11 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing

11.1 Three-Dimensional Descriptions -- General

CVonline: Object, World and Scene Representations,
CV-OnlineJuly 2001.
HTML Version. Survey, Object Representation. BibRef 0107

NaturePix: Visual Cognitive Modeling Research,
2007.
WWW Link. Dataset, 3-D Data. ASU 3-D datasets. Replaces former ASU dataset?

EyeTronics,
2007
WWW Link. Vendor, Stereo Sensor. System for 3-D models from images. Also sells 3-D models.

3DSOM,
2007. 3D Software Object Modeller.
WWW Link. Vendor, Model Generation. System for 3-D models from images.

The Stanford 3D Scanning Repository,
2007.
WWW Link. Dataset, 3-D Data. Stanford graphics databases

AQSENSE,
1989.
WWW Link. Vendor, 3-D Shape. Code, 3-D Shape. Code for 3-D shape descriptions and inspection. Match 3-D, XYZ from range maps, merge range maps. The SAL3D (3D Shape Analysis Library) product.

The Beazley Archive of Classical Art Pottery Database,
July 2013
WWW Link. Dataset, Pottery.

Srihari, S.N.[Sargur N.],
Representation of Three-Dimensional Digital Images,
Surveys(13), No. 4, December 1981, pp. 399-424. Survey, Tomography. Tomography. Data structures. Among other things, compares octree type representation with others. BibRef 8112

Barnhill, R.E.,
A Survey of the Representation and Design of Surfaces,
IEEE_CGA(3), No. 7, October 1983, pp. 9-16. Survey, Representation. BibRef 8310

Aggarwal, J.K., Davis, L.S., Martin, W.N., Roach, J.W.,
Survey: Representation Methods in Three-Dimensional Objects,
PPR82(377-391). Survey, Representation. BibRef 8200

Besl, P.J.[Paul J.], and Jain, R.C.[Ramesh C.],
Three-Dimensional Object Recognition,
Surveys(17), No. 1, March 1985, pp. 75-145. Survey, Representation. BibRef 8503
Earlier:
Range Image Understanding,
CVPR85(430-449). Descriptions, Three-Dimensional. Recognize Three-Dimensional Objects. A survey of various techniques. BibRef

Besl, P.J.,
Geometric Modeling and Computer Vision,
PIEEE(76), No. 8, August 1988, pp. 936-958. BibRef 8808

Besl, P.J.,
Surfaces in Range Image Understanding,
Berlin: Springer-Verlag1988. BibRef 8800 Book BibRef
And: Add A2: Jain, R.C.,
Surface Characterization of Three-Dimensional Object Recognition in Depth Maps,
MichiganRSD-TR-20-84, 1984. More details covered in a variety of papers? BibRef

Besl, P.J.[Paul J.],
Geometric Signal Processing,
AIRI90(141-205). BibRef 9000

Forrest, A.R.[A. Robin],
On Coons' and Other Methods for the Representation of Curved Surfaces,
CGIP(1), No. 4, December 1972, pp. 341-359.
Elsevier DOI At the time, not a lot of Coons surface work had been published. A review. BibRef 7212

Jain, R., Aggarwal, J.K.,
Computer Analysis of Scenes with Curved Objects,
PIEEE(67), 1979, pp. 805-812. BibRef 7900

Chiyokura, B., Kimura, F.,
Design of Solids with Free-Form Surfaces,
Computer Graphics(17), No. 3, 1983, pp. 289-293. BibRef 8300

Reed, G.M.[George M.],
On the Characterization of Simple Closed Surfaces in Three-Dimensional Digital Images,
CVGIP(25), No. 2, February 1984, pp. 226-235.
Elsevier DOI BibRef 8402

Reed, G.M.[George M.], Rosenfeld, A.,
Recognition of Surfaces in three-Dimensional Digital Imgaes,
InfoControl(53), 1982, pp. 108-120. BibRef 8200
Earlier: UMD-TR-1210, August 1982. BibRef

Morgenthaler, D.G., and Rosenfeld, A.,
Surfaces in Three-Dimensional Digital Images,
InfoControl(51), 1981, pp. 227-247. BibRef 8100
Earlier: UMD-TR-940, September 1980. BibRef

Bowyer, K.W., Dyer, C.R.,
Three-Dimensional Shape Representation,
HPRIP-CV94(17-51). BibRef 9400

Nishihara, H.K.,
Intensity, Visible-Surface, and Volumetric Representation,
AI(17), No. 1-3, August 1981, pp. 265-284.
Elsevier DOI A variety of 3-D representation techniques are discussed with examples from MIT work. BibRef 8108

Yamamoto, K.,
Future Directions in Computer Vision and Image Understanding: ETL Perspectives,
ICPR90(I: 32-37).
IEEE DOI Mostly 3-D processing work. BibRef 9000

Ullmann, J.R.,
An Investigation of Occlusion in One Dimension,
CVGIP(22), No. 1, April 1983, pp. 194-203.
Elsevier DOI Two-D occlusions:
See also Analysis of 2-D Occlusion by Subtracting Out. BibRef 8304

Voss, K.,
Images, Objects, and Surfaces in Z[N],
PRAI(5), 1991, pp. 797-808. BibRef 9100

Flinchbaugh, B.E.[Bruce E.],
System and method for displaying, and interactively excavating and examining a three dimensional volume,
US_Patent4,685,070, August 17, 1993.
HTML Version. Display 2-D representation of 3-D object. Tesselation of cells. BibRef 9308

Fisher, R.B.,
Representing 3D Structures for Visual Recognition,
AIR(1), No. 3, 1987, pp. 183-200. BibRef 8700 Edinburgh Survey, Representation. Survey of visual model representations
See also SMS: A Suggestive Modelling System for Object Recognition. BibRef

Maybank, S.J.,
The projective geometry of ambiguous surfaces,
Royal(A: 332), 1990, pp. pp. 1-47. BibRef 9000

Faugeras, O.D.,
Stratification of 3-Dimensional Vision: Projective, Affine, and Metric Representations,
JOSA-A(12), No. 3, March 1995, pp. 465-484.
See also Few Steps Toward Artificial 3-D Vision, A. BibRef 9503

Bajcsy, R.,
Signal-to-Symbol Transformation and Vice-Versa: From Fundamental Processes to Representation,
Surveys(27), No. 3, September 1995, pp. 310-313. Survey, Representation. BibRef 9509

Chen, P.C., Tsai, W.C., Hwang, S.Y.,
A Graded Approach to Shape Representation,
JVCIR(7), No. 2, June 1996, pp. 105-115. 9607
BibRef

Watt, R.J.,
Issues in Shape Perception,
IVC(11), No. 6, July-August 1993, pp. 389-394.
Elsevier DOI BibRef 9307

Mohr, R.,
Projective Geometry and Computer Vision,
HPRCV97(Chapter II:4). (LIFIA, France) BibRef 9700

Loncaric, S.[Sven],
A Survey of Shape Analysis Techniques,
PR(31), No. 8, August 1998, pp. 983-1001.
Elsevier DOI 9807
Survey, Shape. BibRef

Lengyel, J.[Jed],
The Convergence of Graphics and Vision,
Computer(31), No. 7, July 1998, pp. 46-53. Survey, Graphics and Vision. Survey of the similarities. Vision generates the models, graphics assume the models. Both have a spectrum of image-based to physical-based techniques, attack from opposite ends. BibRef 9807

Goshtasby, A.A.[A. Ardeshir], Sonka, M.[Milan], Udupa, J.K.[Jayaram K.],
Analysis of Volumetric Images,
CVIU(77), No. 2, February 2000, pp. 79-83.
DOI Link 0003
BibRef

Paquet, E.[Eric], Rioux, M.[Marc], Murching, A.[Anil], Naveen, T.[Thumpudi], Tabatabai, A.[Ali],
Description of shape information for 2-D and 3-D objects,
SP:IC(16), No. 1-2, September 2000, pp. 103-122.
Elsevier DOI 0008
BibRef

Campbell, R.J.[Richard J.], Flynn, P.J.[Patrick J.],
A Survey of Free-Form Object Representation and Recognition Techniques,
CVIU(81), No. 2, February 2001, pp. 166-210.
DOI Link 0103
Survey, Object Representation. BibRef
Earlier:
Eigenshapes for 3D Object Recognition in Range Data,
CVPR99(II: 505-510).
IEEE DOI Extend appearance based to range data. BibRef

Oliva, A.[Aude], Torralba, A.B.[Antonio B.],
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope,
IJCV(42), No. 3, May-June 2001, pp. 145-175.
DOI Link
WWW Link. 0108
Dataset, Outdoor Secens. BibRef
Earlier:
Scene-Centered Description from Spatial Envelope Properties,
BMCV02(263 ff.).
Springer DOI 0303
Otherwise known as OSR dataset. Spatial envelope: low dimensional representation of the secen. Perceptual dimensions to represent the dominat satial structure. BibRef

Pastor, L.[Luis], Rodríguez, A.[Angel], Espadero, J.M.[J. Miguel], Rincón, L.[Luis],
3D wavelet-based multiresolution object representation,
PR(34), No. 12, December 2001, pp. 2497-2513.
Elsevier DOI 0110
Award, Pattern Recognition, Honorable Mention. BibRef

Pastor, L.[Luis], Rodríguez, A.[Angel],
Surface approximation of 3D objects from irregularly sampled clouds of 3D points using spherical wavelets,
CIAP99(70-75).
IEEE DOI 9909
BibRef

Zribi, M.[Mourad],
Description of three-dimensional gray-level objects by the harmonic analysis approach,
PRL(23), No. 1-3, January 2002, pp. 235-243.
Elsevier DOI 0201
BibRef

Brimkov, V.E.[Valentin E.], Andres, E.[Eric], Barneva, R.P.[Reneta P.],
Object Discretizations in Higher Dimensions,
PRL(23), No. 6, April 2002, pp. 623-636.
Elsevier DOI 0202

See also Advances in combinatorial image analysis. BibRef

Brimkov, V.E.[Valentin E.],
Connectedness of Offset Digitizations in Higher Dimensions,
CompIMAGE10(36-46).
Springer DOI 1006
BibRef

Brimkov, V.E.[Valentin E.], Barneva, R.P.[Reneta P.],
Polyhedrization of Discrete Convex Volumes,
ISVC06(I: 548-557).
Springer DOI 0611
BibRef

Brimkov, V.E.[Valentin E.], Maimone, A.[Angelo], Nordo, G.[Giorgio],
On the Notion of Dimension in Digital Spaces,
IWCIA06(241-252).
Springer DOI 0606
BibRef

Brimkov, V.E.[Valentin E.],
Digitization scheme that assures faithful reconstruction of plane figures,
PR(42), No. 8, August 2009, pp. 1637-1649.
Elsevier DOI 0904
BibRef
Earlier:
Scaling of Plane Figures That Assures Faithful Digitization,
IWCIA08(xx-yy).
Springer DOI 0804
Digital geometry; Lattice polygon; Scaling factor; Polyhedral reconstruction; NP-hard problem; Object reconstruction BibRef

Andres, E.[Eric],
Discrete linear objects in dimension n: the standard model,
GM(65), No. 1-3, May 2003, pp. 92-111.
Elsevier DOI 0309
BibRef

Sato, Y.[Yoichi], Ikeuchi, K.[Katsushi], (Eds.)
Modeling from Reality (Book),
KluwerBoston, November 2001. ISBN 0-7923-7515-7. Ref as: BibRef 0111 MfR01
WWW Link. Mostly chapters from past papers, research at Tokyo and CMU. Turn real objects and environments into 3-D models for VR systems. BibRef

Ikeuchi, K.,
Modeling from reality,
3DIM01(117-124).
IEEE DOI 0106

See also Towards an Assembly Plan from Observation, Part I: Task Recognition with Polyhedral Objects. BibRef

Leyton, M.[Michael],
A Generative Theory of Shape,
Springer-VerlagOctober 2001. ISBN 3-540-42717-1.
Springer DOI Maximize transfer of structure and recoverability of generative operations. BibRef 0110

Leyton, M.[Michael],
The Structure of Paintings,
Springer2006, ISBN 978-3-211-35739-2
Springer DOI Shape is equivalent to memory storage. A principal argument of these foundations is that artworks are maximal memory stores. BibRef 0600

Defez, E., Villanueva-Oller, J., Villanueva, R.J., Law, A.,
Matrix Cubic Splines for Progressive 3D Imaging,
JMIV(17), No. 1, July 2002, pp. 41-53.
DOI Link 0211
BibRef

Marques, F.[Ferran], Lavagetto, F.[Fabian], Strintzis, M.G.[Michael G.],
Image processing for 3D imaging,
SP:IC(17), No. 9, October 2002, pp. 653-655.
Elsevier DOI 0211
BibRef

Galpin, F.[Franck], Morin, L.[Luce],
Sliding Adjustment for 3D Video Representation,
JASP(2002), No. 10, October 2002, pp. 1088-1101.
WWW Link. 0211
BibRef
Earlier:
Video Coding Using Streamed 3d Representation,
ICIP00(Vol III: 636-639).
IEEE DOI 0008
BibRef

Balter, R., Gioia, P., Morin, L., Galpin, F.,
Scalable and efficient coding of 3d model extracted from a video,
3DPVT04(836-843).
IEEE DOI 0412
BibRef

Galpin, F., Balter, R., Morin, L., Deguchi, K.,
3D models coding and morphing for efficient video compression,
CVPR04(I: 334-341).
IEEE DOI 0408
BibRef

de Kemp, E.A.[Eric A.], Sprague, K.B.[Kevin B.],
Interpretive Tools for 3-D Structural Geological Modeling Part I: Bézier-Based Curves, Ribbons and Grip Frames,
GeoInfo(7), No. 1, March 2003, pp. 55-71.
DOI Link 0304
BibRef

Sprague, K.B.[Kevin B.], de Kemp, E.A.[Eric A.],
Interpretive Tools for 3-D Structural Geological Modelling Part II: Surface Design from Sparse Spatial Data,
GeoInfo(9), No. 1, March 2005, pp. 5-32.
Springer DOI 0509
BibRef

Abrams, L., Fishkind, D.E., Priebe, C.E.,
A proof of the spherical homeomorphism conjecture for surfaces,
MedImg(21), No. 12, December 2002, pp. 1564-1566.
IEEE Top Reference. 0301
BibRef

Abrams, L., Fishkind, D.E., Priebe, C.E.,
The generalized spherical homeomorphism theorem for digital images,
MedImg(23), No. 5, May 2004, pp. 655-657.
IEEE Abstract. 0406
Spherical homeomorphism conjecture (
See also Automated graph-based analysis and correction of cortical volume topology. ). MRI reconstruction. BibRef

Sun, Y.Y.[Yi-Yong], Paik, J.K.[Joon-Ki], Koschan, A.F., Page, D.L., Abidi, M.A.,
Point fingerprint: A new 3-D object representation scheme,
SMC-B(33), No. 4, August 2003, pp. 712-717.
IEEE Abstract. 0308
BibRef

Csakany, P., Wallace, A.M.,
Representation and classification of 3-D objects,
SMC-B(33), No. 4, August 2003, pp. 638-647.
IEEE Abstract. 0308
BibRef

Alterson, R.[Robert], Spetsakis, M.E.[Minas E.],
Object recognition with adaptive Gabor features,
IVC(22), No. 12, 1 October 2004, pp. 1007-1014.
Elsevier DOI 0409
BibRef
Earlier:
An Adaptive-Sampling Algorithm for Object Representation,
VI02(1).
PDF File. 0208
BibRef

Rushmeier, H.E., and Bernardini, F.,
The 3D model acquisition pipeline,
CGForum(21), No. 2, 2002, pp. 149-172. Describes the techniques tobuild 3D model of real objects. BibRef 0200

Bernardini, F., Mittleman, J., Rushmeier, H.E., Silva, C., Taubin, G.,
The Ball-Pivoting Algoritm for Surface Reconstruction,
VCG(5), 1999, pp. 349-359.
IEEE DOI 1408
For Code:
See also Analysis and Implementation of a Parallel Ball Pivoting Algorithm, An. Also see:
See also Implementation and Parallelization of the Scale Space Meshing Algorithm, An. BibRef

Rushmeier, H.E.,
3D capture for computer graphics,
3DIM01(375-381).
IEEE DOI 0106
BibRef

Zanuttigh, P.[Pietro], Brusco, N.[Nicola], Taubman, D.S.[David S.], Cortelazzo, G.M.[Guido M.],
A novel framework for the interactive transmission of 3D scenes,
SP:IC(21), No. 9, October 2006, pp. 787-811.
Elsevier DOI 0611
BibRef
Earlier:
Greedy Non-Linear Approximation of the Plenoptic Function for Interactive Transmission of 3D Scenes,
ICIP05(I: 629-632).
IEEE DOI 0512
3D Scene compression; Interactive browsing; Scene rendering; Wavelet transforms; JPEG 2000; Distortion modelling BibRef

Zanuttigh, P.[Pietro], Brusco, N.[Nicola], Cortelazzo, G.M.[Guido M.], Taubman, D.S.[David S.],
A Rate Distortion Framework for 3D Browsing,
3DTV07(1-4).
IEEE DOI 0705
BibRef

Patané, G.[Giuseppe],
Laplacian spectral distances and kernels on 3D shapes,
PRL(47), No. 1, 2014, pp. 102-110.
Elsevier DOI 1408
Spectral distances BibRef

Patanè, G.[Giuseppe],
Fourier-Based and Rational Graph Filters for Spectral Processing,
PAMI(45), No. 6, June 2023, pp. 7063-7074.
IEEE DOI 2305
Convolution, Laplace equations, Kernel, Fourier transforms, Chebyshev approximation, Eigenvalues and eigenfunctions, spectral graph processing BibRef

Patané, G.[Giuseppe],
A unified definition and computation of Laplacian spectral distances,
PR(93), 2019, pp. 68-78.
Elsevier DOI 1906
Laplacian spectrum, Spectral distances, Spectral kernels, Heat kernel, Diffusion distances and geometry, Shape and graph analysis BibRef

Klette, R., Kozera, R., Noakes, L., Weickert, J., (Eds.)
Geometric Properties for Incomplete Data,
Springer2006, ISBN 978-1-4020-3857-0
WWW Link. The area of high-accuracy measurements of length, curvature, motion parameters and other geometrical quantities from acquired image data. BibRef 0600

Krim, H.[Hamid], Yezzi, Jr., A.J.[Anthony J.], (Eds.)
Statistics and Analysis of Shapes,
Springer2006. ISBN: 978-0-8176-4376-8.
WWW Link. Medial axis, skeletons, point clouds, curves, perspective, high dimensional spaces, shape metrics. BibRef 0600

de Floriani, L.[Leila], Spagnuolo, M.[Michela], (Eds.)
Shape Analysis and Structuring,
Springer2008, ISBN: 978-3-540-33264-0. Indexed as: BibRef 0800 ShapeAnalysis08
WWW Link. Survey, Shape Analysis. BibRef

Ozaktas, H.M.[Haldun M.], Onural, L.[Levent], (Eds.)
Three-Dimensional Television: Capture, Transmission, Display,
Springer2008, ISBN: 978-3-540-72531-2.
WWW Link. The results of the European project on 3D TV. BibRef 0800

Samet, H.[Hanan],
Object-based and image-based object representations,
Surveys(36), No. 2, June 2004, pp. 159-217.
WWW Link. 0805
Survey, Object Representation. BibRef

Peters, J.[Jörg], Reif, U.[Ulrich],
Subdivision Surfaces,
Springer2008, ISBN: 978-3-540-76405-2.
WWW Link. Buy this book: Subdivision Surfaces (Geometry and Computing) BibRef 0800

Eisert, P.[Peter], Pollefeys, M.[Marc], Tubaro, S.[Stefano],
Three-Dimensional Image and Video Processing, Intro,
JIVP(2008), No. 2008, pp. xx-yy.
DOI Link 0904
BibRef

Toriwaki, J.[Junichiro], Yoshida, H.[Hiroyuki],
Fundamentals of Three-dimensional Digital Image Processing,
Springer2009, ISBN: 978-1-84800-172-5
WWW Link. Survey, 3-D. Survey, Representation. 0905
Buy this book: Fundamentals of Three-dimensional Digital Image Processing BibRef

Cyganek, B.[Boguslaw], Siebert, J.P.[J. Paul],
An Introduction to 3D Computer Vision Techniques and Algorithms,
WileyMarch 2009. ISBN: 978-0-470-01704-3.
HTML Version. Buy this book: An Introduction to 3D Computer Vision Techniques and Algorithms 0905
BibRef

Wöhler, C.[Christian],
3D Computer Vision: Efficient Methods and Applications,
Springer2013. ISBN 978-1-4471-4149-5

Ohser, J.[Joachim], Schladitz, K.[Katja],
3D Images of Materials Structures: Processing and Analysis,
WileyNovember 2009, ISBN: 978-3-527-31203-0
HTML Version. Buy this book: 3D Images of Materials Structures: Processing and Analysis 0911
BibRef

Quan, L.[Long],
Image-Based Modeling,
Springer2010, ISBN: 978-1-4419-6678-0
WWW Link. Modeling for graphics. Vision for modeling. Buy this book: Image-Based Modeling 1010
BibRef

Tyler, C.W.[Christopher W.], (Ed.)
Computer Vision: From Surfaces to 3D Objects,
CRC PressBoca Raton, FL, December 09, 2010 ISBN: 9781439817124
WWW Link. Buy this book: Computer Vision: From Surfaces to 3D Objects 1010
Survey, 3-D Recognition. Survey, 3-D Description. BibRef

Tyler, C.W.[Christopher W.], Nicholas, S.C.[Spero C.],
Perceptual coding for 3D reconstruction,
EUVIP11(116-121).
IEEE DOI 1110
Encoding for the 3-D computations. BibRef

Miao, Y.W.[Yong-Wei], Feng, J.Q.[Jie-Qing],
Perceptual-saliency extremum lines for 3D shape illustration,
VC(26), No. 6-8, June 2010, pp. 433-443.
WWW Link. 1101
BibRef

Rustamov, R.M.[Raif M.],
A versatile framework for shape description,
VC(26), No. 10, October 2010, pp. 1245-1256.
WWW Link. 1101
BibRef
Earlier:
Robust Volumetric Shape Descriptor,
EG3DOR10(1-5)
DOI Link 1301
BibRef
Earlier:
Template Based Shape Descriptor,
3DOR09(1-7)
DOI Link 1301
3D shape retrieval - Numerical shape descriptors - Barycentric coordinates - Laplace-Beltrami eigenfunctions - Diffusion wavelets From surface mesh. BibRef

Rustamov, R.M.[Raif M.],
Interpolated eigenfunctions for volumetric shape processing,
VC(27), No. 11, November 2011, pp. 951-961.
WWW Link. 1112
BibRef

Yu, F., Lu, Z., Luo, H., Wang, P.,
Three-Dimensional Model Analysis and Processing,
Springer2010, ISBN: 978-3-642-12650-5
WWW Link. 1101
Buy this book: Three-Dimensional Model Analysis and Processing (Advanced Topics in Science and Technology in China) BibRef

libE57: software tools for managing E57 files,
OnlineDecember 11, 2010.
WWW Link. Code, 3D Data. BibRef 1012

Huber, D.F.[Daniel F.],
A new, open standard for 3D imaging data,
SPIE(Newsroom), January 12, 2011.
DOI Link 1101
Survey, 3D Data. E57 Format. The E57 format is a general-purpose, flexible standard for storing data from laser scanners and other 3D-imaging systems. BibRef

Edwards, J.,
Three-Dimensional Research Adds New Dimensions,
SPMag(28), No. 3, 2011, pp. 10-13.
IEEE DOI 1105
Survey, 3-D Research. Special Reports BibRef

Abate, M., Tovena, F.,
Curves and Surfaces,
Springer2012, ISBN: 978-88-470-1940-9

Pears, N.E.[Nick E.], Liu, Y.H.[Yong-Huai], Bunting, P.[Peter], (Eds.)
3D Imaging, Analysis and Applications,
Springer2012, ISBN: 978-1-4471-4062-7

Rusu, R.B.[Radu Bogdan],
Semantic 3D Object Maps for Everyday Robot Manipulation,
Springer2013. ISBN 978-3-642-35478-6

Breuß, M.[Michael], Bruckstein, A.M.[Alfred M.], Maragos, P.[Petros], (Eds.)
Innovations for Shape Analysis: Models and Algorithms,
Springer2013. ISBN 978-3-642-34140-3.

Förstner, W.[Wolfgang],
Graphical Models in Geodesy and Photogrammetry,
PFG(2013), No. 4, 2013, pp. 255-267.
DOI Link 1309
BibRef

Takyar, U., Maugey, T.[Thomas], Frossard, P.[Pascal],
Extended Layered Depth Image Representation in Multiview Navigation,
SPLetters(21), No. 1, January 2014, pp. 22-25.
IEEE DOI 1402
image representation BibRef

Maugey, T.[Thomas], Ortega, A., Frossard, P.[Pascal],
Graph-Based Representation for Multiview Image Geometry,
IP(24), No. 5, May 2015, pp. 1573-1586.
IEEE DOI 1504
data compression
See also Optimized Packet Scheduling in Multiview Video Navigation Systems. BibRef

Asari, M.A., Sheikh, U.U., Supriyanto, E.,
3D shape descriptor for object recognition based on Kinect-like depth image,
IVC(32), No. 4, 2014, pp. 260-269.
Elsevier DOI 1404
Inter-class BibRef

Dickinson, S.J.[Sven J.], Pizlo, Z.[Zygmunt], (Eds.),
Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective,

Bu, S.H.[Shu-Hui], Han, P.C.[Peng-Cheng], Liu, Z.B.[Zhen-Bao], Li, K.[Ke], Han, J.W.[Jun-Wei],
Shift-invariant ring feature for 3D shape,
VC(30), No. 6-8, June 2014, pp. 867-876.
WWW Link. 1407
BibRef

Chen, Y.[Ying], Vetro, A.[Anthony],
Next-Generation 3D Formats with Depth Map Support,
MultMedMag(21), No. 2, April 2014, pp. 90-94.
IEEE DOI 1407
Decoding BibRef

Zhou, H.L.[Hai-Ling], Zheng, J.M.[Jian-Min], Wei, L.[Lei],
Representing Images Using Curvilinear Feature Driven Subdivision Surfaces,
IP(23), No. 8, August 2014, pp. 3268-3280.
IEEE DOI 1408
computer graphics BibRef

Digne, J.[Julie],
An Analysis and Implementation of a Parallel Ball Pivoting Algorithm,
IPOL(2014), No. 1, pp. 149-168.
DOI Link 1408
Code, 3D Reconstruction. Surface reconstruction from a set of 3D points with coordinates and oriented normals.
See also Ball-Pivoting Algoritm for Surface Reconstruction, The. BibRef

Boscaini, D.[Davide], Castellani, U.[Umberto],
A sparse coding approach for local-to-global 3D shape description,
VC(30), No. 11, November 2014, pp. 1233-1245.
Springer DOI 1411
Combined shape description. BibRef

Alaoui Mhamdi, M.A.[Mohammed Ayoub], Ziou, D.[Djemel],
A local approach for 3D object recognition through a set of size functions,
IVC(32), No. 12, 2014, pp. 1030-1044.
Elsevier DOI 1412
3D model description. Split object by principal axes. Each portion represented by size. BibRef

Farinella, G.M.[Giovanni Maria], Ravì, D., Tomaselli, V., Guarnera, M., Battiato, S.[Sebastiano],
Representing scenes for real-time context classification on mobile devices,
PR(48), No. 4, 2015, pp. 1086-1100.
Elsevier DOI 1502
Scene representation BibRef

Battiato, S.[Sebastiano], Farinella, G.M.[Giovanni Maria], Guarnera, M.[Mirko], Ravì, D.[Daniele], Tomaselli, V.[Valeria],
Instant Scene Recognition on Mobile Platform,
ECCVDemos12(III: 655-658).
Springer DOI 1210
For camera properties (white balance, exposure, etc.) BibRef

Wang, X.C.[Xiao-Chao], Hu, J.P.[Jian-Ping], Zhang, D.B.[Dong-Bo], Qin, H.[Hong],
Efficient EMD and Hilbert spectra computation for 3D geometry processing and analysis via space-filling curve,
VC(31), No. 6-8, June 2015, pp. 1135-1145.
Springer DOI 1506
EMD: Empirical Mode Decomposition. BibRef

Shi, B.G.[Bao-Guang], Bai, S.[Song], Zhou, Z.C.[Zhi-Chao], Bai, X.[Xiang],
DeepPano: Deep Panoramic Representation for 3-D Shape Recognition,
SPLetters(22), No. 12, December 2015, pp. 2339-2343.
IEEE DOI 1512
Convert 3D shape into a panoramic view (cylinder projection around axis). Apply CNN to learn the representation. image recognition BibRef

Biasotti, S., Cerri, A., Aono, M., Ben Hamza, A., Garro, V., Giachetti, A., Giorgi, D., Godil, A., Li, C., Sanada, C., Spagnuolo, M., Tatsuma, A., Velasco-Forero, S.,
Retrieval and classification methods for textured 3D models: A comparative study,
VC(32), No. 2, February 2016, pp. 217-241.
Springer DOI 1602
Survey, 3D Models. Comparative study of six methods for the retrieval and classification of textured 3D models. BibRef

Iglesias, A.[Andrés], Gálvez, A.[Akemi], Avila, A.[Andreina],
Hybridizing mesh adaptive search algorithm and artificial immune systems for discrete rational Bézier curve approximation,
VC(32), No. 3, March 2016, pp. 393-402.
WWW Link. 1604
BibRef

Hong, J.Y.[Jhen-Yao], Way, D.L.[Der-Lor], Shih, Z.C.[Zen-Chung], Tai, W.K.[Wen-Kai], Chang, C.C.[Chin-Chen],
Inner engraving for the creation of a balanced LEGO sculpture,
VC(32), No. 5, May 2016, pp. 569-578.
Springer DOI 1605
description based on LEGO blocks and interlock rules. BibRef

Guo, Y.H.[Yi-Hui], Lin, S.J.[Shu-Jin], Su, Z.[Zhuo], Luo, X.N.[Xiao-Nan], Wang, R.M.[Ruo-Mei], Kang, Y.[Yang],
A 3D model perceptual feature metric based on global height field,
VC(32), No. 9, September 2016, pp. 1151-1164.
WWW Link. 1609
BibRef

Kasaei, S.H.[S. Hamidreza], Tomé, A.M.[Ana Maria], Lopes, L.S.[Luís Seabra], Oliveira, M.[Miguel],
GOOD: A global orthographic object descriptor for 3D object recognition and manipulation,
PRL(83, Part 3), No. 1, 2016, pp. 312-320.
Elsevier DOI 1609
3D object recognition BibRef

Kasaei, S.H.[S. Hamidreza], Lopes, L.S.[Luís Seabra], Tomé, A.M.[Ana Maria],
Local-LDA: Open-Ended Learning of Latent Topics for 3D Object Recognition,
PAMI(42), No. 10, October 2020, pp. 2567-2580.
IEEE DOI 2009
Object recognition, Robots, Visualization, Task analysis, Training, Shape, object perception BibRef

Dai, G.X.[Guo-Xian], Xie, J.[Jin], Zhu, F.[Fan], Fang, Y.[Yi],
Learning a discriminative deformation-invariant 3D shape descriptor via many-to-one encoder,
PRL(83, Part 3), No. 1, 2016, pp. 330-338.
Elsevier DOI 1609
Shape descriptor BibRef

Xie, J.[Jin], Zhu, F.[Fan], Dai, G.X.[Guo-Xian], Shao, L., Fang, Y.[Yi],
Progressive Shape-Distribution-Encoder for Learning 3D Shape Representation,
IP(26), No. 3, March 2017, pp. 1231-1242.
IEEE DOI 1703
computational geometry BibRef

Wang, M.[Meng], Xie, J.[Jin], Zhu, F.[Fan], Fang, Y.[Yi],
Linear discrimination dictionary learning for shape descriptors,
PRL(83, Part 3), No. 1, 2016, pp. 349-356.
Elsevier DOI 1609
Linear discriminant analysis BibRef

Xie, J.[Jin], Dai, G.X.[Guo-Xian], Zhu, F.[Fan], Wong, E.K.[Edward K.], Fang, Y.[Yi],
DeepShape: Deep-Learned Shape Descriptor for 3D Shape Retrieval,
PAMI(39), No. 7, July 2017, pp. 1335-1345.
IEEE DOI 1706
BibRef
Earlier: A1, A5, A3, A4, Only:
Deepshape: Deep learned shape descriptor for 3D shape matching and retrieval,
CVPR15(1275-1283)
IEEE DOI 1510
Feature extraction, Heating, Kernel, Neurons, Shape, Solid modeling, 3D shape retrieval, Fisher discrimination criterion, auto-encoder, heat diffusion, heat kernel signature. BibRef

Xie, J.[Jin], Dai, G.X.[Guo-Xian], Fang, Y.[Yi],
Deep Multimetric Learning for Shape-Based 3D Model Retrieval,
MultMed(19), No. 11, November 2017, pp. 2463-2474.
IEEE DOI 1710
Feature extraction, Manifolds, Measurement, Neural networks, Shape, Solid modeling, 3D shape descriptor, 3D shape retrieval, deep neural network, metric learning, multiple, shape, features BibRef

Dai, G.X.[Guo-Xian], Xie, J., Fang, Y.,
Deep Correlated Holistic Metric Learning for Sketch-Based 3D Shape Retrieval,
IP(27), No. 7, July 2018, pp. 3374-3386.
IEEE DOI 1805
Computational modeling, Feature extraction, Measurement, Shape, Solid modeling, mitigate BibRef

Xie, J.[Jin], Dai, G.X.[Guo-Xian], Zhu, F.[Fan], Shao, L., Fang, Y.[Yi],
Deep Nonlinear Metric Learning for 3-D Shape Retrieval,
Cyber(48), No. 1, January 2018, pp. 412-422.
IEEE DOI 1801
BibRef
Earlier: A1, A2, A3, A5, Only:
Learning Barycentric Representations of 3D Shapes for Sketch-Based 3D Shape Retrieval,
CVPR17(3615-3623)
IEEE DOI 1711
Encoding, Feature extraction, Heating, Kernel, Measurement, Shape, Solid modeling, 3-D shape descriptor, 3-D shape retrieval, neural network. Probability distribution, Visualization BibRef

Zhu, J.[Jing], Rizzo, J.R.[John-Ross], Fang, Y.[Yi],
Learning domain-invariant feature for robust depth-image-based 3D shape retrieval,
PRL(119), 2019, pp. 24-33.
Elsevier DOI 1902
Discriminative neural network, Cross-domain, Depth images, 3D shape retrieval BibRef

Zhu, F.[Fan], Xie, J.[Jin], Fang, Y.[Yi],
Heat Diffusion Long-Short Term Memory Learning for 3D Shape Analysis,
ECCV16(VII: 305-321).
Springer DOI 1611
BibRef

Fang, Y.[Yi], Xie, J.[Jin], Dai, G.X.[Guo-Xian], Wang, M.[Meng], Zhu, F.[Fan], Xu, T.T.[Tian-Tian], Wong, E.K.[Edward K.],
3D deep shape descriptor,
CVPR15(2319-2328)
IEEE DOI 1510
BibRef

Radhika Mani, M., Potukuchi, D.M., Satyanarayana, C.,
A novel approach for shape-based object recognition with curvelet transform,
MultInfoRetr(5), No. 4, November 2016, pp. 219-228.
Springer DOI 1612
BibRef

Conde-Rodríguez, F.[Francisco], Torres, J.C.[Juan-Carlos], García-Fernández, Á.L.[Ángel-Luis], Feito-Higueruela, F.R.[Francisco-Ramón],
A comprehensive framework for modeling heterogeneous objects,
VC(33), No. 1, January 2017, pp. 17-31.
Springer DOI 1702
BibRef

Wang, W.M.[Wei-Ming], Li, B.J.[Bao-Jun], Qian, S.C.[Si-Cheng], Liu, Y.J.[Yong-Jin], Wang, C.C.L.[Charlie C. L.], Liu, L.G.[Li-Gang], Yin, B.C.[Bao-Cai], Liu, X.P.[Xiu-Ping],
Cross section-based hollowing and structural enhancement,
VC(33), No. 6-8, June 2017, pp. 949-960.
Springer DOI 1706
For 3D printing, how much of the model can be hollow. BibRef

Naffouti, S.E.[Seif Eddine], Fougerolle, Y.[Yohan], Sakly, A.[Anis], Mériaudeau, F.[Fabrice],
An advanced global point signature for 3D shape recognition and retrieval,
SP:IC(58), No. 1, 2017, pp. 228-239.
Elsevier DOI 1710
Laplace-Beltrami operator BibRef

Naffouti, S.E.[Seif Eddine], Fougerolle, Y.[Yohan], Aouissaoui, I.[Ichraf], Sakly, A.[Anis], Mériaudeau, F.[Fabrice],
Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval,
SIViP(12), No. 5, July 2018, pp. 915-923.
Springer DOI
WWW Link. 1806
BibRef

Zou, Y.[Yu], Wang, X.Q.[Xue-Qian], Zhang, T.[Tao], Liang, B.[Bin], Song, J.Y.[Jing-Yan], Liu, H.D.[Hou-De],
BRoPH: An efficient and compact binary descriptor for 3D point clouds,
PR(76), No. 1, 2018, pp. 522-536.
Elsevier DOI 1801
Local reference frame BibRef

Effland, A.[Alexander], Rumpf, M.[Martin], Simon, S.[Stefan], Stahn, K.[Kirsten], Wirth, B.[Benedikt],
Bézier Curves in the Space of Images,
SSVM15(372-384).
Springer DOI 1506
BibRef

Gooya, A.[Ali], Lekadir, K.[Karim], Castro-Mateos, I.[Isaac], Pozo, J.M.[Jose Maria], Frangi, A.F.[Alejandro F.],
Mixture of Probabilistic Principal Component Analyzers for Shapes from Point Sets,
PAMI(40), No. 4, April 2018, pp. 891-904.
IEEE DOI 1804
healthy versus pathological heart morphologies, and iii) lumbar vertebrae. Data models, Manifolds, Principal component analysis, Probability density function, Shape, Sociology, variational Bayes BibRef

Clément, M.[Michaël], Kurtz, C.[Camille], Wendling, L.[Laurent],
Learning spatial relations and shapes for structural object description and scene recognition,
PR(84), 2018, pp. 197-210.
Elsevier DOI 1809
BibRef
Earlier:
Bags of spatial relations and shapes features for structural object description,
ICPR16(1994-1999)
IEEE DOI 1705
BoF based on positions. Spatial relations, Relative position descriptors, Bags of relations, Structural object description, Force histograms. Clustering algorithms, Image segmentation, Shape, Visualization, Vocabulary BibRef

Guan, X.F.[Xue-Feng], van Oosterom, P.[Peter], Cheng, B.[Bo],
A Parallel N-Dimensional Space-Filling Curve Library and Its Application in Massive Point Cloud Management,
IJGI(7), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Potenziani, M.[Marco], Callieri, M.[Marco], Dellepiane, M.[Matteo], Scopigno, R.[Roberto],
Publishing and Consuming 3D Content on the Web: A Survey,
FTCGV(10), No. 4, 2018, pp. 244-333.
DOI Link 1901
Survey, 3D Tools. Survey of the currently available Web3D tools and their applications. Tools for 3D printing, viewing, editing. BibRef

Bell, S., Upchurch, P., Snavely, N., Bala, K.,
OpenSurfaces: A richly annotated catalog of surface appearance,
TOG(32), 2013, pp. 111.
DOI Link BibRef 1300

Wagner, A.[André],
Degeneracy of the Intersection of Three Quadrics,
JMIV(61), No. 3, March 2019, pp. 352-358.
WWW Link. 1903
BibRef

Wang, J.D.[Ji-Dong], Dai, J.J.[Jia-Jia], Li, K.S.[Kin-Sum], Wang, J.[Jun], Wei, M.Q.A.[Ming-Qi-Ang], Pang, M.Y.[Ming-Yong],
Cost-effective printing of 3D objects with self-supporting property,
VC(35), No. 5, May 2019, pp. 639-651.
Springer DOI 1906
Optimize the amount of material you need to actually deposit. BibRef

Hu, J.B.[Jiang-Bei], Wang, S.F.[Sheng-Fa], Wang, Y.[Yi], Li, F.Q.[Feng-Qi], Luo, Z.X.[Zhong-Xuan],
A lightweight methodology of 3D printed objects utilizing multi-scale porous structures,
VC(35), No. 6-8, June 2018, pp. 949-959.
Springer DOI 1906
Printing porous structures. BibRef

Krayer, B.[Bastian], Müller, S.[Stefan],
Generating signed distance fields on the GPU with ray maps,
VC(35), No. 6-8, June 2018, pp. 961-971.
Springer DOI 1906
Represent objects as distances to the closest surface points. BibRef

Shen, Z., Shang, X., Zhao, M., Dong, X., Xiong, G., Wang, F.,
A Learning-Based Framework for Error Compensation in 3D Printing,
Cyber(49), No. 11, November 2019, pp. 4042-4050.
IEEE DOI 1908
error compensation, learning (artificial intelligence), neural nets, orthotics, production engineering computing, error compensation BibRef

Istenic, K.[Klemen], Gracias, N.[Nuno], Arnaubec, A.[Aurélien], Escartín, J.[Javier], Garcia, R.[Rafael],
Scale Accuracy Evaluation of Image-Based 3D Reconstruction Strategies Using Laser Photogrammetry,
RS(11), No. 18, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Zhu, Z., Wang, Y., Jiang, G., Yang, Y.,
Efficient Shape Coding for Object-Based 3D Video Applications,
CirSysVideo(29), No. 11, November 2019, pp. 3317-3325.
IEEE DOI 1911
Shape, Encoding, Image coding, Correlation, Video coding, Video sequences, 3D video, shape coding, predictive coding BibRef

Qiu, D.[Di], Lam, K.C.[Ka-Chun], Lui, L.M.[Lok-Ming],
Computing Quasi-Conformal Folds,
SIIMS(12), No. 3, 2019, pp. 1392-1424.
DOI Link 1911
Computing surface folding maps has numerous applications ranging from computer graphics to material design. BibRef

Getto, R.[Roman], Kuijper, A.[Arjan], Fellner, D.W.[Dieter W.],
Automatic procedural model generation for 3D object variation,
VC(36), No. 1, January 2020, pp. 53-70.
Springer DOI 2001
Model to generate variations of an an object. BibRef

Debroux, N.[Noémie], Aston, J.[John], Bonardi, F.[Fabien], Forbes, A.[Alistair], Le Guyader, C.[Carole], Romanchikova, M.[Marina], Schönlieb, C.B.[Carola-Bibiane],
A Variational Model Dedicated to Joint Segmentation, Registration, and Atlas Generation for Shape Analysis,
SIIMS(13), No. 1, 2020, pp. 351-380.
DOI Link 2004
BibRef

Debroux, N.[Noemie], Le Guyader, C.[Carole], Vese, L.A.[Luminita A.],
A Multiscale Deformation Representation,
SIIMS(16), No. 2, 2023, pp. 802-841.
DOI Link 2306
BibRef

Hoffmann, L.[Leah],
Attaining The Third Dimension,
CACM(63), No. 6, June 2020, pp. 96-ff.
DOI Link 2005
News article on Ed Catmull and Pat Hanrahan Turing lecture. BibRef

Ioannidou, S.[Stefania], Pantazis, G.[George],
Helmert Transformation Problem. From Euler Angles Method to Quaternion Algebra,
IJGI(9), No. 9, 2020, pp. xx-yy.
DOI Link 2009
BibRef
And: A2, A1: Reply to comments. IJGI(13), No. 10, 2024, pp. 366.
DOI Link 2411
3D coordinate transformations.
See also Comment on Transformation Problem. From Euler Angles Method to Quaternion Algebra. BibRef

Bektas, S.[Sebahattin],
Comment on 'Transformation Problem. From Euler Angles Method to Quaternion Algebra',
IJGI(13), No. 10, 2024, pp. 359.
DOI Link 2411

See also Helmert Transformation Problem. From Euler Angles Method to Quaternion Algebra. BibRef

Choi, G.P.T.[Gary P. T.], Leung-Liu, Y.[Yusan], Gu, X.F.[Xian-Feng], Lui, L.M.[Lok Ming],
Parallelizable Global Conformal Parameterization of Simply-Connected Surfaces via Partial Welding,
SIIMS(13), No. 3, 2020, pp. 1049-1083.
DOI Link 2010
BibRef

Zhu, Z.P.[Zhi-Peng], Choi, G.P.T.[Gary P. T.], Lui, L.M.[Lok Ming],
Parallelizable Global Quasi-Conformal Parameterization of Multiply Connected Surfaces via Partial Welding,
SIIMS(15), No. 4, 2022, pp. 1765-1807.
DOI Link 2211
BibRef

Yuan, J.F.[Jue-Fei], Abdul-Rashid, H.[Hameed], Li, B.[Bo], Lu, Y.J.[Yi-Juan], Schreck, T.[Tobias], Bai, S.[Song], Bai, X.[Xiang], Bui, N.M.[Ngoc-Minh], Do, M.N.[Minh N.], Do, T.L.[Trong-Le], Duong, A.D.[Anh-Duc], He, K.[Kai], He, X.W.[Xin-Wei], Holenderski, M.[Mike], Jarnikov, D.[Dmitri], Le, T.K.[Tu-Khiem], Li, W.H.[Wen-Hui], Liu, A.[Anan], Liu, X.L.[Xiao-Long], Menkovski, V.[Vlado], Nguyen, K.T.[Khac-Tuan], Nguyen, T.A.[Thanh-An], Nguyen, V.T.[Vinh-Tiep], Nie, W.Z.[Wei-Zhi], Ninh, V.T.[Van-Tu], Rey, P.[Perez], Su, Y.T.[Yu-Ting], Ton-That, V.[Vinh], Tran, M.T.[Minh-Triet], Wang, T.Y.[Tian-Yang], Xiang, S.[Shu], Zhe, S.[Shandian], Zhou, H.[Heyu], Zhou, Y.[Yang], Zhou, Z.C.[Zhi-Chao],
A comparison of methods for 3D scene shape retrieval,
CVIU(201), 2020, pp. 103070.
Elsevier DOI 2011
3D scenes, 3D shape retrieval, Scene benchmark, Performance evaluation, Query-by-Sketch, Query-by-Image, SHREC BibRef

Alaoui Mhamdi, M.A.[Mohammed Ayoub], Ziou, D.[Djemel],
3D object recognition through a size function resulting from an invariant topological feature,
PR(120), 2021, pp. 108131.
Elsevier DOI 2109
A critical points based descriptor for objects recognition. Object description, Object recognition, Object categorization, Shape classification BibRef

Wang, J.X.[Jia-Xiang], Sun, Z.L.[Zhan-Li], Zeng, Z.G.[Zhi-Gang], Lam, K.M.[Kin-Man],
3D Shape Estimation With an Enhanced Sparse Representation Approach,
SPLetters(28), 2021, pp. 1685-1688.
IEEE DOI 2109
Shape, Estimation, Solid modeling, Computational modeling, 3D reconstruction BibRef

Song, D.[Dan], Li, T.B.[Tian-Bao], Li, W.H.[Wen-Hui], Nie, W.Z.[Wei-Zhi], Liu, W.[Wu], Liu, A.[Anan],
Universal Cross-Domain 3D Model Retrieval,
MultMed(23), 2021, pp. 2721-2731.
IEEE DOI 2109
Using labeled 2-D images with 3-D models for descriptions. Solid modeling, Adaptation models, Computational modeling, Data models, domain adaptation BibRef

Li, W.H.[Wen-Hui], Zhou, H.[Houran], Zhang, C.Y.[Chen-Yu], Nie, W.Z.[Wei-Zhi], Li, X.Y.[Xuan-Ya], Liu, A.A.[An-An],
Dual-Stage Uncertainty Modeling for Unsupervised Cross-Domain 3D Model Retrieval,
MultMed(26), 2024, pp. 8996-9007.
IEEE DOI 2408
Solid modeling, Uncertainty, Semantics, Prototypes, Gaussian distribution, Bicycles, Cross-domain learning, domain adaptation BibRef

Li, W.H.[Wen-Hui], Zhao, Z.L.[Zhen-Lan], Liu, A.A.[An-An], Gao, Z.[Zan], Yan, C.G.[Cheng-Gang], Mao, Z.D.[Zhen-Dong], Chen, H.P.[Hai-Peng], Nie, W.Z.[Wei-Zhi],
Joint Local Correlation and Global Contextual Information for Unsupervised 3D Model Retrieval and Classification,
CirSysVideo(32), No. 5, May 2022, pp. 3265-3278.
IEEE DOI 2205
Solid modeling, Context modeling, Data models, Analytical models, Deep learning, Feature extraction, unsupervised feature learning BibRef

Hao, L.B.[Lin-Bo], Wang, H.M.[Hua-Ming],
Geometric feature statistics histogram for both real-valued and binary feature representations of 3D local shape,
IVC(117), 2022, pp. 104339.
Elsevier DOI 2112
3D point cloud, Local feature descriptor, Multiple geometric features, Binary extension, Feature matching BibRef

Dhar, S.[Soumi], Pal, S.[Shyamosree],
Surface Reconstruction: Roles in the Field of Computer Vision and Computer Graphics,
IJIG(22), No. 1 2022, pp. 2250008.
DOI Link 2202
BibRef

Sun, T.C.[Tie-Cheng], Liu, G.H.[Guang-Hui], Li, R.[Ru], Liu, S.C.[Shuai-Cheng], Zhu, S.Y.[Shu-Yuan], Zeng, B.[Bing],
Quadratic Terms Based Point-to-Surface 3D Representation for Deep Learning of Point Cloud,
CirSysVideo(32), No. 5, May 2022, pp. 2705-2718.
IEEE DOI 2205
Shape, Feature extraction, Task analysis, Surface reconstruction, Training, Surface treatment, 3D deep learning BibRef

Yan, X.F.[Xiong-Feng], Yang, M.[Min],
A Comparative Study of Various Deep Learning Approaches to Shape Encoding of Planar Geospatial Objects,
IJGI(11), No. 10, 2022, pp. xx-yy.
DOI Link 2211
BibRef

Sun, X.[Xiao], Huang, Y.[Yang], Lian, Z.H.[Zhou-Hui],
Learning isometry-invariant representations for point cloud analysis,
PR(134), 2023, pp. 109087.
Elsevier DOI 2212
3D Shape analysis, Isometry invariant, Non-rigid BibRef

Qin, S.F.[Shao-Fei], Zhang, X.[Xuan], Xu, H.T.[Hong-Teng], Xu, Y.[Yi],
Fast Quaternion Product Units for Learning Disentangled Representations in SO_3,
PAMI(45), No. 4, April 2023, pp. 4504-4520.
IEEE DOI 2303
Data in a 3D rotation group SO_3. Quaternions, Skeleton, Data models, Point cloud compression, Solid modeling, Computational modeling, Quaternion product units, 3D rotation modeling BibRef

Safwan-Mahad, F.[Fairuz], Iwamura, M.[Masakazu], Kise, K.[Koichi],
Learning Multi-Level Features for Improved 3D Reconstruction,
IEICE(E106-D), No. 3, March 2023, pp. 381-390.
WWW Link. 2303
BibRef

Hao, L.[Linbo], Yang, X.F.[Xue-Feng], Xu, K.[Ke], Yi, W.T.[Wen-Tao], Shen, Y.[Ying], Wang, H.[Huaming],
Rotational Voxels Statistics Histogram for both real-valued and binary feature representations of 3D local shape,
JVCIR(93), 2023, pp. 103817.
Elsevier DOI 2305
3D local feature descriptor, Point cloud, 3D multi-pose processing mechanism, Binary extension BibRef

Comic, L.[Lidija], Largeteau-Skapin, G.[Gaëlle], Zrour, R.[Rita], Biswas, R.[Ranita], Andres, E.[Eric],
Discrete analytical objects in the body-centered cubic grid,
PR(142), 2023, pp. 109693.
Elsevier DOI 2307
Discrete geometry, BCC Grid, Discrete analytical plane, Discrete analytical sphere, Discrete analytical line, 3D Coordinate system BibRef

Liu, J.X.[Jin-Xian], Ni, B.B.[Bing-Bing], Chen, Y.[Ye], Yu, Z.B.[Zhen-Bo], Wang, H.[Hang],
Learning by Restoring Broken 3D Geometry,
PAMI(45), No. 9, September 2023, pp. 11024-11039.
IEEE DOI 2309
self-supervised 3D learning. Learn via breaking the object. Apply to new domain. BibRef

Ogayar-Anguita, C.J.[Carlos J.], López-Ruiz, A.[Alfonso], Segura-Sánchez, R.J.[Rafael J.], Rueda-Ruiz, A.J.[Antonio J.],
A Version Control System for Point Clouds,
RS(15), No. 18, 2023, pp. 4635.
DOI Link 2310
BibRef

Farshian, A.[Anis], Götz, M.[Markus], Cavallaro, G.[Gabriele], Debus, C.[Charlotte], Nießner, M.[Matthias], Benediktsson, J.A.[Jón Atli], Streit, A.[Achim],
Deep-Learning-Based 3-D Surface Reconstruction: A Survey,
PIEEE(111), No. 11, November 2023, pp. 1464-1501.
IEEE DOI 2311
Survey, Surface Reconstruction. BibRef

Clementini, E.[Eliseo], Cohn, A.G.[Anthony G.],
Extension of RCC*-9 to Complex and Three-Dimensional Features and Its Reasoning System,
IJGI(13), No. 1, 2024, pp. 25.
DOI Link 2402
RCC*-9 is a mereotopological qualitative spatial calculus for simple lines and regions. BibRef

Zhou, Y.[Yan], Sun, H.J.[Hua-Jie], Zhang, H.D.[Huai-Dong], Xu, X.M.[Xue-Miao], Yi, C.[Chang'an], Ye, D.[Dewang], Zhou, Y.X.[Yue-Xia], Liu, X.Y.[Xiang-Yu],
GaFL: Geometric-aware Feature Learning for universal 3D models recognition,
PR(149), 2024, pp. 110214.
Elsevier DOI 2403
Universal 3D models recognition, Geometric feature, Spherical convolution, Inactivation fusion BibRef

Patil, S.G.[Supriya Gadi], Chang, A.X.[Angel X.], Savva, M.[Manolis],
Evaluating 3D Shape Analysis Methods for Robustness to Rotation Invariance,
CRV23(63-72)
IEEE DOI 2406
Geometry, Solid modeling, Shape, Feature extraction, Encoding, Robustness, Rotation Invariance, Instance Classification, 3D shape analysis BibRef

Kluger, F.[Florian], Brachmann, E.[Eric], Yang, M.Y.[Michael Ying], Rosenhahn, B.[Bodo],
Robust Shape Fitting for 3D Scene Abstraction,
PAMI(46), No. 9, September 2024, pp. 6306-6325.
IEEE DOI 2408
A few abstract shapes together. Shape, Image reconstruction, Training, Solid modeling, Estimation, Surface reconstruction, Scene abstraction, shape decomposition, minimal solver BibRef

Lin, J.[Jia], Ge, W.C.[Wan-Cheng], Rigoll, G.[Gerhard], Yin, H.L.[Hui-Lin],
CSANet: Cuboid-Wise Shape Augmentation 3D Object Detector for Occluded Targets,
SPLetters(31), 2024, pp. 1750-1754.
IEEE DOI 2408
Shape, Point cloud compression, Proposals, Feature extraction, Detectors, Task analysis, 3D object detection, autonomous driving, shape augmentation BibRef

Huang, H.[Hao], Wang, L.J.[Ling-Jing], Li, X.[Xiang], Yuan, S.H.[Shuai-Hang], Wen, C.C.[Cong-Cong], Hao, Y.[Yu], Fang, Y.[Yi],
Learning to learn point signature for 3D shape geometry,
PRL(184), 2024, pp. 140-147.
Elsevier DOI Code:
WWW Link. 2408
Point signature, Shape registration, Shape segmentation, Meta-learning BibRef

Cheng, H.Z.[Hao-Zhe], Zhu, J.[Jihua], Hu, N.[Naiwen], Chen, J.Q.[Jin-Qian], Yan, W.[Wenbiao],
PTM: Torus Masking for 3D Representation Learning Guided by Robust and Trusted Teachers,
CirSysVideo(34), No. 12, December 2024, pp. 12158-12170.
IEEE DOI 2501
Masked Point Modeling (MPM) typically involves randomly or blockly discarding points or patches and then reconstructing them. Solid modeling, Image reconstruction, Noise, Point cloud compression, Uncertainty, Task analysis, evidence deep learning BibRef

Zhao, M.R.[Ming-Rui], Wang, Y.Z.[Yi-Zhi], Yu, F.G.[Feng-Gen], Zou, C.Q.[Chang-Qing], Mahdavi-Amiri, A.[Ali],
Sweepnet: Unsupervised Learning Shape Abstraction via Neural Sweepers,
ECCV24(XXXVII: 302-320).
Springer DOI 2412
Code:
WWW Link. BibRef

Zhang, C.[Canyu], Li, X.G.[Xiao-Guang], Guo, Q.[Qing], Wang, S.[Song],
SAIR: Learning Semantic-aware Implicit Representation,
ECCV24(IV: 319-335).
Springer DOI 2412
BibRef

Li, C.L.[Chun-Liang], Han, W.C.[Wen-Cheng], Yin, J.[Junbo], Zhao, S.[Sanyuan], Shen, J.B.[Jian-Bing],
REPVF: A Unified Vector Fields Representation for Multi-task 3d Perception,
ECCV24(XXXII: 273-292).
Springer DOI 2412
BibRef

Morgenstern, W.[Wieland], Barthel, F.[Florian], Hilsmann, A.[Anna], Eisert, P.[Peter],
Compact 3D Scene Representation via Self-Organizing Gaussian Grids,
ECCV24(LXXXV: 18-34).
Springer DOI 2412
BibRef

Kim, T.[Taehoon], Na, J.[Jaemin], Hwang, J.W.[Joong-Won], Hwang, W.J.[Won-Jun],
Stay Focus on Object: Cross-Domain Detection Using Domain-Invariant Object Representation,
ICIP24(2487-2493)
IEEE DOI 2411
Training, Object detection, Detectors, Domain Adaptation, Object Detection BibRef

Weng, Y.J.[Yi-Jia], Wen, B.[Bowen], Tremblay, J.[Jonathan], Blukis, V.[Valts], Fox, D.[Dieter], Guibas, L.J.[Leonidas J.], Birchfield, S.[Stan],
Neural Implicit Representation for Building Digital Twins of Unknown Articulated Objects,
CVPR24(3141-3150)
IEEE DOI Code:
WWW Link. 2410
Geometry, Solid modeling, Accuracy, Shape, Buildings, Digital twins, articulated object, neural radiance fields, neural reconstruction BibRef

Sarkar, A.[Ayush], Mai, H.L.[Han-Lin], Mahapatra, A.[Amitabh], Lazebnik, S.[Svetlana], Forsyth, D.A., Bhattad, A.[Anand],
Shadows Don't Lie and Lines Can't Bend! Generative Models Don't know Projective Geometry ... for Now,
CVPR24(28140-28149)
IEEE DOI 2410
Computational modeling, Detectors, Generators, Reliability, generative models, projective geometry, shadows, perspective geometry BibRef

El Banani, M.[Mohamed], Raj, A.[Amit], Maninis, K.K.[Kevis-Kokitsi], Kar, A.[Abhishek], Li, Y.Z.[Yuan-Zhen], Rubinstein, M.[Michael], Sun, D.Q.[De-Qing], Guibas, L.J.[Leonidas J.], Johnson, J.[Justin], Jampani, V.[Varun],
Probing the 3D Awareness of Visual Foundation Models,
CVPR24(21795-21806)
IEEE DOI Code:
WWW Link. 2410
Training, Visualization, Solid modeling, Image segmentation, Codes, Representation Learning, 3D Vision, Foundation Models, 3D Awareness BibRef

Yariv, L.[Lior], Puny, O.[Omri], Gafni, O.[Oran], Lipman, Y.[Yaron],
Mosaic-SDF for 3D Generative Models,
CVPR24(4630-4639)
IEEE DOI 2410
Signed Distance Function (SDF). Training, Point cloud compression, Solid modeling, Shape, Computational modeling, Computer architecture BibRef

Ling, L.[Lu], Sheng, Y.C.[Yi-Chen], Tu, Z.[Zhi], Zhao, W.[Wentian], Xin, C.[Cheng], Wan, K.[Kun], Yu, L.[Lantao], Guo, Q.Y.[Qian-Yu], Yu, Z.X.[Zi-Xun], Lu, Y.W.[Ya-Wen], Li, X.[Xuanmao], Sun, X.[Xingpeng], Ashok, R.[Rohan], Mukherjee, A.[Aniruddha], Kang, H.[Hao], Kong, X.[Xiangrui], Hua, G.[Gang], Zhang, T.Y.[Tian-Yi], Benes, B.[Bedrich], Bera, A.[Aniket],
DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-based 3D Vision,
CVPR24(22160-22169)
IEEE DOI 2410
Representation learning, Solid modeling, Lighting, Benchmark testing, Neural radiance field, Reflection BibRef

Miller, B.[Bailey], Chen, H.Y.[Han-Yu], Lai, A.[Alice], Gkioulekas, I.[Ioannis],
Objects as Volumes: A Stochastic Geometry View of Opaque Solids,
CVPR24(87-97)
IEEE DOI 2410
Geometry, Solid modeling, Surface reconstruction, Lighting, Scattering, Gaussian processes BibRef

Su, Z.[Zhuo], Welling, M.[Max], Pietikäinen, M.[Matti], Liu, L.[Li],
SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud Representation,
3DV22(547-556)
IEEE DOI Code:
WWW Link. 2408
Point cloud compression, Solid modeling, Codes, Computational modeling, Computer architecture, Robustness, Point-cloud-representation BibRef

Xian, Y.Q.[Yong-Qin], Chibane, J.[Julian], Bhatnagar, B.L.[Bharat Lal], Schiele, B.[Bernt], Akata, Z.[Zeynep], Pons-Moll, G.[Gerard],
Any-Shot GIN: Generalizing Implicit Networks for Reconstructing Novel Classes,
3DV22(526-535)
IEEE DOI 2408
Training, Surface reconstruction, Shape, Estimation, Benchmark testing, Rendering (computer graphics), zero shot learning BibRef

Postels, J.[Janis], Danelljan, M.[Martin], Van Gool, L.J.[Luc J.], Tombari, F.[Federico],
ManiFlow: Implicitly Representing Manifolds with Normalizing Flows,
3DV22(84-93)
IEEE DOI 2408
Manifolds, Point cloud compression, Training, Surface reconstruction, Shape, Noise reduction BibRef

Weiherer, M.[Maximilian], Klein, F.[Finn], Egger, B.[Bernhard],
Approximating Intersections and Differences Between Linear Statistical Shape Models Using Markov Chain Monte Carlo,
WACV24(6352-6361)
IEEE DOI 2404
Measurement, Analytical models, Adaptation models, Monte Carlo methods, Shape, Computational modeling, Focusing, Visualization BibRef

de Chanlatte, M.R.[Marissa Ramirez], Colella, P.[Phil], Darrell, T.J.[Trevor J.], Carlson, A.K.[Alexandra Katherine], de With, P.H.N.[Peter H.N.], Deng, H.Y.[Hua-Yu], Guan, S.[Shanyan], Hays, J.[James], Houben, T.[Tim], Huisman, T.[Thomas], Jaipuria, N.[Nikita], Johansen, H.[Hans], Khalid, S.[Shuja], Krishnan, A.[Akshay], Li, C.[Chuming], Pisarenco, M.[Maxim], Raj, A.[Amit], Rudzicz, F.[Frank], Schoonbeek, T.J.[Tim J.], Sridhar, S.[Sandhya], Tseng, N.[Nathan], van der Sommen, F.[Fons], Wang, C.[Chen], Wang, Y.[Yunbo], Wu, T.[Tong], Yang, X.K.[Xiao-Kang], Yao, J.W.[Jia-Wei], Young, D.[Derek], Zhang, X.L.[Xian-Ling],
Proceedings of the Workshop on 3D Geometry Generation for Scientific Computing,
WACVW24(762-766)
IEEE DOI 2404
Geometry, Deep learning, Scientific computing, Pressing BibRef

Stier, N.[Noah], Ranjan, A.[Anurag], Colburn, A.[Alex], Yan, Y.J.[Ya-Jie], Yang, L.[Liang], Ma, F.[Fangchang], Angles, B.[Baptiste],
FineRecon: Depth-aware Feed-forward Network for Detailed 3D Reconstruction,
ICCV23(18377-18386)
IEEE DOI 2401
BibRef

Stathopoulos, A.[Anastasis], Pavlakos, G.[Georgios], Han, L.G.[Li-Gong], Metaxas, D.N.[Dimitris N.],
Learning Articulated Shape with Keypoint Pseudo-Labels from Web Images,
CVPR23(13092-13101)
IEEE DOI 2309
BibRef

Xue, L.[Le], Gao, M.F.[Ming-Fei], Xing, C.[Chen], Martín-Martín, R.[Roberto], Wu, J.J.[Jia-Jun], Xiong, C.M.[Cai-Ming], Xu, R.[Ran], Niebles, J.C.[Juan Carlos], Savarese, S.[Silvio],
ULIP: Learning a Unified Representation of Language, Images, and Point Clouds for 3D Understanding,
CVPR23(1179-1189)
IEEE DOI 2309
BibRef

Li, X.[Xiang], Wen, C.C.[Cong-Cong], Huang, H.[Hao],
Unsupervised 3d Shape Representation Learning Using Normalizing Flow,
ACCV22(I:158-175).
Springer DOI 2307
BibRef

Zhang, T.H.[Tun-Hou], Ma, M.Y.[Ming-Yuan], Yan, F.[Feng], Li, H.[Hai], Chen, Y.[Yiran],
Joint Point Interaction-Dimension Search for 3D Point Cloud,
WACV23(1298-1307)
IEEE DOI 2302
Point cloud compression, Geometry, Solid modeling, Semantic segmentation, Computational modeling, Robotics BibRef

Karmakar, N.[Nilanjana], Biswas, A.[Arindam], Nandy, S.C.[Subhas C.], Bhattacharya, B.B.[Bhargab B.],
On the Construction of Planar Embedding for a Class of Orthogonal Polyhedra,
IWCIA22(84-104).
Springer DOI 2301
2D-representations of 3D digital objects. BibRef

Low, W.F.[Weng Fei], Lee, G.H.[Gim Hee],
Minimal Neural Atlas: Parameterizing Complex Surfaces with Minimal Charts and Distortion,
ECCV22(II:465-481).
Springer DOI 2211
BibRef

Long, X.X.[Xiao-Xiao], Lin, C.[Cheng], Wang, P.[Peng], Komura, T.[Taku], Wang, W.P.[Wen-Ping],
SparseNeuS: Fast Generalizable Neural Surface Reconstruction from Sparse Views,
ECCV22(XXXII:210-227).
Springer DOI 2211
BibRef

Morreale, L.[Luca], Aigerman, N.[Noam], Guerrero, P.[Paul], Kim, V.G.[Vladimir G.], Mitra, N.J.[Niloy J.],
Neural Convolutional Surfaces,
CVPR22(19311-19320)
IEEE DOI 2210
Geometry, Image coding, Dictionaries, Smoothing methods, Shape, Pipelines, Representation learning, Vision + graphics BibRef

Murphy, K.A.[Kieran A.], Jampani, V.[Varun], Ramalingam, S.[Srikumar], Makadia, A.[Ameesh],
Learning ABCs: Approximate Bijective Correspondence for isolating factors of variation with weak supervision,
CVPR22(15989-15999)
IEEE DOI 2210
Deep learning, Codes, Annotations, Focusing, Partitioning algorithms, Representation learning, Self- semi- meta- unsupervised learning BibRef

Athar, A.[Ali], Luiten, J.[Jonathon], Hermans, A.[Alexander], Ramanan, D.[Deva], Leibe, B.[Bastian],
HODOR: High-level Object Descriptors for Object Re-Segmentation in Video Learned from Static Images,
CVPR22(3012-3021)
IEEE DOI 2210
Training, Image coding, Codes, Annotations, Image annotation, Object segmentation, Video analysis and understanding, Self- semi- meta- unsupervised learning BibRef

Rabab, O.[Ouchker], Tahiri, M.A.[Mohamed Amine], Bencherqui, A.[Ahmed], Amakdouf, H.[Hicham], Jamil, M.O.[Mohamed Ouazzani], Qjidaa, H.[Hassan],
Efficient Localization And Reconstruction Of 3D Objects Using The New Hybrid Squire Moment,
ISCV22(1-8)
IEEE DOI 2208
Location awareness, Simulation, Intelligent systems, Image reconstruction, reconstruction BibRef

Shan, M.[Mo], Feng, Q.J.[Qiao-Jun], Jau, Y.Y.[You-Yi], Atanasov, N.[Nikolay],
ELLIPSDF: Joint Object Pose and Shape Optimization with a Bi-level Ellipsoid and Signed Distance Function Description,
ICCV21(5926-5935)
IEEE DOI 2203
Geometry, Simultaneous localization and mapping, Shape, Computational modeling, Semantics, Vision for robotics and autonomous vehicles BibRef

Loiseau, R.[Romain], Monnier, T.[Tom], Aubry, M.[Mathieu], Landrieu, L.[Loïc],
Representing Shape Collections With Alignment-Aware Linear Models,
3DV21(1044-1053)
IEEE DOI 2201
Point cloud compression, Deep learning, Solid modeling, Codes, Shape, Neural networks BibRef

Otero, R., Lagüela, S., Arias, P.,
Algorithm for the Counterclockwise Ordering of Vertexes of Slanted Surfaces Towards the Generation of Semantic GBXML Models,
ISPRS21(B4-2021: 375-381).
DOI Link 2201
BibRef

Chen, G.J.[Gao-Jie], Sun, R.[Ran], Ma, J.[Jie], Wu, B.L.[Bing-Li],
Attention-Based Local Region Aggregation Network for Hierarchical Point Cloud Learning,
ICIP21(3093-3097)
IEEE DOI 2201
Shape, Image processing, Aggregates, Benchmark testing, Point cloud, Region aggregation, Attention mechanism, Hierarchical network BibRef

Yao, S.[Shun], Yang, F.[Fei], Cheng, Y.M.[Yong-Mei], Mozerov, M.G.[Mikhail G.],
3D Shapes Local Geometry Codes Learning with SDF,
DLGC21(2110-2117)
IEEE DOI 2112
Signed Distance Function for 3D descriptions. Geometry, Training, Measurement, Solid modeling, Codes, Shape BibRef

Ali, S.[Sharjeel], van Kaick, O.[Oliver],
Evaluation of Latent Space Learning with Procedurally-Generated Datasets of Shapes,
DLGC21(2086-2094)
IEEE DOI 2112
Solid modeling, Shape, Computational modeling, Shape measurement, Neural networks BibRef

Mihajlovic, M.[Marko], Weder, S.[Silvan], Pollefeys, M.[Marc], Oswald, M.R.[Martin R.],
DeepSurfels: Learning Online Appearance Fusion,
CVPR21(14519-14530)
IEEE DOI 2111
Geometry, Runtime, Shape, Scalability, Pipelines, Machine learning, Rendering (computer graphics) BibRef

Lal, S.[Shamit], Prabhudesai, M.[Mihir], Mediratta, I.[Ishita], Harley, A.W.[Adam W.], Fragkiadaki, K.[Katerina],
CoCoNets: Continuous Contrastive 3D Scene Representations,
CVPR21(12482-12491)
IEEE DOI 2111
Training, Visualization, Solid modeling, Object detection, Predictive models, Feature extraction BibRef

Yang, M.Y.[Ming-Yue], Wen, Y.X.[Yu-Xin], Chen, W.K.[Wei-Kai], Chen, Y.W.[Yong-Wei], Jia, K.[Kui],
Deep Optimized Priors for 3D Shape Modeling and Reconstruction,
CVPR21(3268-3277)
IEEE DOI 2111
Training, Solid modeling, Shape, Particle measurements, Time measurement BibRef

Paschalidou, D.[Despoina], Katharopoulos, A.[Angelos], Geiger, A.[Andreas], Fidler, S.[Sanja],
Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks,
CVPR21(3203-3214)
IEEE DOI 2111
Geometry, Solid modeling, Shape, Computational modeling, Neural networks BibRef

Chen, X.T.[Xiao-Tian], Wang, Y.W.[Yu-Wang], Chen, X.J.[Xue-Jin], Zeng, W.J.[Wen-Jun],
S2R-DepthNet: Learning a Generalizable Depth-specific Structural Representation,
CVPR21(3033-3042)
IEEE DOI 2111
Training, Geometry, Semantics, Estimation, Feature extraction BibRef

Liu, Z.Y.[Ze-Yu], Liu, J.W.[Jian-Wei], Zuo, X.[Xin], Li, W.M.[Wei-Min],
Learning 3D-Craft Generation with Predictive Action Neural Network,
MMMod21(I:541-553).
Springer DOI 2106
Construct houses in Minecraft environment. BibRef

Tattersall, G.[George], Zhu, D.Z.[Di-Zhong], Smith, W.A.P.[William A. P.], Deterding, S.[Sebastian], Huber, P.[Patrik],
Reconstructing Creative Lego Models,
ACCV20(I:55-70).
Springer DOI 2103
BibRef

Zhang, J.M.[Jun-Ming], Yu, M.Y.[Ming-Yuan], Vasudevan, R.[Ram], Johnson-Roberson, M.[Matthew],
Learning Rotation-Invariant Representations of Point Clouds Using Aligned Edge Convolutional Neural Networks,
3DV20(200-209)
IEEE DOI 2102
Task analysis, Training, Convolution, Shape, Sensors, Point Cloud, Deep Learning BibRef

Maboudi, M., Gerke, M., Hack, N., Brohmann, L., Schwerdtner, P., Placzek, G.,
Current Surveying Methods for the Integration of Additive Manufacturing In the Construction Process,
ISPRS20(B4:763-768).
DOI Link 2012
To create the basic conditions for the introduction of additive manufacturing in construction, and thus to pave the way for the use of resource-efficient constructions with a high level of design freedom. 3D Concrete Printing. BibRef

Ma, X.Z.[Xin-Zhu], Liu, S.N.[Shi-Nan], Xia, Z.Y.[Zhi-Yi], Zhang, H.W.[Hong-Wen], Zeng, X.Y.[Xing-Yu], Ouyang, W.L.[Wan-Li],
Rethinking Pseudo-Lidar Representation,
ECCV20(XIII:311-327).
Springer DOI 2011
the efficacy of pseudo-LiDAR representation comes from the coordinate transformation, instead of data representation BibRef

Yang, Z.[Ze], Xu, Y.H.[Ying-Hao], Xue, H.[Han], Zhang, Z.[Zheng], Urtasun, R.[Raquel], Wang, L.W.[Li-Wei], Lin, S.[Stephen], Hu, H.[Han],
Dense Reppoints: Representing Visual Objects with Dense Point Sets,
ECCV20(XXI:227-244).
Springer DOI 2011
BibRef

Cosmo, L.[Luca], Norelli, A.[Antonio], Halimi, O.[Oshri], Kimmel, R.[Ron], Rodolà, E.[Emanuele],
LIMP: Learning Latent Shape Representations with Metric Preservation Priors,
ECCV20(III:19-35).
Springer DOI 2012
BibRef

Cosmo, L.[Luca], Minello, G.[Giorgia], Bronstein, M.M.[Michael M.], Rossi, L.[Luca], Torsello, A.[Andrea],
The Average Mixing Kernel Signature,
ECCV20(XX:1-17).
Springer DOI 2011
signature for points on non-rigid three-dimensional shapes. BibRef

Yu, R.X.[Rui-Xuan], Wei, X.[Xin], Tombari, F.[Federico], Sun, J.[Jian],
Deep Positional and Relational Feature Learning for Rotation-invariant Point Cloud Analysis,
ECCV20(X:217-233).
Springer DOI 2011
BibRef

Sheshappanavar, S.V.[Shivanand Venkanna], Kambhamettu, C.[Chandra],
A Novel Local Geometry Capture in Pointnet++ for 3D Classification,
DLGC20(1059-1068)
IEEE DOI 2008
Ellipsoids, Solid modeling, Feature extraction, Shape, Computational modeling BibRef

Guan, Y.[Yanran], Jahan, T.[Tansin], van Kaick, O.[Oliver],
Generalized Autoencoder for Volumetric Shape Generation,
L3DGM20(1082-1088)
IEEE DOI 2008
Shape, Training, Solid modeling, Manifolds, Interpolation, Decoding BibRef

Chen, N.L.[Neng-Lun], Liu, L.J.[Ling-Jie], Cui, Z.M.[Zhi-Ming], Chen, R.N.[Run-Nan], Ceylan, D.G.[Duy-Gu], Tu, C.H.[Chang-He], Wang, W.P.[Wen-Ping],
Unsupervised Learning of Intrinsic Structural Representation Points,
CVPR20(9118-9127)
IEEE DOI 2008
Shape, Task analysis, Feature extraction, Semantics, Principal component analysis, Machine learning BibRef

Mo, K.C.[Kai-Chun], Guerrero, P.[Paul], Yi, L.[Li], Su, H.[Hao], Wonka, P.[Peter], Mitra, N.J.[Niloy J.], Guibas, L.J.[Leonidas J.],
StructEdit: Learning Structural Shape Variations,
CVPR20(8856-8865)
IEEE DOI 2008
Coding differences in shapes. Shape, Geometry, Decoding, Encoding BibRef

Hao, Z.K.[Ze-Kun], Averbuch-Elor, H.[Hadar], Snavely, N.[Noah], Belongie, S.[Serge],
DualSDF: Semantic Shape Manipulation Using a Two-Level Representation,
CVPR20(7628-7638)
IEEE DOI 2008
Shape, Neural networks, Solid modeling, Surface reconstruction, Automobiles, Couplings BibRef

Nunez, E., Joshi, S.H.,
Deep Learning of Warping Functions for Shape Analysis,
Diff-CVML20(3782-3790)
IEEE DOI 2008
Shape, Machine learning, Computational efficiency, Dynamic programming, Training, Prediction algorithms, Sociology BibRef

Mezghanni, M.[Mariem], Bodrito, T.[Théo], Boulkenafed, M.[Malika], Ovsjanikov, M.[Maks],
Physical Simulation Layer for Accurate 3D Modeling,
CVPR22(13504-13513)
IEEE DOI 2210
Training, Visualization, Solid modeling, Shape, Computational modeling, Programming, Vision + graphics BibRef

Gadelha, M., Gori, G., Ceylan, D., Mech, R., Carr, N., Boubekeur, T., Wang, R., Maji, S.,
Learning Generative Models of Shape Handles,
CVPR20(399-408)
IEEE DOI 2008
Shape, Task analysis, Solid modeling, Interpolation, Silicon, Computational modeling BibRef

Zhu, J., Fang, Y.,
Reference Grid-assisted Network for 3D Point Signature Learning from Point Clouds,
WACV20(211-220)
IEEE DOI 2006
Feature extraction, Robustness, Task analysis, Geometry BibRef

Avants, B.[Brian], Greenblatt, E.[Elliot], Hesterman, J.[Jacob], Tustison, N.[Nicholas],
Deep Volumetric Feature Encoding for Biomedical Images,
WBIR20(91-100).
Springer DOI 2006
BibRef

Achlioptas, P., Guibas, L.J.[Leonidas J.], Goodman, N., Fan, J., Hawkins, R.,
Shapeglot: Learning Language for Shape Differentiation,
ICCV19(8937-8946)
IEEE DOI 2004
CAD, image representation, learning (artificial intelligence), natural languages, object recognition, Pragmatics BibRef

Kulkarni, N., Tulsiani, S., Gupta, A.,
Canonical Surface Mapping via Geometric Cycle Consistency,
ICCV19(2202-2211)
IEEE DOI 2004
object detection, solid modelling, supervised learning, 3D model, extensive manual labeling, Solid modeling BibRef

Littwin, G., Wolf, L.B.,
Deep Meta Functionals for Shape Representation,
ICCV19(1824-1833)
IEEE DOI 2004
Code, 3D.
WWW Link. image classification, image reconstruction, image representation, image resolution, neural nets, shape recognition, BibRef

Cosmo, L.[Luca], Panine, M.[Mikhail], Rampini, A.[Arianna], Ovsjanikov, M.[Maks], Bronstein, M.M.[Michael M.], Rodola, E.[Emanuele],
Isospectralization, or How to Hear Shape, Style, and Correspondence,
CVPR19(7521-7530).
IEEE DOI 2002
Can one recover the shape of a geometric object from its Laplacian spectrum? BibRef

Shen, W.C.[Wei-Chao], Jia, Y.D.[Yun-De], Wu, Y.W.[Yu-Wei],
3D Shape Reconstruction From Images in the Frequency Domain,
CVPR19(4466-4474).
IEEE DOI 2002
BibRef

Yin, K., Chen, Z., Chaudhuri, S., Fisher, M., Kim, V.G., Zhang, H.,
COALESCE: Component Assembly by Learning to Synthesize Connections,
3DV20(61-70)
IEEE DOI 2102
Shape, Geometry, Surface reconstruction, Solid modeling, Transforms, Joining processes BibRef

Muralikrishnan, S.[Sanjeev], Kim, V.G.[Vladimir G.], Fisher, M.[Matthew], Chaudhuri, S.[Siddhartha],
Shape Unicode: A Unified Shape Representation,
CVPR19(3785-3794).
IEEE DOI 2002
BibRef

Park, J.J.[Jeong Joon], Florence, P.[Peter], Straub, J.[Julian], Newcombe, R.A.[Richard A.], Lovegrove, S.J.[Steven J.],
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation,
CVPR19(165-174).
IEEE DOI 2002
BibRef

Ambellan, F.[Felix], Zachow, S.[Stefan], von Tycowicz, C.[Christoph],
An As-invariant-as-possible Gl+(3)-based Statistical Shape Model,
MFCA19(219-228).
Springer DOI 1912
BibRef

Jallouli, M.[Malika], Khalifa, W.B.[Wafa Belhadj], Ben Mabrouk, A.[Anouar], Mahjoub, M.A.[Mohamed Ali],
Toward New Spherical Harmonic Shannon Entropy for Surface Modeling,
CAIP19(II:38-48).
Springer DOI 1909
BibRef

Simpson, I.J.A.[Ivor J.A.], Vicente, S.[Sara], Campbell, N.D.F.[Neill D.F.],
Learning Structured Gaussians to Approximate Deep Ensembles,
CVPR22(366-374)
IEEE DOI 2210
Solid modeling, Uncertainty, Correlation, Computational modeling, Estimation, Predictive models, Statistical methods, 3D from single images BibRef

di Martino, A.[Alessandro], Bodin, E.[Erik], Ek, C.H.[Carl Henrik], Campbell, N.D.F.[Neill D. F.],
Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation,
ACCV18(IV:3-20).
Springer DOI 1906
BibRef

Piewak, F.[Florian], Pinggera, P.[Peter], Enzweiler, M.[Markus], Pfeiffer, D.[David], Zöllner, M.[Marius],
Improved Semantic Stixels via Multimodal Sensor Fusion,
GCPR18(447-458).
Springer DOI 1905
BibRef

Liu, S., Giles, C.L., Ororbia, A.G.,
Learning a Hierarchical Latent-Variable Model of 3D Shapes,
3DV18(542-551)
IEEE DOI 1812
image reconstruction, image representation, image retrieval, learning (artificial intelligence), probability, solid modelling, image reconstruction BibRef

Kuse, M., Jaiswal, S.P., Shen, S.,
Deep-mapnets: A residual network for 3D environment representation,
ICIP17(2652-2656)
IEEE DOI 1803
Cameras, Data models, Rendering (computer graphics), Solid modeling, Training, Transforms, residual network learning BibRef

Zhao, M., Cheung, G., Florencio, D., Ji, X.,
Progressive graph-signal sampling and encoding for static 3D geometry representation,
ICIP17(735-739)
IEEE DOI 1803
Encoding, Geometry, Image coding, Kernel, Manifolds, progressive coding BibRef

Das, S., Bhandarkar, S.M.,
Local Geometry Inclusive Global Shape Representation,
MADO17(1256-1265)
IEEE DOI 1802
Computational modeling, Geometry, Measurement, Optimization, Shape, Strain, Three-dimensional displays, 3D shape representation, shape symmetry BibRef

Zou, C., Yumer, E., Yang, J., Ceylan, D., Hoiem, D.[Derek],
3D-PRNN: Generating Shape Primitives with Recurrent Neural Networks,
ICCV17(900-909)
IEEE DOI 1802
Gaussian processes, image representation, recurrent neural nets, 3D world, 3DPRNN, Gaussian fields, abstract shape representation, Training BibRef

Elhabian, S.[Shireen], Whitaker, R.[Ross],
ShapeOdds: Variational Bayesian Learning of Generative Shape Models,
CVPR17(2185-2196)
IEEE DOI 1711
Bayes methods, Computational modeling, Data models, Image segmentation, Load modeling, Shape, Training BibRef

Sinha, A.[Ayan], Unmesh, A.[Asim], Huang, Q.X.[Qi-Xing], Ramani, K.[Karthik],
SurfNet: Generating 3D Shape Surfaces Using Deep Residual Networks,
CVPR17(791-800)
IEEE DOI 1711
Atmospheric modeling, Geometry, Neural networks, Shape, Solid modeling, Surface reconstruction, BibRef

Toure, E.H.B., Fall, I., Bah, A., Camara, M.S., Ba, M.,
Consistency preserving for evolving megamodels through axiomatic semantics,
ISCV17(1-8)
IEEE DOI 1710
Data models, Software, Unified modeling language, Axiomatic Semantics, Megamodels, Software Evolution. BibRef

Saleem, N.H.[Noor Haitham], Chien, H.J.[Hsiang-Jen], Rezaei, M.[Mahdi], Klette, R.[Reinhard],
Improved Stixel Estimation Based on Transitivity Analysis in Disparity Space,
CAIP17(I: 28-40).
Springer DOI 1708
BibRef

Abbeloos, W.[Wim], Goedemé, T.[Toon],
Point Pair Feature Based Object Detection for Random Bin Picking,
CRV16(432-439)
IEEE DOI 1612
Bin Picking. Representation for free form 3D. BibRef

Firman, M.[Michael],
RGBD Datasets: Past, Present and Future,
LS3D16(661-673)
IEEE DOI 1612
Survey, Datasets. reviewing datasets across eight categories: semantics, object pose estimation, camera tracking, scene reconstruction, object tracking, human actions, faces and identification. BibRef

Pramod, R.T., Arun, S.P.,
Do Computational Models Differ Systematically from Human Object Perception?,
CVPR16(1601-1609)
IEEE DOI 1612
What does the representation do regarding recognition. BibRef

Akizuki, S.[Shuichi], Hashimoto, M.[Manabu],
Physical Reasoning for 3D Object Recognition Using Global Hypothesis Verification,
6DPose16(III: 595-605).
Springer DOI 1611
Can the layout in a scene hypothesis be achieved by using simple collision detection. BibRef

Krcál, M.[Marek], Pilarczyk, P.[Pawel],
Computation of Cubical Steenrod Squares,
CTIC16(140-151).
Springer DOI 1608
BibRef

Lienhardt, P.[Pascal], Peltier, S.[Samuel],
Homology Computation During an Incremental Construction Process,
CTIC16(7-15).
Springer DOI 1608
BibRef

Su, H.[Hang], Maji, S.[Subhransu], Kalogerakis, E.[Evangelos], Learned-Miller, E.G.[Erik G.],
Multi-view Convolutional Neural Networks for 3D Shape Recognition,
ICCV15(945-953)
IEEE DOI 1602
Cameras BibRef

George, D.[David], Tam, G.[Gary], Xie, X.H.[Xiang-Hua],
Analysis of face and segment level descriptors for robust 3D co-segmentation,
BMVW15(xx-yy).
DOI Link 1601
BibRef

Kimmel, R.[Ron],
A Spectral Perspective on Shapes,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Cuesta, J.J.[Jhouben J.], Álvarez, M.A.[Mauricio A.], Orozco, Á.Á.[Álvaro Á.],
Global and Local Gaussian Process for Multioutput and Treed Data,
CIAP15(I:161-171).
Springer DOI 1511
BibRef

Wu, Z.R.[Zhi-Rong], Song, S.[Shuran], Khosla, A.[Aditya], Yu, F.[Fisher], Zhang, L.[Linguang], Tang, X.[Xiaoou], Xiao, J.X.[Jian-Xiong],
3D ShapeNets: A deep representation for volumetric shapes,
CVPR15(1912-1920)
IEEE DOI 1510
BibRef

Godehardt, M.[Michael], Jablonski, A.[Andreas], Wirjadi, O.[Oliver], Schladitz, K.[Katja],
Fast Estimation of Intrinsic Volumes in 3D Gray Value Images,
ISMM15(657-668).
Springer DOI 1506
BibRef

Opgenhaffen, L., Sepers, M.H.,
3D Modelling: Crossing Traditional Boundaries Between Different Research Areas,
3D-Arch15(411-414).
DOI Link 1504
BibRef

Kramarev, V.[Vladislav], Walas, K.[Krzysztof], Leonardis, A.[Aleš],
Categorisation of 3D Objects in Range Images Using Compositional Hierarchies of Parts Based on MDL and Entropy Selection Criteria,
SCIA15(289-301).
Springer DOI 1506
BibRef

Kramarev, V.[Vladislav], Zurek, S.[Sebastian], Wyatt, J.L.[Jeremy L.], Leonardis, A.[Ales],
Object Categorization from Range Images Using a Hierarchical Compositional Representation,
ICPR14(586-591)
IEEE DOI 1412
Feature extraction. hierarchical compositional representation of 3D shape. BibRef

Uhrig, J.[Jonas], Cordts, M.[Marius], Franke, U.[Uwe], Brox, T.[Thomas],
Pixel-Level Encoding and Depth Layering for Instance-Level Semantic Labeling,
GCPR16(14-25).
Springer DOI 1611
Award, GCPR, HM. BibRef

Cordts, M.[Marius], Schneider, L.[Lukas], Enzweiler, M.[Markus], Franke, U.[Uwe], Roth, S.[Stefan],
Object-Level Priors for Stixel Generation,
GCPR14(172-183).
Springer DOI 1411
BibRef

Grbic, S.[Saša], Swee, J.K.Y.[Joshua K.Y.], Ionasec, R.I.[Razvan I.],
ShapeForest: Building Constrained Statistical Shape Models with Decision Trees,
ECCV14(III: 597-612).
Springer DOI 1408
locate points on deformable objects. BibRef

Scharwächter, T.[Timo], Enzweiler, M.[Markus], Franke, U.[Uwe], Roth, S.[Stefan],
Stixmantics: A Medium-Level Model for Real-Time Semantic Scene Understanding,
ECCV14(V: 533-548).
Springer DOI 1408
BibRef

Lee, J.Y.[Joon-Young], Jung, J.Y.[Ji-Young], Bok, Y.[Yunsu], Park, J.[Jaesik], Choi, D.G.[Dong-Geol], Han, Y.[Yudeog], Kweon, I.S.[In So],
Robust Computer Vision Techniques for High-Quality 3D Modeling,
ACPR13(6-10)
IEEE DOI 1408
computer vision BibRef

Liu, Z.B.[Zhen-Bao], Zhang, F.[Feng], Bu, S.H.[Shu-Hui],
Spectral Classification of 3D Articulated Shapes,
MMMod14(II: 315-322).
Springer DOI 1405
BibRef

Rao, Q.[Qing], Grünler, C.[Christian], Hammori, M.[Markus], Chakraborty, S.[Samarjit],
Stixel on the Bus: An Efficient Lossless Compression Scheme for Depth Information in Traffic Scenarios,
MMMod14(I: 568-579).
Springer DOI 1405
BibRef

Urschler, M., Bornik, A., Donoser, M.,
Memory Efficient 3D Integral Volumes,
BD3DCV13(722-729)
IEEE DOI 1403
computer vision BibRef

Fabado, S., Seguí, A.E., Cabrelles, M., Navarro, S., García-De-San-Miguel, D., Lerma, J.L.,
3DVEM Software Modules for Efficient Management of Point Clouds and Photorealistic 3D Models,
CIPA13(255-260).
DOI Link 1311
BibRef

Wegrzyn, D.[Dominik], Alexandre, L.A.[Luís A.],
A Genetic Algorithm-Evolved 3D Point Cloud Descriptor,
CIARP13(I:92-99).
Springer DOI 1311
Descriptor for 3D point clouds. BibRef

Cipolla, R.,
3D shape and its applications,
ICARCV12(11).
IEEE DOI 1304
State of the art review of shape: registration, reconstruction and recognition. BibRef

Wang, P.[Ping], Wang, W.[Wei], Gao, Y.H.[Ying-Hui], Li, S.F.[Shi-Fei],
A recognition approach of 3-D objects based on the Tsallis entropy,
CVRS12(242-245).
IEEE DOI 1302
Spin images related. 3D surface descriptions. BibRef

Veltkamp, R.C.[Remco C.], ter Haar, F.B.[Frank B.],
SHREC 2009: Shape Retrieval Contest,
3DOR09(57-59)
DOI Link 1301
Overview. BibRef

Bronstein, A.M., Bronstein, M.M., Castellani, U., Falcidieno, B., Fusiello, A., Godil, A., Guibas, L.J., Kokkinos, I., Lian, Z., Ovsjanikov, M., Patané, G., Spagnuolo, M., Toldo, R.,
SHREC'10 Track: Robust Shape Retrieval,
EG3DOR10(71-78)
DOI Link 1301
BibRef

Myrcha, J.[Julian], Rokita, P.[Przemyslaw],
Multimedia Objects Conversion for a Digital Repository: A Case Study,
ICCVG12(196-203).
Springer DOI 1210
Format conversion. BibRef

Dezhkam, A.[Arsalan], Kasaei, S.[Shohreh],
A fast 3D reconstruction of inextensible surfaces using adaptive weights,
ICIIP11(1-7).
IEEE DOI 1112
BibRef

Sturm, P.F.[Peter F.],
A Historical Survey of Geometric Computer Vision,
CAIP11(I: 1-8).
Springer DOI 1109
Survey, Geometric. BibRef

Terashima, Y.[Yoshito],
Scene Classification with a Biologically Inspired Method,
CSAIL(TR-2009-020). 2009-05-10
WWW Link. 1101
BibRef Ph.D.Thesis. 2009. Shape-based model in HVS, edges and color. BibRef

Sharma, A.[Avinash], Horaud, R.[Radu],
Shape matching based on diffusion embedding and on mutual isometric consistency,
NORDIA10(29-36).
IEEE DOI 1006
BibRef

Shinagawa, Y.[Yoshihisa], Lin, Y.P.[Yu-Ping],
Untangling fibers by quotient appearance manifold mapping for grayscale shape classification,
ICCV09(2006-2013).
IEEE DOI 0909
Fibers in appearance manifold of shape classes in Euclidean space. BibRef

Wang, B.[Bing], Rushmeier, H.E.[Holly E.],
A compact representation for scanned 3D objects,
3DIM09(1793-1800).
IEEE DOI 0910
Representation to preserve the look of the object (graphics) rather than precise measurements. BibRef

Zhong, Y.[Yu],
Intrinsic shape signatures: A shape descriptor for 3D object recognition,
3DRR09(689-696).
IEEE DOI 0910
BibRef

Pan, H.F.[Hong-Fei], Liang, D.[Don], Tang, J.[Jun], Wang, N.[Nian],
Shape Representation and Clustering Based on Laplacian Spectrum,
CISP09(1-4).
IEEE DOI 0910
BibRef

Colombe, J.B.,
Toward view-invariant representations of object structure learned using object constancy cues in natural movies,
AIPR04(86-91).
IEEE DOI 0410
BibRef

Muffert, M.[Maximilian], Schneider, N.[Nicolai], Franke, U.[Uwe],
Stix-Fusion: A Probabilistic Stixel Integration Technique,
CRV14(16-23)
IEEE DOI 1406
Current measurement BibRef

Pfeiffer, D.[David], Erbs, F.[Friedrich], Franke, U.[Uwe],
Pixels, Stixels, and Objects,
CVVT12(III: 1-10).
Springer DOI 1210
BibRef

Pfeiffer, D.[David], Franke, U.[Uwe],
Towards a Global Optimal Multi-Layer Stixel Representation of Dense 3D Data,
BMVC11(xx-yy).
HTML Version. 1110
BibRef

Badino, H.[Hernán], Franke, U.[Uwe], Pfeiffer, D.[David],
The Stixel World: A Compact Medium Level Representation of the 3D-World,
DAGM09(51-60).
Springer DOI 0909
BibRef

Atmosukarto, I.[Indriyati], Shapiro, L.G.[Linda G.],
A Learning Approach to 3D Object Representation for Classification,
SSPR08(267-276).
Springer DOI 0812
BibRef

Chung, K.L.[Kai Lun], Zhuo, W.[Wei],
Graph-Based Visual Analytic Tools for Parallel Coordinates,
ISVC08(II: 990-999).
Springer DOI 0812
BibRef

Duan, Q.S.[Qi-San], Chen, X.X.[Xue-Xia], Lü, W.X.[Wen-Xu],
Section Approach for Representation of 3-Dimentional Point Clouds,
ISPRS08(B3b: 199 ff).
PDF File. 0807
BibRef

Vetro, A.[Anthony],
3D in the Home: Mass Market or Niche?,
3DTV08(7-8).
IEEE DOI 0805
BibRef

Xu, G.L.[Guo-Liang],
Finite Element Methods for Geometric Modeling and Processing Using General Fourth Order Geometric Flows,
GMP08(xx-yy).
Springer DOI 0804
BibRef

Hahmann, S.[Stefanie], Belayev, A.[Alexander], Buse, L.[Laurent], Elber, G.[Gershon], Mourrain, B.[Bernard], Roessl, C.[Christian],
Shape Interrogation,
ShapeAnalysis08(1). 0802
BibRef

Leng, B.[Biao], Li, L.Q.[Li-Qun], Qin, Z.[Zheng],
MADE: A Composite Visual-Based 3D Shape Descriptor,
MIRAGE07(93-104).
Springer DOI 0703

See also Automatic Combination of Feature Descriptors for Effective 3D Shape Retrieval. BibRef

Dai, J.F.[Jun-Fei], Luo, W.[Wei], Yau, S.T.[Shing-Tung], Gu, X.F.D.[Xian-Feng David],
Geometric Accuracy Analysis for Discrete Surface Approximation,
GMP06(59-72).
Springer DOI 0607
BibRef

Mio, W., Liu, X.W.[Xiu-Wen],
Landmark Representation of Shapes and Fisher-Rao Geometry,
ICIP06(2113-2116).
IEEE DOI 0610
BibRef

Ha, V.H.S., Moura, J.M.F.,
Three-dimensional intrinsic shape,
ICIP04(III: 2099-2102).
IEEE DOI 0505

See also Efficient 2D shape orientation. BibRef

Chao, J.H.[Jin-Hui], Li, F.X.[Fang Xing],
A Surface Model Based on a Fibre Bundle of 1-Parameter Groups of Hamiltonian Lie Algebra,
ICIP05(I: 1021-1024).
IEEE DOI 0512
BibRef

Chao, J.H.[Jin-Hui], Kim, J.D.[Jong-Dae],
A fibre bundle model of surfaces and its generalization,
ICPR04(I: 560-563).
IEEE DOI 0409
BibRef

Vranic, D.V.,
An improvement of rotation invariant 3D-shape descriptor based on functions on concentric spheres,
ICIP03(III: 757-760).
IEEE DOI 0312
BibRef

Kimmel, R.,
Geometric segmentation of 3D structures,
ICIP03(II: 639-642).
IEEE DOI 0312
BibRef

Koenderink, J.J.[Jan J.],
Monocentric Optical Space,
CAIP03(689-696).
Springer DOI 0311
Visual space is a homogeneous, flat non-Euclidean space. Ambiguities in the 2-D view.
See also Structure of Locally Orderless Images, The. BibRef

Wahl, E., Hillenbrand, U.[Ulrich], Hirzinger, G.[Gerd],
Surflet-Pair-Relation Histograms: A Statistical 3D-Shape Representation for Rapid Classification,
3DIM03(474-481).
IEEE DOI 0311
BibRef

Liu, X.G.[Xin-Guo], Sun, R., Kang, S.B.[Sing Bing], Shum, H.Y.[Heung-Yeung],
Directional histogram model for three-dimensional shape similarity,
CVPR03(I: 813-820).
IEEE DOI 0307
captures the shape variation of an object. first extract a directional distribution of thickness histogram signatures. BibRef

Torralba, A.B.[Antonio B.], Freeman, W.T.[William T.],
Properties and Applications of Shape Recipes,
CVPR03(II: 383-390).
IEEE DOI 0307
BibRef
And: MIT AIMAIM-2002-019, December 2002.
WWW Link. In low-level vision, the representation of scene properties such as shape, albedo, etc., are very high dimensional as they have to describe complicated structures. The approach proposed here is to let the image itself bear as much of the representational burden as possible. 0306
BibRef

Freeman, W.T.[William T.], Torralba, A.B.[Antonio B.],
Shape Recipes: Scene Representations that Refer to the Image,
MIT AIMAIM-2002-016, September 2002.
WWW Link. 0306
BibRef

Watanabe, T.[Toshinori], Sugawara, K.[Ken],
Ill-Configured Object Representation by Neighbour Set with Applications to Aerial Image Analyses,
PCV02(A: 387). 0305
BibRef

Sinha, P.[Pawan],
Qualitative Representations for Recognition,
BMCV02(249 ff.).
Springer DOI 0303
BibRef

Lin, Q.F.[Qing-Fen],
Enhancement, Detection, and Visualization of 3D Volume Data,
Ph.D.Thesis, Linkoping University, May, 2003.
HTML Version. BibRef 0305

Danielsson, P.E.[Per-Erik], Lin, Q.[Qingfen],
A New Shape Space for Second Order 3D-Variations,
VF01(145 ff.).
Springer DOI 0209
BibRef

Pollefeys, M.[Marc], Kang, S.B.[Sing Bing], Slabaugh, G.G.[Gregory G.], Cornelis, K.[Kurt], Debevec, P.E.[Paul E.],
Panel Session on Visual Scene Representation,
SMILE00(161 ff.).
Springer DOI 0209
BibRef

Triggs, B.[Bill], Nistér, D.[David], Kanatani, K.[Kenichi], Ponce, J.[Jean], Zhang, Z.Y.[Zheng-You],
Panel Session on Computations and Algorithms,
SMILE00(86 ff.).
Springer DOI 0209
BibRef

Hlavac, V.,
3D reconstruction, omnidirectional vision and understanding of scenes,
BMVC02(Invited Talk). 0208
BibRef

Reed, T.,
The Representation and Coding of Volumetric Images Using the 3-d Derivative of Gaussian Transform,
ICIP01(II: 585-588).
IEEE DOI 0108
BibRef

Lamboray, E., Wumlin, S., Waschbusch, M., Gross, M., Pfister, H.,
Unconstrained free-viewpoint video coding,
ICIP04(V: 3261-3264).
IEEE DOI 0505
BibRef

Pfister, H., Zwicker, M., van Baar, J.[Jeroen], Gross, M.,
Surfels: Surface Elements as Rendering Primitives,
SIGGraph-00(335-343). 2000. Surfel. BibRef 0001

Gross, M.,
Point samples for efficient 3D processing and content creation,
3DPVT04(742-742).
IEEE DOI 0412
BibRef

Sramek, M., Dimitrov, L.I.,
f3d: A file format and tools for storage and manipulation of volumetric data sets,
3DPVT02(368-371). 0206
BibRef

Bilodeau, G.A.[Guillaume-Alexandre], Bergevin, R.[Robert],
Generic Modeling of 3d Objects from Single 2d Images,
ICPR00(Vol I: 770-773).
IEEE DOI 0009
BibRef

Knutsson, H., Andersson, M., Borga, M., Wiklund, J.,
Automated Generation of Representations in Vision,
ICPR00(Vol III: 59-66).
IEEE DOI 0009
Survey. BibRef

Borga, M., Andersson, M., Knutsson, H.,
Generation of Representations for Supervised Learning: A Velocity Estimation Example,
SCIA01(O-W2). 0206
BibRef
Earlier: A3, A1, Only:
Learning visual operators from examples: a new paradigm in image processing,
CIAP99(58-62).
IEEE DOI 9909
BibRef

Mohr, R., Buschmann, R., Falkenhagen, L., Van Gool, L.J., Koch, R.,
CUMULI, PANORAMA, and VANGUARD Project Overview,
SMILE98(xx-yy). BibRef 9800

Johnson, A.E., Hoffman, R., Osborn, J., Hebert, M.,
A System for Semi-Automated Modelling of Complex Environments,
3DIM97(9 - Environment Modeling) 9702
BibRef

Chown, T.J., Lewis, P.H.,
EFRM-based detection and extraction of ridge and valley features in grey level images,
ICPR92(III:339-342).
IEEE DOI 9208
BibRef

Jia, Y.D.[Yun-De],
Description and recognition of curved objects,
ICPR92(III:464-467).
IEEE DOI 9208
BibRef

Abe, N., Itho, F., and Tsuji, S.,
Toward Generation of 3-Dimensional Models of Objects Using 2-Dimensional Figures and Explanations in Language,
IJCAI83(1113-1115). BibRef 8300

Baker, H.H.,
Three-Dimensional Modelling,
IJCAI77(649-655). BibRef 7700

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Generation or Representation of Surface Patches .