Region-Based Convolutional Networks for Accurate Object Detection and Segmentation
暂无分享,去创建一个
Jitendra Malik | Trevor Darrell | Jeff Donahue | Ross B. Girshick | Trevor Darrell | Jeff Donahue | Jitendra Malik
[1] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[2] Lawrence D. Jackel,et al. Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.
[3] Rich Caruana,et al. Multitask Learning: A Knowledge-Based Source of Inductive Bias , 1993, ICML.
[4] R. Vaillant,et al. An original approach for the localization of objects in images , 1993 .
[5] R. Vaillant,et al. Original approach for the localisation of objects in images , 1994 .
[6] John C. Platt,et al. A Convolutional Neural Network Hand Tracker , 1994, NIPS.
[7] Sebastian Thrun,et al. Is Learning The n-th Thing Any Easier Than Learning The First? , 1995, NIPS.
[8] Tomaso A. Poggio,et al. Example-Based Learning for View-Based Human Face Detection , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[9] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[10] Takeo Kanade,et al. Neural Network-Based Face Detection , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[11] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[12] Kunihiko Fukushima,et al. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position , 1980, Biological Cybernetics.
[13] Antonio Torralba,et al. Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.
[14] Alexei A. Efros,et al. Geometric context from a single image , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[15] 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).
[16] Alexei A. Efros,et al. Using Multiple Segmentations to Discover Objects and their Extent in Image Collections , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[17] Joseph J. Lim,et al. Recognition using regions , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[18] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[19] Cordelia Schmid,et al. Evaluation of GIST descriptors for web-scale image search , 2009, CIVR '09.
[20] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[21] David A. McAllester,et al. Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[22] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[23] Derek Hoiem,et al. Category Independent Object Proposals , 2010, ECCV.
[24] Subhransu Maji,et al. Semantic contours from inverse detectors , 2011, 2011 International Conference on Computer Vision.
[25] Vladlen Koltun,et al. Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials , 2011, NIPS.
[26] Graham W. Taylor,et al. Adaptive deconvolutional networks for mid and high level feature learning , 2011, 2011 International Conference on Computer Vision.
[27] Jitendra Malik,et al. Semantic segmentation using regions and parts , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[28] Cristian Sminchisescu,et al. Semantic Segmentation with Second-Order Pooling , 2012, ECCV.
[29] Thomas Deselaers,et al. Measuring the Objectness of Image Windows , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[30] Derek Hoiem,et al. Diagnosing Error in Object Detectors , 2012, ECCV.
[31] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[32] Cristian Sminchisescu,et al. CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[33] Hao Su,et al. Crowdsourcing Annotations for Visual Object Detection , 2012, HCOMP@AAAI.
[34] Sanja Fidler,et al. Bottom-Up Segmentation for Top-Down Detection , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[35] Pascal Vincent,et al. Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[36] Deva Ramanan,et al. Histograms of Sparse Codes for Object Detection , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[37] Camille Couprie,et al. Learning Hierarchical Features for Scene Labeling , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[38] Koen E. A. van de Sande,et al. Selective Search for Object Recognition , 2013, International Journal of Computer Vision.
[39] Luca Maria Gambardella,et al. Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks , 2013, MICCAI.
[40] Joseph J. Lim,et al. Sketch Tokens: A Learned Mid-level Representation for Contour and Object Detection , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[41] Dumitru Erhan,et al. Deep Neural Networks for Object Detection , 2013, NIPS.
[42] Jonathon Shlens,et al. Fast, Accurate Detection of 100,000 Object Classes on a Single Machine , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[43] Yann LeCun,et al. Pedestrian Detection with Unsupervised Multi-stage Feature Learning , 2012, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[44] Ming Yang,et al. Regionlets for Generic Object Detection , 2013, 2013 IEEE International Conference on Computer Vision.
[45] Jitendra Malik,et al. Learning Rich Features from RGB-D Images for Object Detection and Segmentation , 2014, ECCV.
[46] Trevor Darrell,et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[47] Jitendra Malik,et al. Simultaneous Detection and Segmentation , 2014, ECCV.
[48] Dumitru Erhan,et al. Scalable, High-Quality Object Detection , 2014, ArXiv.
[49] R. Fergus,et al. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks , 2013, ICLR.
[50] James M. Rehg,et al. RIGOR: Reusing Inference in Graph Cuts for Generating Object Regions , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[51] Philip H. S. Torr,et al. BING: Binarized normed gradients for objectness estimation at 300fps , 2014, Computational Visual Media.
[52] Dumitru Erhan,et al. Scalable Object Detection Using Deep Neural Networks , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[53] Zaïd Harchaoui,et al. On learning to localize objects with minimal supervision , 2014, ICML.
[54] Koen E. A. van de Sande,et al. Fisher and VLAD with FLAIR , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[55] Trevor Darrell,et al. From Large-Scale Object Classifiers to Large-Scale Object Detectors: An Adaptation Approach , 2014 .
[56] Armand Joulin,et al. Deep Fragment Embeddings for Bidirectional Image Sentence Mapping , 2014, NIPS.
[57] Jonathan T. Barron,et al. Multiscale Combinatorial Grouping , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[58] Michael S. Bernstein,et al. Scalable multi-label annotation , 2014, CHI.
[59] C. Lawrence Zitnick,et al. Edge Boxes: Locating Object Proposals from Edges , 2014, ECCV.
[60] Trevor Darrell,et al. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition , 2013, ICML.
[61] Vladlen Koltun,et al. Geodesic Object Proposals , 2014, ECCV.
[62] Jitendra Malik,et al. Analyzing the Performance of Multilayer Neural Networks for Object Recognition , 2014, ECCV.
[63] Jitendra Malik,et al. R-CNNs for Pose Estimation and Action Detection , 2014, ArXiv.
[64] Iasonas Kokkinos,et al. Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs , 2014, ICLR.
[65] Jitendra Malik,et al. Hypercolumns for object segmentation and fine-grained localization , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[66] Ross B. Girshick,et al. Fast R-CNN , 2015, 1504.08083.
[67] Vibhav Vineet,et al. Conditional Random Fields as Recurrent Neural Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[68] Jian Sun,et al. Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[69] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[70] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[71] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[72] Bernt Schiele,et al. What Makes for Effective Detection Proposals? , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[73] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.