 2009. [PDF]
• [9] Christoph H. Lampert and Matthew B. Blaschko. Structured prediction by joint kernel support estimation. Machine Learning, 2009. [PDF]
• [10] Phi The Pham, Marie-Francine Moens, and Tinne Tuytelaars. Linking names and faces: seeing the problem in different ways. In ECCV Workshop on Faces in Real-Life Images: Detection, Alignment and Recognition, 2009. [PDF]
• [11] Phi The Pham, Marie-Francine Moens, and Tinne Tuytelaars. Cross-media alignment of names and faces. IEEE Transactions on Multimedia. Accepted, 2009. [PDF]
• [12] X. Tan and B. Triggs. Enhanced local texture feature sets for face recognition under difficult lighting conditions. IEEE Trans. Image Processing. Under revision, July 2009.
• [13] T. Tuytelaars, C. H. Lampert, M. B. Blaschko, and W. Buntine. Unsupervised object discovery: A comparison. International Journal of Computer Vision, 2009. [PDF]
• [14] A. Opelt, A. Pinz, and A. Zisserman. Learning an alphabet of shape and appearance for multi-class object detection. IJCV, 80(1), October 2008. [PDF]
• [15] Matthew B. Blaschko and Christoph H. Lampert. Correlational spectral clustering. In Computer Vision and Pattern Recognition (CVPR), 2008. [PDF]
• [16] Matthew B. Blaschko, Christoph H. Lampert, and Arthur Gretton. Semi-supervised laplacian regularization of kernel canonical correlation analysis. In ECML PKDD, 2008. [PDF]
• [17] Christoph H. Lampert. Partitioning of image datasets using discriminative context partitioning. In Computer Vision and Pattern Recognition (CVPR), 2008. [PDF]
• [18] Sebastian Nowozin and Gökhan Bakir. A decoupled approach to exemplar-based unsupervised learning. In International Conference on Machine Learning (ICML), 2008. [PDF]
• [19] Sebastian Nowozin and Stefanie Jegelka. Solution stability in linear programming relaxations: graph partitioning and unsupervised learning. In International Conference on Machine Learning (ICML), 2009. [PDF]
• WP 3
• [20] Christoph H. Lampert, Hannes Nickisch, and Stefan Harmeling. Learning to detect unseen object classes by between-class attribute transfer. In Computer Vision and Pattern Recognition (CVPR), 2009. [PDF]
• [21] Peter V. Gehler and S. Nowozin. Let the kernel figure it out: Principled learning of pre-processing for kernel classifiers. In Computer Vision and Pattern Recognition (CVPR), 2009. [PDF]
• [22] Peter V. Gehler and Sebastian Nowozin. On feature combination for multiclass object classification. In IEEE International Conference on Computer Vision (ICCV), 2009. [PDF]
• [23] Peter V. Gehler and Sebastian Nowozin. Infinite kernel learning. Technical Report 178, Max-Planck Institute for Biological Cybernetics, 10 2008. [PDF]
• [24] Diane Larlus, Jakob Verbeek, and Frédéric Jurie. Category level object segmentation by combining bag-of-words models with dirichlet processes and random fields. International Journal of Computer Vision, 2009. [PDF]
• [25] Yang Wen and B. Triggs. Scene segmentation via low-dimensional semantic representation and conditional random field. IEEE Trans. Image Processing. Submitted, September 2009.
• [26] Dengxin Dai, Yang Wen, and B. Triggs. SAR image labeling with hierarchical markov aspect models. IEEE Trans. Geoscience and Remote Sensing. Submitted, September 2009.
• [27] Joost van de Weijer, Cordelia Schmid, Jakob Verbeek, and Diane Larlus. Learning color names for real-world applications. IEEE Transactions on Image Processing, 18(7):1512--1523, Jul 2009. [PDF]
• [28] A. Thomas, V. Ferrari, B. Leibe, T. Tuytelaars, and L. Van Gool. Shape-from-recognition: Recognition enables meta-data transfer. Computer Vision and Image Understanding, 2009. [PDF]
• [29] A. Thomas, V. Ferrari, B. Leibe, T. Tuytelaars, and L. Van Gool. Using multi-view recognition and meta-data annotation to guide a robot's attention. International Journal of Robotics Research, 28(8):976--998, 2009. [PDF]
• WP 4
• [30] J. Sivic, B.C Russell, A. Zisserman, W.T. Freeman, and A.A. Efros. Unsupervised discovery of visual object class hierarchies. In IEEE Conference on Computer Vision and Pattern Recognition, 2008. [PDF]
• [31] M. B. Blaschko and A. Gretton. A hilbert-schmidt dependence maximization approach to unsupervised structure discovery. In International Workshop on Mining and Learning with Graphs (MLG), 2008. [PDF]
• [32] Matthew B. Blaschko and Arthur Gretton. Learning taxonomies by dependence maximization. In Advances in Neural Information Processing Systems (NIPS), 2009. [PDF]
• [33] Matthew B. Blaschko and Arthur Gretton. Taxonomy inference using kernel dependence measures. Technical Report 181, Max-Planck Institute for Biological Cybernetics, 11 2008. [PDF]
• [34] W. Buntine. Estimating likelihoods for topic models. In 1st Asian Conference on Machine Learning, 2009. [PDF]
• [35] Jukka Perkiö, Tinne Tuytelaars, and Wray Buntine. Exploring scale-induced feature hierarchies in natural images. In Eighth International Conference on Machine Learning and Applications (ICMLA 2009), Washington, DC, USA, 2009. IEEE Computer Society. [PDF]
• [36] P. Zehnder, E. Koller-Meier, and L. Van Gool. An efficient shared multi-class detection cascade. In British Machine Vision Conference, 2008. [PDF]
• [37] Marcin Marszalek and Cordelia Schmid. Constructing category hierarchies for visual recognition. In European Conference on Computer Vision, pages IV 479--491, 2008. [PDF]
• [38] Koen Deschacht and Marie-Francine Moens. The latent words language model. In 18th Annual Belgian-Dutch Conference on Machine Learning (Benelearn 09), 2009. [PDF]
• [39] Koen Deschacht and Marie-Francine Moens. Semi-supervised semantic role labeling using the latent words language model. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing (EMNLP 2009). Association for Computational Linguistics, 2009. [PDF]
• [40] A. Vedaldi, V. Gulshan, M. Varma, and A. Zisserman. Multiple kernels for object detection. In International Conference on Computer Vision, 2009. [PDF]
• WP 5
• [41] M. Guillaumin, T. Mensink, J. Verbeek, and C. Schmid. Automatic face naming with caption-based supervision. In CVPR, 2008. [PDF]
• [42] T. Mensink and J. Verbeek. Improving people search using query expansions: How friends help to find people. In ECCV, 2008. [PDF]
• [43] M. Allan and J. Verbeek. Ranking user-annotated images for multiple query terms. In BMVC, 2009. [PDF]
• [44] Matthieu Guillaumin, Jakob Verbeek, and Cordelia Schmid. Is that you? metric learning approaches for face identification. In International Conference on Computer Vision, sep 2009. [PDF]
• [45] M. Guillaumin, T. Mensink, J. Verbeek, and C. Schmid. Tagprop: Discriminative metric learning in nearest neighbor models for image auto-annotation. In ICCV, 2009. [PDF]
• WP 6
• [46] M. Everingham, J. Sivic, and A. Zisserman. Taking the bite out of automatic naming of characters in TV video. Image and Vision Computing, 27(5), 2009. [PDF]
• [47] J. Sivic, M. Everingham, and A. Zisserman. ``Who are you?'' -- Learning person specific classifiers from video. In IEEE Conference on Computer Vision and Pattern Recognition, 2009. [PDF]
• [48] J. Zhu, L. Van Gool, and S. C. Hoi. Unsupervised face alignment by robust nonrigid mapping. In ICCV, September 2009. [PDF]
• [49] H. Wang, M. M. Ullah, A. Kläser, I. Laptev, and C. Schmid. Evaluation of local spatio-temporal features for action recognition. In BMVC, 2009. [PDF]
• [50] A. Kläser, M. Marszalek, and C. Schmid. A spatio-temporal descriptor based on 3D-gradients. In BMVC, 2008. [PDF]
• [51] G. Willems, J.H. Becker, T. Tuytelaars, and L. Van Gool. Exemplar-based action recognition in video. In British Machine Vision Conference, 2009. [PDF]
• [52] G. Willems, T. Tuytelaars, and L. Van Gool. An efficient dense and scale-invariant spatio-temporal interest point detector. In European Conference on Computer Vision, 2008. [PDF]
• [53] A. Gaidon, M. Marszalek, and C. Schmid. Mining visual actions from movies. In BMVC, 2009. [PDF]
• [54] M. Marszalek, I. Laptev, and C. Schmid. Actions in context. In CVPR, 2009. [PDF]
• [55] V. Ferrari, M. Marin-Jimenez, and A. Zisserman. Progressive search space reduction for human pose estimation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 2008. [PDF]
• [56] V. Ferrari, M. Marin-Jimenez, and A. Zisserman. Pose search: retrieving people using their pose. In IEEE Conference on Computer Vision and Pattern Recognition, 2009. [PDF]
• [57] P. Sankar, C. V. Jawahar, and A. Zisserman. Subtitle-free movie to script alignment. In Proceedings of the British Machine Vision Conference, 2009. [PDF]
• [58] Jukka Perkiö, Antti Tuominen, and Petri Myllymäki. Image similarity: From syntax to weak semantics using multimodal features with application to multimedia retrieval. In 2009 International Conference on Multimedia Information NEtworking and Security, Washington, DC, USA, 2009. IEEE Computer Society. [PDF]
• WP 7
• [59] Gerardus Poulisse and Marie-Francine Moens. Multimodal news story segmentation. In First International Conference on Intelligent Human Computer Interaction (IHCI 2009), pages 95--101. Springer, 2009. [PDF]
• [60] Gerardus Poulisse, Marie-Francine Moens, and Tomas Dekens. News story segmentation in multiple modalities. In 7th International Workshop on Content-based Multimedia Indexing, pages 26--32. IEEE Computer Society Press, 2009. [PDF]
• [61] Gert-Jan Poulisse, Marie-Francine Moens, Tomas Dekens, and Koen Deschacht. News story segmentation in multiple modalities. Multimedia Tools and Applications. In press. [PDF]
• [62] Wim De Smet and Marie-Francine Moens. Cross-language linking of news stories on the web using interlingual topic modelling. In Proceedings of the 2nd Workshop on Social Web Search and Mining (SWSM 2009) at CIKL 2009. ACM, 2009. [PDF]
• [63] N. Quadrianto, A.J. Smola, L. Song, and T. Tuytelaars. Kernelized sorting. IEEE Transactions on Pattern Analysis and Machine Intelligence. In press. [PDF]
• [64] Wim De Smet and Marie-Francine Moens. An aspect based document representation for event clustering. In 19th Meeting of Computational Linguistics in The Netherlands, 2009. [PDF]

Available PHD Theses

• [1] M. B. Blaschko. Kernel Methods in Computer Vision: Object Localization, Clustering, and Taxonomy Discovery. PhD thesis, Technische Universität Berlin, Germany. March 2009. [PDF]
• [2] P. V. Gehler. Kernel Learning Approaches for Image Classification. PhD thesis, Universität des Saarlandes, Saarbrücken, Germany. June 2009. [PDF]

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Contact: Bill Triggs (coordinator), Bill.Triggs@imag.fr, phone +33 4 7651 4553
Laboratoire Jean Kuntzmann, 51 rue des Mathematiques, 38402 Saint Martin d'Heres, Grenoble, France