Superpixels: An evaluation of the state-of-the-art

[1]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[2]  Rudolf Mester,et al.  Statistical Model Based Image Segmentation Using Region Growing, Contour Relaxation And Classification , 1988, Other Conferences.

[3]  Beatriz Marcotegui,et al.  Bottom-up segmentation of image sequences for coding , 1997, Ann. des Télécommunications.

[4]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  B. S. Manjunath,et al.  Color image segmentation , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[6]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  A. ADoefaa,et al.  ? ? ? ? f ? ? ? ? ? , 2003 .

[8]  Jitendra Malik,et al.  Learning a classification model for segmentation , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[9]  Gareth Funka-Lea,et al.  Multi-label Image Segmentation for Medical Applications Based on Graph-Theoretic Electrical Potentials , 2004, ECCV Workshops CVAMIA and MMBIA.

[10]  Jitendra Malik,et al.  Learning to detect natural image boundaries using local brightness, color, and texture cues , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Daniel P. Huttenlocher,et al.  Efficient Graph-Based Image Segmentation , 2004, International Journal of Computer Vision.

[12]  Alexei A. Efros,et al.  Automatic photo pop-up , 2005, ACM Trans. Graph..

[13]  Jianguo Zhang,et al.  The PASCAL Visual Object Classes Challenge , 2006 .

[14]  Alexei A. Efros,et al.  Recovering Surface Layout from an Image , 2007, International Journal of Computer Vision.

[15]  Leo Grady,et al.  Random Walks for Image Segmentation , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Janez Demsar,et al.  Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..

[17]  Antonio Torralba,et al.  LabelMe: A Database and Web-Based Tool for Image Annotation , 2008, International Journal of Computer Vision.

[18]  Alexei A. Efros,et al.  Recovering Occlusion Boundaries from a Single Image , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[19]  Christopher Rohkohl,et al.  Efficient Image Segmentation Using Pairwise Pixel Similarities , 2007, DAGM-Symposium.

[20]  Umar Mohammed,et al.  Superpixel lattices , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[21]  Ullrich Köthe,et al.  Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification , 2008, DAGM-Symposium.

[22]  Stephen Gould,et al.  Multi-Class Segmentation with Relative Location Prior , 2008, International Journal of Computer Vision.

[23]  Stefano Soatto,et al.  Quick Shift and Kernel Methods for Mode Seeking , 2008, ECCV.

[24]  Krystian Mikolajczyk,et al.  Segmentation Based Interest Points and Evaluation of Unsupervised Image Segmentation Methods , 2009, BMVC.

[25]  Li Fei-Fei,et al.  ImageNet: A large-scale hierarchical image database , 2009, CVPR.

[26]  B. Schiele,et al.  Pedestrian detection: A benchmark , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[27]  Roland Siegwart,et al.  Medial Features for Superpixel Segmentation , 2009, MVA.

[28]  Sven J. Dickinson,et al.  TurboPixels: Fast Superpixels Using Geometric Flows , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[29]  Peter Carr,et al.  Minimizing energy functions on 4-connected lattices using elimination , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[30]  Stephen Gould,et al.  Decomposing a scene into geometric and semantically consistent regions , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[31]  John MacCormick,et al.  Fast superpixels for video analysis , 2009, 2009 Workshop on Motion and Video Computing (WMVC).

[32]  Aurélien Ducournau,et al.  Hypergraph coarsening for image superpixelization , 2010, 2010 5th International Symposium On I/V Communications and Mobile Network.

[33]  Vincent Lepetit,et al.  A Fully Automated Approach to Segmentation of Irregularly Shaped Cellular Structures in EM Images , 2010, MICCAI.

[34]  Joost van de Weijer,et al.  Harmony potentials for joint classification and segmentation , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[35]  Svetlana Lazebnik,et al.  Superparsing , 2010, International Journal of Computer Vision.

[36]  S. Süsstrunk,et al.  SLIC Superpixels ? , 2010 .

[37]  Andrea Vedaldi,et al.  Vlfeat: an open and portable library of computer vision algorithms , 2010, ACM Multimedia.

[38]  Mei Han,et al.  Efficient hierarchical graph-based video segmentation , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[39]  Paria Mehrani,et al.  Superpixels and Supervoxels in an Energy Optimization Framework , 2010, ECCV.

[40]  Stewart Burn,et al.  Superpixels via pseudo-Boolean optimization , 2011, 2011 International Conference on Computer Vision.

[41]  Rama Chellappa,et al.  Entropy rate superpixel segmentation , 2011, CVPR 2011.

[42]  Charless C. Fowlkes,et al.  Contour Detection and Hierarchical Image Segmentation , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[43]  Hongbin Zha,et al.  Structure-Sensitive Superpixels via Geodesic Distance , 2011, 2011 International Conference on Computer Vision.

[44]  Stewart Burn,et al.  Superpixels, Occlusion and Stereo , 2011, 2011 International Conference on Digital Image Computing: Techniques and Applications.

[45]  Rudolf Mester,et al.  Multichannel Segmentation Using Contour Relaxation: Fast Super-Pixels and Temporal Propagation , 2011, SCIA.

[46]  Jonathan T. Barron,et al.  A category-level 3-D object dataset: Putting the Kinect to work , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[47]  Atsuto Maki,et al.  Homogeneous Superpixels from Random Walks , 2011, MVA.

[48]  Georg Langs,et al.  Superpixel-Based Interest Points for Effective Bags of Visual Words Medical Image Retrieval , 2011, MCBR-CDS.

[49]  Huchuan Lu,et al.  Superpixel tracking , 2011, 2011 International Conference on Computer Vision.

[50]  Hongbin Zha,et al.  Structure-sensitive superpixels via geodesic distance , 2011, ICCV.

[51]  Luis E. Ortiz,et al.  Parsing clothing in fashion photographs , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[52]  Rainer Stiefelhagen,et al.  Measuring and evaluating the compactness of superpixels , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[53]  Pascal Fua,et al.  Supervoxel-Based Segmentation of Mitochondria in EM Image Stacks With Learned Shape Features , 2012, IEEE Transactions on Medical Imaging.

[54]  Chenliang Xu,et al.  Evaluation of super-voxel methods for early video processing , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[55]  Yael Pritch,et al.  Saliency filters: Contrast based filtering for salient region detection , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[56]  Yunfan Du,et al.  Superpixels using random walker , 2012, 2012 IEEE Global High Tech Congress on Electronics.

[57]  Michael J. Black,et al.  A Naturalistic Open Source Movie for Optical Flow Evaluation , 2012, ECCV.

[58]  Peer Neubert,et al.  Superpixel Benchmark and Comparison , 2012 .

[59]  Michael Beetz,et al.  Depth-adaptive superpixels , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[60]  Pascal Fua,et al.  SLIC Superpixels Compared to State-of-the-Art Superpixel Methods , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[61]  Xiaofeng Ren,et al.  Discriminatively Trained Sparse Code Gradients for Contour Detection , 2012, NIPS.

[62]  Jie Wang,et al.  VCells: Simple and Efficient Superpixels Using Edge-Weighted Centroidal Voronoi Tessellations , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[63]  Derek Hoiem,et al.  Indoor Segmentation and Support Inference from RGBD Images , 2012, ECCV.

[64]  Luc Van Gool,et al.  SEEDS: Superpixels Extracted via Energy-Driven Sampling , 2012, ECCV.

[65]  Xiaochun Cao,et al.  Topology Preserved Regular Superpixel , 2012, 2012 IEEE International Conference on Multimedia and Expo.

[66]  Peer Neubert,et al.  Evaluating Superpixels in Video: Metrics Beyond Figure-Ground Segmentation , 2013, BMVC.

[67]  Florentin Wörgötter,et al.  Voxel Cloud Connectivity Segmentation - Supervoxels for Point Clouds , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[68]  Kwang-Shik Kim,et al.  Improved simple linear iterative clustering superpixels , 2013, 2013 IEEE International Symposium on Consumer Electronics (ISCE).

[69]  Jian Zhang,et al.  Estimating the 3D Layout of Indoor Scenes and Its Clutter from Depth Sensors , 2013, 2013 IEEE International Conference on Computer Vision.

[70]  Afshin Dehghan,et al.  Improving an Object Detector and Extracting Regions Using Superpixels , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[71]  Santiago Manen,et al.  Online Video SEEDS for Temporal Window Objectness , 2013, 2013 IEEE International Conference on Computer Vision.

[72]  Andrew Owens,et al.  SUN3D: A Database of Big Spaces Reconstructed Using SfM and Object Labels , 2013, 2013 IEEE International Conference on Computer Vision.

[73]  Rudolf Mester,et al.  Contour-Relaxed Superpixels , 2013, EMMCVPR.

[74]  Jian Dong,et al.  A Deformable Mixture Parsing Model with Parselets , 2013, 2013 IEEE International Conference on Computer Vision.

[75]  C. Lawrence Zitnick,et al.  Structured Forests for Fast Edge Detection , 2013, 2013 IEEE International Conference on Computer Vision.

[76]  Sanja Fidler,et al.  Holistic Scene Understanding for 3D Object Detection with RGBD Cameras , 2013, 2013 IEEE International Conference on Computer Vision.

[77]  Luc Van Gool,et al.  Depth SEEDS: Recovering incomplete depth data using superpixels , 2013, 2013 IEEE Workshop on Applications of Computer Vision (WACV).

[78]  Cevahir Çigla,et al.  Super pixel extraction via convexity induced boundary adaptation , 2013, 2013 IEEE International Conference on Multimedia and Expo (ICME).

[79]  Kun Li,et al.  3-D Geometry Enhanced Superpixels for RGB-D Data , 2013, PCM.

[80]  Gregory Shakhnarovich,et al.  Image Segmentation by Cascaded Region Agglomeration , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[81]  Minh N. Do,et al.  Patch Match Filter: Efficient Edge-Aware Filtering Meets Randomized Search for Fast Correspondence Field Estimation , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[82]  Xuming He,et al.  Discrete-Continuous Depth Estimation from a Single Image , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[83]  Jeffrey J. Rodriguez,et al.  Superpixels using morphology for rock image segmentation , 2014, 2014 Southwest Symposium on Image Analysis and Interpretation.

[84]  Alexander Wong,et al.  Grid Seams: A Fast Superpixel Algorithm for Real-Time Applications , 2014, 2014 Canadian Conference on Computer and Robot Vision.

[85]  Xiaochun Cao,et al.  Regularity Preserved Superpixels and Supervoxels , 2014, IEEE Transactions on Multimedia.

[86]  Luc Van Gool,et al.  SEEDS: Superpixels Extracted Via Energy-Driven Sampling , 2012, International Journal of Computer Vision.

[87]  Pietro Perona,et al.  Microsoft COCO: Common Objects in Context , 2014, ECCV.

[88]  Huchuan Lu,et al.  Robust Superpixel Tracking , 2014, IEEE Transactions on Image Processing.

[89]  Esa Rahtu,et al.  Generating Object Segmentation Proposals Using Global and Local Search , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[90]  Jonathan T. Barron,et al.  Multiscale Combinatorial Grouping , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[91]  Xuelong Li,et al.  Lazy Random Walks for Superpixel Segmentation , 2014, IEEE Transactions on Image Processing.

[92]  Peer Neubert,et al.  Compact Watershed and Preemptive SLIC: On Improving Trade-offs of Superpixel Segmentation Algorithms , 2014, 2014 22nd International Conference on Pattern Recognition.

[93]  Wanda Benesova,et al.  Fast Superpixel Segmentation Using Morphological Processing , 2014 .

[94]  Pierre Buyssens,et al.  Eikonal based region growing for superpixels generation : Application to semi-supervised real time organ segmentation in CT images , 2014 .

[95]  Shuicheng Yan,et al.  Fashion Parsing With Weak Color-Category Labels , 2014, IEEE Transactions on Multimedia.

[96]  Jitendra Malik,et al.  Indoor Scene Understanding with RGB-D Images: Bottom-up Segmentation, Object Detection and Semantic Segmentation , 2015, International Journal of Computer Vision.

[97]  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 .

[98]  Etienne Decencière,et al.  Waterpixels: Superpixels based on the watershed transformation , 2014, 2014 IEEE International Conference on Image Processing (ICIP).

[99]  Carlo S. Regazzoni,et al.  A generative superpixel method , 2014, 17th International Conference on Information Fusion (FUSION).

[100]  Jana Kosecka,et al.  Semantic segmentation with heterogeneous sensor coverages , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[101]  Raquel Urtasun,et al.  Efficient Joint Segmentation, Occlusion Labeling, Stereo and Flow Estimation , 2014, ECCV.

[102]  Rynson W. H. Lau,et al.  SuperCNN: A Superpixelwise Convolutional Neural Network for Salient Object Detection , 2015, International Journal of Computer Vision.

[103]  Andreas Geiger,et al.  Joint 3D Object and Layout Inference from a Single RGB-D Image , 2015, GCPR.

[104]  James M. Rehg,et al.  The Middle Child Problem: Revisiting Parametric Min-Cut and Seeds for Object Proposals , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[105]  Guosheng Lin,et al.  Deep convolutional neural fields for depth estimation from a single image , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[106]  David Cárdenas-Peña,et al.  Waterpixels , 2015, IEEE Transactions on Image Processing.

[107]  Luc Van Gool,et al.  Superpixel meshes for fast edge-preserving surface reconstruction , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[108]  Gernot A. Fink,et al.  On the Influence of Superpixel Methods for Image Parsing , 2015, VISAPP.

[109]  John W. Fisher,et al.  A fast method for inferring high-quality simply-connected superpixels , 2015, 2015 IEEE International Conference on Image Processing (ICIP).

[110]  Sanja Fidler,et al.  Real-time coarse-to-fine topologically preserving segmentation , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[111]  Jianxiong Xiao,et al.  SUN RGB-D: A RGB-D scene understanding benchmark suite , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[112]  Junrui Lv An Improved SLIC Superpixels using Reciprocal nearest Neighbor Clustering , 2015 .

[113]  Zhengqin Li,et al.  Superpixel segmentation using Linear Spectral Clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[114]  Xiangyu Zhu,et al.  Object detection by labeling superpixels , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[115]  Andreas Geiger,et al.  Object scene flow for autonomous vehicles , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[116]  Cevahir Çigla,et al.  Convexity constrained efficient superpixel and supervoxel extraction , 2015, Signal Process. Image Commun..

[117]  Peter V. Gehler,et al.  Superpixel Convolutional Networks Using Bilateral Inceptions , 2015, ECCV.