Towards effective codebookless model for image classification
暂无分享,去创建一个
Lei Zhang | Qilong Wang | Peihua Li | Wangmeng Zuo | W. Zuo | Lei Zhang | Qilong Wang | P. Li
[1] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[2] Fang Liu,et al. Shape of Gaussians as feature descriptors , 2009, CVPR.
[3] Christoph H. Lampert,et al. Deep Fisher Kernels -- End to End Learning of the Fisher Kernel GMM Parameters , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[4] Thomas S. Huang,et al. Image Classification Using Super-Vector Coding of Local Image Descriptors , 2010, ECCV.
[5] Cristian Sminchisescu,et al. Free-Form Region Description with Second-Order Pooling , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] Iasonas Kokkinos,et al. Describing Textures in the Wild , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[7] Zhaoquan Cai,et al. Deep Boosting: Joint feature selection and analysis dictionary learning in hierarchy , 2016, Neurocomputing.
[8] Eli Shechtman,et al. In defense of Nearest-Neighbor based image classification , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[9] Andrew Zisserman,et al. Video Google: a text retrieval approach to object matching in videos , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[10] Wilhelm Burger,et al. Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.
[11] Takumi Kobayashi,et al. Dirichlet-Based Histogram Feature Transform for Image Classification , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[12] Jason Weston,et al. WSABIE: Scaling Up to Large Vocabulary Image Annotation , 2011, IJCAI.
[13] William K. Pratt,et al. Digital Image Processing, 4th Edition , 2007, J. Electronic Imaging.
[14] Nicholas Ayache,et al. Fast and Simple Calculus on Tensors in the Log-Euclidean Framework , 2005, MICCAI.
[15] Qilong Wang,et al. Local Log-Euclidean Covariance Matrix (L2ECM) for Image Representation and Its Applications , 2012, ECCV.
[16] Dieter Fox,et al. Multipath Sparse Coding Using Hierarchical Matching Pursuit , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[17] TianQi,et al. Towards Codebook-Free , 2014 .
[18] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[19] Kaare Brandt Petersen,et al. Sparse Kernel Orthonormalized PLS for feature extraction in large data sets , 2006, NIPS.
[20] Matthijs C. Dorst. Distinctive Image Features from Scale-Invariant Keypoints , 2011 .
[21] Trevor Darrell,et al. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition , 2013, ICML.
[22] Haim H. Permuter,et al. A study of Gaussian mixture models of color and texture features for image classification and segmentation , 2006, Pattern Recognit..
[23] Qi Tian,et al. Towards Codebook-Free: Scalable Cascaded Hashing for Mobile Image Search , 2014, IEEE Transactions on Multimedia.
[24] Yasuo Kuniyoshi,et al. Global Gaussian approach for scene categorization using information geometry , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[25] Fatih Murat Porikli,et al. Region Covariance: A Fast Descriptor for Detection and Classification , 2006, ECCV.
[26] Cordelia Schmid,et al. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[27] Xavier Pennec,et al. A Riemannian Framework for Tensor Computing , 2005, International Journal of Computer Vision.
[28] Andrea Vedaldi,et al. Vlfeat: an open and portable library of computer vision algorithms , 2010, ACM Multimedia.
[29] SánchezJorge,et al. Image Classification with the Fisher Vector , 2013 .
[30] Thomas Mensink,et al. Image Classification with the Fisher Vector: Theory and Practice , 2013, International Journal of Computer Vision.
[31] Leonidas J. Guibas,et al. The Earth Mover's Distance as a Metric for Image Retrieval , 2000, International Journal of Computer Vision.
[32] Rita Cucchiara,et al. GOLD: Gaussians of Local Descriptors for image representation , 2015, Comput. Vis. Image Underst..
[33] K. Mikolajczyk,et al. Higher-order Occurrence Pooling on Mid- and Low-level Features: Visual Concept Detection , 2013 .
[34] Trevor Darrell,et al. Pose pooling kernels for sub-category recognition , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[35] Barbara Caputo,et al. Class-Specific Material Categorisation , 2005, ICCV.
[36] Liyu Gong,et al. Shape of Gaussians as feature descriptors , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[37] Cristian Sminchisescu,et al. Efficient Match Kernel between Sets of Features for Visual Recognition , 2009, NIPS.
[38] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[39] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[40] Jing Xu,et al. Deep boosting: Layered feature mining for general image classification , 2014, 2014 IEEE International Conference on Multimedia and Expo (ICME).
[41] Trevor Darrell,et al. The pyramid match kernel: discriminative classification with sets of image features , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[42] Cor J. Veenman,et al. Visual Word Ambiguity , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[43] Yihong Gong,et al. Locality-constrained Linear Coding for image classification , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[44] I. Dryden,et al. Non-Euclidean statistics for covariance matrices, with applications to diffusion tensor imaging , 2009, 0910.1656.
[45] I. Johnstone,et al. Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model. , 2013, Annals of statistics.
[46] Yu-Bin Yang,et al. Visual feature coding for image classification integrating dictionary structure , 2015, Pattern Recognit..
[47] Lei Zhang,et al. A Novel Earth Mover's Distance Methodology for Image Matching with Gaussian Mixture Models , 2013, 2013 IEEE International Conference on Computer Vision.
[48] Fei-FeiLi,et al. One-Shot Learning of Object Categories , 2006 .
[49] Thomas Seidl,et al. Modeling image similarity by Gaussian mixture models and the Signature Quadratic Form Distance , 2011, 2011 International Conference on Computer Vision.
[50] Huchuan Lu,et al. Saliency Detection via Absorbing Markov Chain , 2013, 2013 IEEE International Conference on Computer Vision.
[51] Mehrtash Tafazzoli Harandi,et al. From Manifold to Manifold: Geometry-Aware Dimensionality Reduction for SPD Matrices , 2014, ECCV.
[52] Miroslav Lovric,et al. Multivariate Normal Distributions Parametrized as a Riemannian Symmetric Space , 2000 .
[53] Liang Lin,et al. Representing and recognizing objects with massive local image patches , 2012, Pattern Recognit..
[54] Pietro Perona,et al. The Caltech-UCSD Birds-200-2011 Dataset , 2011 .
[55] Jian Sun,et al. Blessing of Dimensionality: High-Dimensional Feature and Its Efficient Compression for Face Verification , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[56] Edward H. Adelson,et al. Material perception: What can you see in a brief glance? , 2010 .
[57] Cristian Sminchisescu,et al. Semantic Segmentation with Second-Order Pooling , 2012, ECCV.
[58] C. Stein. Lectures on the theory of estimation of many parameters , 1986 .
[59] Luc Van Gool,et al. Self-Adaptable Templates for Feature Coding , 2014, NIPS.
[60] Fei-Fei Li,et al. What, where and who? Classifying events by scene and object recognition , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[61] Gary R. Bradski,et al. A codebook-free and annotation-free approach for fine-grained image categorization , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[62] Cordelia Schmid,et al. Aggregating local descriptors into a compact image representation , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[63] Hongdong Li,et al. Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[64] Pietro Perona,et al. One-shot learning of object categories , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.