2017 ICCV Challenge: Detecting Symmetry in the Wild

Motivated by various new applications of computational symmetry in computer vision and in an effort to advance machine perception of symmetry in the wild, we organize the third international symmetry detection challenge at ICCV 2017, after the CVPR 2011/2013 symmetry detection competitions. Our goal is to gauge the progress in computational symmetry with continuous benchmarking of both new algorithms and datasets, as well as more polished validation methodology. Different from previous years, this time we expand our training/testing data sets to include 3D data, and establish the most comprehensive and largest annotated datasets for symmetry detection to date; we also expand the types of symmetries to include densely-distributed and medial-axis-like symmetries; furthermore, we establish a challenge-and-paper dual track mechanism where both algorithms and articles on symmetry-related research are solicited. In this report, we provide a detailed summary of our evaluation methodology for each type of symmetry detection algorithm validated. We demonstrate and analyze quantified detection results in terms of precision-recall curves and F-measures for all algorithms evaluated. We also offer a short survey of the paper-track submissions accepted for our 2017 symmetry challenge.

[1]  O. Chum,et al.  Detection, Rectification and Segmentation of Coplanar Repeated Patterns , 2014, CVPR 2014.

[2]  Yanxi Liu,et al.  Computational Symmetry , 2014, Computer Vision, A Reference Guide.

[3]  Seungkyu Lee,et al.  Reflection Symmetry Detection via Appearance of Structure Descriptor , 2016, ECCV.

[4]  Herbert L. Roitblat,et al.  Dolphin Detection and Conceptualization of Symmetry , 1992 .

[5]  Jitendra Malik,et al.  A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

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

[7]  Sven J. Dickinson,et al.  Detecting Curved Symmetric Parts Using a Deformable Disc Model , 2013, 2013 IEEE International Conference on Computer Vision.

[8]  Matthias Nießner,et al.  ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[9]  Niloy J. Mitra,et al.  Symmetry in 3D Geometry: Extraction and Applications , 2013, Comput. Graph. Forum.

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

[11]  Xiang Bai,et al.  DeepSkeleton: Learning Multi-Task Scale-Associated Deep Side Outputs for Object Skeleton Extraction in Natural Images , 2016, IEEE Transactions on Image Processing.

[12]  J D Delius,et al.  Symmetry: can pigeons conceptualize it? , 1978, Behavioral biology.

[13]  Cécile Barat,et al.  Wavelet-Based Reflection Symmetry Detection via Textural and Color Histograms , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

[14]  Iasonas Kokkinos,et al.  Learning-Based Symmetry Detection in Natural Images , 2012, ECCV.

[15]  Kalyan Sunkavalli,et al.  Nautilus , 2017, ACM Trans. Graph..

[16]  Riccardo Leonardi,et al.  InnerSpec: Technical Report , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

[17]  Vladlen Koltun,et al.  Robust reconstruction of indoor scenes , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[18]  Yiannis Aloimonos,et al.  Detection and Segmentation of 2D Curved Reflection Symmetric Structures , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[19]  Yuan Xie,et al.  Instance-Level Salient Object Segmentation , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[20]  Sven J. Dickinson,et al.  AMAT: Medial Axis Transform for Natural Images , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[21]  Seungkyu Lee,et al.  Bilateral symmetry detection based on scale invariant structure feature , 2015, 2015 IEEE International Conference on Image Processing (ICIP).

[22]  Yan Wang,et al.  Object Skeleton Extraction in Natural Images by Fusing Scale-Associated Deep Side Outputs , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[23]  Yanxi Liu,et al.  Symmetry Detection from RealWorld Images Competition 2013: Summary and Results , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[24]  Sven J. Dickinson,et al.  Multiscale Symmetric Part Detection and Grouping , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[25]  Yiannis Aloimonos,et al.  Detecting Reflectional Symmetries in 3D Data Through Symmetrical Fitting , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

[26]  Yanxi Liu,et al.  Symmetry reCAPTCHA , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[27]  David Grant Colburn Hildebrand,et al.  Finding Mirror Symmetry via Registration and Optimal Symmetric Pairwise Assignment of Curves , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

[28]  Zesheng Tang,et al.  Reflection Symmetry Detection Using Locally Affine Invariant Edge Correspondence , 2015, IEEE Transactions on Image Processing.

[29]  Michael Arens,et al.  Hierarchical Grouping Using Gestalt Assessments , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

[30]  Iasonas Kokkinos,et al.  DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[31]  Jan-Olof Eklundh,et al.  Detecting Symmetry and Symmetric Constellations of Features , 2006, ECCV.

[32]  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.

[33]  Alexandru Telea,et al.  An Augmented Fast Marching Method for Computing Skeletons and Centerlines , 2002, VisSym.

[34]  Shanmuganathan Raman,et al.  SymmMap: Estimation of the 2-D Reflection Symmetry Map and Its Applications , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

[35]  Chang Liu,et al.  RSRN: Rich Side-Output Residual Network for Medial Axis Detection , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

[36]  R. Menzel,et al.  Symmetry perception in an insect , 1996, Nature.

[37]  Luc Van Gool,et al.  Computational Symmetry in Computer Vision and Computer Graphics , 2010, Found. Trends Comput. Graph. Vis..

[38]  Jan-Michael Frahm,et al.  Detecting Large Repetitive Structures with Salient Boundaries , 2010, ECCV.

[39]  Hao Su,et al.  A Point Set Generation Network for 3D Object Reconstruction from a Single Image , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[40]  Zihao Hu,et al.  Multiple instance subspace learning via partial random projection tree for local reflection symmetry in natural images , 2016, Pattern Recognit..

[41]  Zygmunt Pizlo,et al.  Detecting 3-D Mirror Symmetry in a 2-D Camera Image for 3-D Shape Recovery , 2014, Proceedings of the IEEE.

[42]  Yanxi Liu,et al.  Beyond Planar Symmetry: Modeling Human Perception of Reflection and Rotation Symmetries in the Wild , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[43]  Xiang Bai,et al.  Fusing Image and Segmentation Cues for Skeleton Extraction in the Wild , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

[44]  Shanmuganathan Raman,et al.  SymmSLIC: Symmetry Aware Superpixel Segmentation , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

[45]  Marc Pollefeys,et al.  A Symmetry Prior for Convex Variational 3D Reconstruction , 2016, ECCV.

[46]  Vladlen Koltun,et al.  A Large Dataset of Object Scans , 2016, ArXiv.

[47]  Martin Giurfa,et al.  Symmetry is in the eye of the ‘beeholder’: innate preference for bilateral symmetry in flower-naïve bumblebees , 2004, Naturwissenschaften.