Unsupervised object discovery via self-organisation
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Joni-Kristian Kämäräinen | Heikki Kälviäinen | Lasse Lensu | Teemu Kinnunen | J. Kämäräinen | H. Kälviäinen | L. Lensu | T. Kinnunen
[1] Cordelia Schmid,et al. Dataset Issues in Object Recognition , 2006, Toward Category-Level Object Recognition.
[2] Cordelia Schmid,et al. An Affine Invariant Interest Point Detector , 2002, ECCV.
[3] Gabriela Csurka,et al. Visual categorization with bags of keypoints , 2002, eccv 2004.
[4] Timo Honkela,et al. Very Large Two-Level SOM for the Browsing of Newsgroups , 1996, ICANN.
[5] Pietro Perona,et al. One-shot learning of object categories , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] G. Griffin,et al. Caltech-256 Object Category Dataset , 2007 .
[7] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[8] Teuvo Kohonen,et al. The self-organizing map , 1990, Neurocomputing.
[9] Cordelia Schmid,et al. Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).
[10] J. Tenenbaum,et al. A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.
[11] Tinne Tuytelaars,et al. Dense interest points , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[12] Antonio Torralba,et al. LabelMe: A Database and Web-Based Tool for Image Annotation , 2008, International Journal of Computer Vision.
[13] Joni-Kristian Kämäräinen,et al. Making Visual Object Categorization More Challenging: Randomized Caltech-101 Data Set , 2010, 2010 20th International Conference on Pattern Recognition.
[14] Erkki Oja,et al. PicSOM - content-based image retrieval with self-organizing maps , 2000, Pattern Recognit. Lett..
[15] Cristian Sminchisescu,et al. Object recognition as ranking holistic figure-ground hypotheses , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[16] Cordelia Schmid,et al. Indexing Based on Scale Invariant Interest Points , 2001, ICCV.
[17] Jiri Matas,et al. Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..
[18] Alex Holub,et al. Exploiting Unlabelled Data for Hybrid Object Classification , 2005 .
[19] Pietro Perona,et al. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.
[20] Cordelia Schmid,et al. A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[21] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[22] Jitendra Malik,et al. Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[23] Pietro Perona,et al. Recognition of planar object classes , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[24] Bernt Schiele,et al. Local features for object class recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[25] Alexei A. Efros,et al. Unsupervised discovery of visual object class hierarchies , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[26] Frédéric Jurie,et al. Creating efficient codebooks for visual recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[27] Christopher Hunt,et al. Notes on the OpenSURF Library , 2009 .
[28] Pietro Perona,et al. Unsupervised Learning of Models for Recognition , 2000, ECCV.
[29] Samuel Kaski,et al. Self organization of a massive document collection , 2000, IEEE Trans. Neural Networks Learn. Syst..
[30] I. Biederman. Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.
[31] Daphna Weinshall,et al. Efficient Learning of Relational Object Class Models , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[32] Joni-Kristian Kämäräinen,et al. Bag-of-Features Codebook Generation by Self-Organisation , 2009, WSOM.
[33] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[34] Jianguo Zhang,et al. The PASCAL Visual Object Classes Challenge , 2006 .
[35] Cordelia Schmid,et al. A Comparison of Affine Region Detectors , 2005, International Journal of Computer Vision.
[36] Luc Van Gool,et al. The 2005 PASCAL Visual Object Classes Challenge , 2005, MLCW.
[37] Patrick J. F. Groenen,et al. Modern Multidimensional Scaling: Theory and Applications , 2003 .
[38] Pietro Perona,et al. Unsupervised learning of visual taxonomies , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[39] Christoph H. Lampert,et al. Unsupervised Object Discovery: A Comparison , 2010, International Journal of Computer Vision.