Alexe, B., Deselaers, T., & Ferrari, V. (2010a). ClassCut for unsupervised class segmentation. In ECCV.
Alexe, B., Deselaers, T., & Ferrari, V. (2010b). What is an object? In CVPR.
Alexe, B., Deselaers, T., & Ferrari, V. (2012). Measuring the objectness of image windows. IEEE Transactions on Pattern Analysis and Machine Intelligence.
Andrews, S., Tsochantaridis, I., & Hofmann, T. (2002). Support vector machines for multiple-instance learning. In NIPS.
Arora, H., Loeff, N., Forsyth, D., & Ahuja, N. (2007). Unsupervised segmentation of objects using efficient learning. In CVPR.
Babenko, B., Branson, S., & Belongie, S. (2009). Similarity metrics for categorization: From monolithic to category specific. In ICCV.
Bagon, S., Brostovski, O., Galun, M., & Irani, M. (2010). Detecting and sketching the common. In CVPR.
Bay, H., Ess, A., Tuytelaars, T., & van Gool, L. (2008). SURF: speeded up robust features. In CVIU.
Blaschko, B., Vedaldi, A., & Zisserman, A. (2010). Simultaneous object detection and ranking with weak supervision. In NIPS.
Borenstein, E., & Ullman, S. (2004). Learning to segment. In ECCV.
Cao, L., & Li, F. F. (2007). Spatially coherent latent topic model for concurrent segmentation and classification of objects and scene. In ICCV.
Carreira, J., Li, F., & Sminchisescu, C. (2010). Constrained parametric min cuts for automatic object segmentation. In CVPR.
Chen, Y., Bi, J., & Wang, J. Z. (2006). MILES: multiple-instance learning via embedded instance selection.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
28(12), 1931–1947.
CrossRef
Chum, O., & Zisserman, A. (2007). An exemplar model for learning object classes. In CVPR.
Crandall, D. J., & Huttenlocher, D. (2006). Weakly supervised learning of part-based spatial models for visual object recognition. In ECCV.
Dalal, N., & Triggs, B. (2005). Histogram of Oriented Gradients for human detection. In CVPR.
Deselaers, T., & Ferrari, V. (2010). A conditional random field for multiple-instance learning. In ICML.
Deselaers, T., Alexe, B., & Ferrari, V. (2010). Localizing objects while learning their appearance. In ECCV.
Dorkó, G., & Schmid, C. (2005). Object class recognition using discriminative local features. Tech. Rep. RR-5497, INRIA, Rhone-Alpes.
Endres, I., & Hoiem, D. (2010). Category independent object proposals. In ECCV.
Everingham, M., Van Gool, L., Williams, C. K. I., & Zisserman, A. (2006). The PASCAL Visual Object Classes Challenge 2006 (VOC2006).
http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2006/.
Everingham, M., Van Gool, L., Williams, C., Winn, J., & Zisserman, A. (2007). The PASCAL Visual Object Classes Challenge 2007 Results.
Everingham, M., et al. (2010). The PASCAL Visual Object Classes Challenge 2010 Results.
Fei-Fei, L., Fergus, R., & Perona, P. (2003). A bayesian approach to unsupervised one-shot learning of object categories. In ICCV (pp. 1134–1141).
Fei-Fei, L., Fergus, R., & Perona, P. (2004). Learning generative visual models from few training examples: an incremental bayesian approach tested on 101 object categories. In CVPR workshop of generative model based vision.
Felzenszwalb, P., Girshick, R., McAllester, D., & Ramanan, D. (2010). Object detection with discriminatively trained part based models.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
32(9), 1627–1645.
CrossRef
Fergus, R., Perona, P., & Zisserman, A. (2003). Object class recognition by unsupervised scale-invariant learning. In CVPR.
Finley, T., & Joachims, T. (2008). Training structural svms when exact inference is intractable. In ICML.
Fritz, M., & Schiele, B. (2006). Towards unsupervised discovery of visual categories. In DAGM.
Frome, A., Singer, Y., Sha, F., & Malik, J. (2007). Learning globally-consistent local distance functions for shape-based image retrieval and classification. In ICCV.
Gaidon, A., Marszalek, M., & Schmid, C. (2009). Mining visual actions from movies. In BMVC.
Galleguillos, C., Babenko, B., Rabinovich, A., & Belongie, S. (2008). Weakly supervised object localization with stable segmentations. In ECCV.
Grauman, K., & Darrell, T. (2006). Unsupervised learning of categories from sets of partially matching image features. In CVPR.
Kim, G., & Torralba, A. (2009). Unsupervised detection of regions of interest using iterative link analysis. In NIPS.
Kolmogorov, V. (2006a). Convergent tree-reweighted message passing for energy minimization.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
28(10), 1568–1583.
CrossRef
Kolmogorov, V. (2006b). Convergent tree-reweighted message passing for energy minimization.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
28(10), 1568–1583.
CrossRef
Lampert, C., Nickisch, H., & Harmeling, S. (2009a). Learning to detect unseen object classes by between-class attribute transfer. In CVPR.
Lampert, C. H., Blaschko, M. B., & Hofmann, T. (2009b). Efficient subwindow search: A branch and bound framework for object localization.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
31(12), 2129–2142.
CrossRef
Lando, M., & Edelman, S. (1995). Generalization from a single view in face recognition. (technical report cs-tr 95-02). The Weizmann Institute of Science.
Lee, Y., & Grauman, K. (2009a). Shape discovery from unlabeled image collections. In CVPR.
Lee, Y. J., & Grauman, K. (2009b). Foreground focus: unsupervised learning from partially matching images.
International Journal of Computer Vision,
85, 143–166.
CrossRef
Malisiewicz, T., & Efros, A. A. (2008). Recognition by association via learning per-exemplar distances. In CVPR.
Nguyen, M., Torresani, L., de la Torre, F., & Rother, C. (2009). Weakly supervised discriminative localization and classification: a joint learning process. In ICCV.
Nowak, E., & Jurie, F. (2007). Learning visual similarity measures for comparing never seen objects. In CVPR.
Oliva, A., & Torralba, A. (2001). Modeling the shape of the scene: a holistic representation of the spatial envelope.
International Journal of Computer Vision,
42(3), 145–175.
MATHCrossRef
Payet, N., & Todorovic, S. (2010). From a set of shapes to object discovery. In ECCV.
Quattoni, A., Collins, M., & Darrell, T. (2008). Transfer learning for image classification with sparse prototype representations. In CVPR.
Raina, R., Battle, A., Lee, H., Packer, B., & Ng, A. (2007). Self-taught learning: transfer learning from unlabeled data. In ICML.
Ramanan, D. (2006). Learning to parse images of articulated bodies. In NIPS.
Rohrbach, M., Stark, M., Szarvas, G., Gurevych, I., & Schiele, B. (2010). What helps where—and why? semantic relatedness for knowledge transfer. In CVPR.
Rother, C., Kolmogorov, V., & Blake, A. (2004). Grabcut: interactive foreground extraction using iterated graph cuts. Computer Graphics, 23(3), 309–314.
Russel, B. C., & Torralba, A. (2008). LabelMe: a database and web-based tool for image annotation.
International Journal of Computer Vision,
77(1–3), 157–173.
CrossRef
Russell, B. C., Efros, A. A., Sivic, J., Freeman, W. T., & Zisserman, A. (2006). Using multiple segmentations to discover objects and their extent in image collections. In CVPR.
Stark, M., Goesele, M., & Schiele, B. (2009). A shape-based object class model for knowledge transfer. In ICCV.
Szummer, M., Kohli, P., & Hoiem, D. (2008). Learning CRFs using graph cuts. In ECCV.
Thrun, S. (1996). Is learning the n-th thing any easier than learning the first? In NIPS.
Todorovic, S., & Ahuja, N. (2006). Extracting subimages of an unknown category from a set of images. In CVPR.
Tommasi, T., & Caputo, B. (2009). The more you know, the less you learn: from knowledge transfer to one-shot learning of object categories. In BMVC.
Tommasi, T., Orabona, F., & Caputo, B. (2010). Safety in numbers: learning categories from few examples with multi model knowledge transfer. In CVPR.
Torresani, L., Szummer, M., & Fitzgibbon, A. (2010). Efficient object category recognition using classemes. In ECCV.
Tsochantaridis, I., Joachims, T., Hofmann, T., & Altun, Y. (2005). Large margin methods for structured and interdependent output variables.
Journal of Machine Learning Research,
6, 1453–1484.
MathSciNetMATH
Viola, P. A., Platt, J., & Zhang, C. (2005). Multiple instance boosting for object detection. In NIPS.
Weinberger, K. Q., Blitzer, J., & Saul, L. K. (2005). Distance metric learning for large margin nearest neighbor classification. In NIPS.
Winn, J., & Jojic, N. (2005a). LOCUS: learning object classes with unsupervised segmentation. In ICCV.
Zhang, J., Marszalek, M., Lazebnik, S., & Schmid, C. (2007). Local features and kernels for classification of texture and object categories: a comprehensive study.
International Journal of Computer Vision,
73(2), 213–238
CrossRef