UvA-DARE (Digital Academic Repository) Nuances in visual recognition
暂无分享,去创建一个
[1] Arnold W. M. Smeulders,et al. Locality in Generic Instance Search from One Example , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[2] Cees Snoek,et al. COSTA: Co-Occurrence Statistics for Zero-Shot Classification , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[3] Tieniu Tan,et al. Feature Coding in Image Classification: A Comprehensive Study , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[4] Naila Murray,et al. Inria+Xerox@FGcomp: Boosting the Fisher vector for fine-grained classification , 2013 .
[5] Andrew Zisserman,et al. Deep Fisher Networks for Large-Scale Image Classification , 2013, NIPS.
[6] Arnold W. M. Smeulders,et al. Fine-Grained Categorization by Alignments , 2013, 2013 IEEE International Conference on Computer Vision.
[7] Forrest N. Iandola,et al. Deformable Part Descriptors for Fine-Grained Recognition and Attribute Prediction , 2013, 2013 IEEE International Conference on Computer Vision.
[8] Andrew Zisserman,et al. Symbiotic Segmentation and Part Localization for Fine-Grained Categorization , 2013, 2013 IEEE International Conference on Computer Vision.
[9] Qi Tian,et al. Hierarchical Part Matching for Fine-Grained Visual Categorization , 2013, 2013 IEEE International Conference on Computer Vision.
[10] Koen E. A. van de Sande,et al. Codemaps - Segment, Classify and Search Objects Locally , 2013, 2013 IEEE International Conference on Computer Vision.
[11] Santiago Manen,et al. Prime Object Proposals with Randomized Prim's Algorithm , 2013, 2013 IEEE International Conference on Computer Vision.
[12] Cordelia Schmid,et al. Segmentation Driven Object Detection with Fisher Vectors , 2013, 2013 IEEE International Conference on Computer Vision.
[13] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[14] Trevor Darrell,et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[15] Trevor Darrell,et al. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition , 2013, ICML.
[16] Koen E. A. van de Sande,et al. Selective Search for Object Recognition , 2013, International Journal of Computer Vision.
[17] Peter N. Belhumeur,et al. POOF: Part-Based One-vs.-One Features for Fine-Grained Categorization, Face Verification, and Attribute Estimation , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[18] Gregory Shakhnarovich,et al. Discriminative Re-ranking of Diverse Segmentations , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[19] Subhransu Maji,et al. Fine-Grained Visual Classification of Aircraft , 2013, ArXiv.
[20] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[21] Linda G. Shapiro,et al. Unsupervised Template Learning for Fine-Grained Object Recognition , 2012, NIPS.
[22] Qi Tian,et al. Scalar quantization for large scale image search , 2012, ACM Multimedia.
[23] Yannis Avrithis,et al. SymCity: feature selection by symmetry for large scale image retrieval , 2012, ACM Multimedia.
[24] Dacheng Tao,et al. Exploiting visual word co-occurrence for image retrieval , 2012, ACM Multimedia.
[25] David W. Jacobs,et al. Dog Breed Classification Using Part Localization , 2012, ECCV.
[26] Luc Van Gool,et al. TriCoS: A Tri-level Class-Discriminative Co-segmentation Method for Image Classification , 2012, ECCV.
[27] Cristian Sminchisescu,et al. Semantic Segmentation with Second-Order Pooling , 2012, ECCV.
[28] Hsuan-Tien Lin,et al. Unsupervised Semantic Feature Discovery for Image Object Retrieval and Tag Refinement , 2012, IEEE Transactions on Multimedia.
[29] Cristian Sminchisescu,et al. CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[30] Cristian Sminchisescu,et al. Object Recognition by Sequential Figure-Ground Ranking , 2011, International Journal of Computer Vision.
[31] Trevor Darrell,et al. Pose pooling kernels for sub-category recognition , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[32] Arnold W. M. Smeulders,et al. Convex reduction of high-dimensional kernels for visual classification , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[33] C. V. Jawahar,et al. Cats and dogs , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[34] 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.
[35] Joachim M. Buhmann,et al. Weakly supervised structured output learning for semantic segmentation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[36] Cordelia Schmid,et al. Discriminative spatial saliency for image classification , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[37] Kun Duan,et al. Discovering localized attributes for fine-grained recognition , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[38] Arnold W. M. Smeulders,et al. Visual synonyms for landmark image retrieval , 2012, Comput. Vis. Image Underst..
[39] Marc'Aurelio Ranzato,et al. Building high-level features using large scale unsupervised learning , 2011, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[40] Vladlen Koltun,et al. Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials , 2011, NIPS.
[41] Qi Tian,et al. Large scale image search with geometric coding , 2011, ACM Multimedia.
[42] Zhiwei Li,et al. Contextual synonym dictionary for visual object retrieval , 2011, ACM Multimedia.
[43] Marcel Worring,et al. Personalizing automated image annotation using cross-entropy , 2011, ACM Multimedia.
[44] Trevor Darrell,et al. The NBNN kernel , 2011, 2011 International Conference on Computer Vision.
[45] Larry S. Davis,et al. Birdlets: Subordinate categorization using volumetric primitives and pose-normalized appearance , 2011, 2011 International Conference on Computer Vision.
[46] Pietro Perona,et al. Strong supervision from weak annotation: Interactive training of deformable part models , 2011, 2011 International Conference on Computer Vision.
[47] Koen E. A. van de Sande,et al. Segmentation as selective search for object recognition , 2011, 2011 International Conference on Computer Vision.
[48] Pietro Perona,et al. Multiclass recognition and part localization with humans in the loop , 2011, 2011 International Conference on Computer Vision.
[49] Subhransu Maji,et al. Semantic contours from inverse detectors , 2011, 2011 International Conference on Computer Vision.
[50] Gabriela Csurka,et al. An Efficient Approach to Semantic Segmentation , 2011, International Journal of Computer Vision.
[51] Pietro Perona,et al. The Caltech-UCSD Birds-200-2011 Dataset , 2011 .
[52] Fei-Fei Li,et al. Combining randomization and discrimination for fine-grained image categorization , 2011, CVPR 2011.
[53] Luc Van Gool,et al. What makes a chair a chair? , 2011, CVPR 2011.
[54] Zeynep Akata,et al. Fisher Vectors for Fine-Grained Visual Categorization , 2011, CVPR 2011.
[55] Kristen Grauman,et al. Efficient region search for object detection , 2011, CVPR 2011.
[56] Rainer Lienhart,et al. Scalable logo recognition in real-world images , 2011, ICMR.
[57] Michael I. Jordan,et al. Unsupervised Kernel Dimension Reduction , 2010, NIPS.
[58] Dieter Fox,et al. Kernel Descriptors for Visual Recognition , 2010, NIPS.
[59] Xian-Sheng Hua,et al. Large-scale robust visual codebook construction , 2010, ACM Multimedia.
[60] Cees Snoek,et al. Landmark image retrieval using visual synonyms , 2010, ACM Multimedia.
[61] Chun Chen,et al. Discriminative codeword selection for image representation , 2010, ACM Multimedia.
[62] Andrea Vedaldi,et al. Vlfeat: an open and portable library of computer vision algorithms , 2010, ACM Multimedia.
[63] Jason Weston,et al. Large scale image annotation: learning to rank with joint word-image embeddings , 2010, Machine Learning.
[64] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[65] Cristian Sminchisescu,et al. Random Fourier Approximations for Skewed Multiplicative Histogram Kernels , 2010, DAGM-Symposium.
[66] Pietro Perona,et al. Visual Recognition with Humans in the Loop , 2010, ECCV.
[67] Xiaodong Yu,et al. Attribute-Based Transfer Learning for Object Categorization with Zero/One Training Example , 2010, ECCV.
[68] Pushmeet Kohli,et al. Graph Cut Based Inference with Co-occurrence Statistics , 2010, ECCV.
[69] Thomas Mensink,et al. Improving the Fisher Kernel for Large-Scale Image Classification , 2010, ECCV.
[70] Thomas S. Huang,et al. Image Classification Using Super-Vector Coding of Local Image Descriptors , 2010, ECCV.
[71] David A. McAllester,et al. Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[72] Cor J. Veenman,et al. Visual Word Ambiguity , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[73] Jean Ponce,et al. A Theoretical Analysis of Feature Pooling in Visual Recognition , 2010, ICML.
[74] Andrew Zisserman,et al. Efficient additive kernels via explicit feature maps , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[75] Florent Perronnin,et al. Large-scale image categorization with explicit data embedding , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[76] Rong Jin,et al. Online visual vocabulary pruning using pairwise constraints , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[77] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[78] Cor J. Veenman,et al. Comparing compact codebooks for visual categorization , 2010, Comput. Vis. Image Underst..
[79] Cristian Sminchisescu,et al. Efficient Match Kernel between Sets of Features for Visual Recognition , 2009, NIPS.
[80] Christoph H. Lampert,et al. Efficient Subwindow Search: A Branch and Bound Framework for Object Localization , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[81] Sven J. Dickinson,et al. TurboPixels: Fast Superpixels Using Geometric Flows , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[82] Gang Hua,et al. Descriptive visual words and visual phrases for image applications , 2009, ACM Multimedia.
[83] Jitendra Malik,et al. Poselets: Body part detectors trained using 3D human pose annotations , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[84] Panu Turcot,et al. Better matching with fewer features: The selection of useful features in large database recognition problems , 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.
[85] Subhransu Maji,et al. Max-margin additive classifiers for detection , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[86] Andrew Zisserman,et al. Multiple kernels for object detection , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[87] Svetlana Lazebnik,et al. Supervised Learning of Quantizer Codebooks by Information Loss Minimization , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[88] Yihong Gong,et al. Linear spatial pyramid matching using sparse coding for image classification , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[89] J. Matas,et al. Efficient representation of local geometry for large scale object retrieval , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[90] Jian Sun,et al. Bundling features for large scale partial-duplicate web image search , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[91] Fei-Fei Li,et al. ImageNet: A large-scale hierarchical image database , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[92] Arnold W. M. Smeulders,et al. What is the spatial extent of an object? , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[93] Gerardo Rubino,et al. Introduction to Rare Event Simulation , 2009, Rare Event Simulation using Monte Carlo Methods.
[94] Andrew Zisserman,et al. Automated Flower Classification over a Large Number of Classes , 2008, 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing.
[95] Stefano Soatto,et al. Localizing Objects with Smart Dictionaries , 2008, ECCV.
[96] Cor J. Veenman,et al. Kernel Codebooks for Scene Categorization , 2008, ECCV.
[97] Lei Wang,et al. A Fast Algorithm for Creating a Compact and Discriminative Visual Codebook , 2008, ECCV.
[98] Subhransu Maji,et al. Classification using intersection kernel support vector machines is efficient , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[99] Roberto Cipolla,et al. Semantic texton forests for image categorization and segmentation , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[100] Michael Isard,et al. Lost in quantization: Improving particular object retrieval in large scale image databases , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[101] Michael Isard,et al. Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[102] Benjamin Recht,et al. Random Features for Large-Scale Kernel Machines , 2007, NIPS.
[103] Rajat Raina,et al. Self-taught learning: transfer learning from unlabeled data , 2007, ICML '07.
[104] Yoram Singer,et al. Pegasos: primal estimated sub-gradient solver for SVM , 2007, ICML '07.
[105] Florent Perronnin,et al. Fisher Kernels on Visual Vocabularies for Image Categorization , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[106] Richard Szeliski,et al. City-Scale Location Recognition , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[107] Michael Isard,et al. Object retrieval with large vocabularies and fast spatial matching , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[108] Trevor Darrell,et al. The Pyramid Match Kernel: Efficient Learning with Sets of Features , 2007, J. Mach. Learn. Res..
[109] Rajat Raina,et al. Efficient sparse coding algorithms , 2006, NIPS.
[110] Paul Over,et al. Evaluation campaigns and TRECVid , 2006, MIR '06.
[111] 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).
[112] 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).
[113] David Nistér,et al. Scalable Recognition with a Vocabulary Tree , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[114] Lih-Yuan Deng,et al. The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation, and Machine Learning , 2006, Technometrics.
[115] Cordelia Schmid,et al. A Comparison of Affine Region Detectors , 2005, International Journal of Computer Vision.
[116] Antonio Criminisi,et al. Object categorization by learned universal visual dictionary , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[117] Shie Mannor,et al. The cross entropy method for classification , 2005, ICML.
[118] Bill Triggs,et al. Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[119] Shie Mannor,et al. Basis Function Adaptation in Temporal Difference Reinforcement Learning , 2005, Ann. Oper. Res..
[120] G. LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[121] Cordelia Schmid,et al. Scale & Affine Invariant Interest Point Detectors , 2004, International Journal of Computer Vision.
[122] Jiri Matas,et al. Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..
[123] T. Tuytelaars,et al. Matching Widely Separated Views Based on Affine Invariant Regions , 2004, International Journal of Computer Vision.
[124] Vladimir Kolmogorov,et al. "GrabCut": interactive foreground extraction using iterated graph cuts , 2004, ACM Trans. Graph..
[125] Thorsten Joachims,et al. Learning a Distance Metric from Relative Comparisons , 2003, NIPS.
[126] Jitendra Malik,et al. Learning a classification model for segmentation , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[127] Andrew Zisserman,et al. Video Google: a text retrieval approach to object matching in videos , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[128] Jiri Matas,et al. Locally Optimized RANSAC , 2003, DAGM-Symposium.
[129] Cordelia Schmid,et al. A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[130] Jitendra Malik,et al. Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[131] Christopher K. I. Williams,et al. The Effect of the Input Density Distribution on Kernel-based Classifiers , 2000, ICML.
[132] Michael J. Swain,et al. Color indexing , 1991, International Journal of Computer Vision.
[133] I. Biederman. Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.
[134] A. Bennett. The Origin of Species by means of Natural Selection; or the Preservation of Favoured Races in the Struggle for Life , 1872, Nature.
[135] 智一 吉田,et al. Efficient Graph-Based Image Segmentationを用いた圃場図自動作成手法の検討 , 2014 .
[136] Matthew D. Zeiler. Hierarchical Convolutional Deep Learning in Computer Vision , 2013 .
[137] J. Uijlings,et al. The Visual Extent of an Object , 2011, International Journal of Computer Vision.
[138] Andrew Zisserman,et al. The devil is in the details: an evaluation of recent feature encoding methods , 2011, BMVC.
[139] David G. Lowe,et al. Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration , 2009, VISAPP.
[140] Antonio Criminisi,et al. TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context , 2007, International Journal of Computer Vision.
[141] Dennis Koelma,et al. The MediaMill TRECVID 2008 Semantic Video Search Engine , 2008, TRECVID.
[142] Bernhard Schölkopf,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2005, IEEE Transactions on Neural Networks.
[143] Gabriela Csurka,et al. Visual categorization with bags of keypoints , 2002, eccv 2004.
[144] Luc Van Gool,et al. Wide Baseline Stereo Matching based on Local, Affinely Invariant Regions , 2000, BMVC.