11.10 Representation of Parts, Part-Based Models

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Recognition by Components: A Theory of Human Image Understanding,
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Geon Based Object Recognition,
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Matching Image Edges to Object Memory,
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Recognition by Functional Parts,
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Object Recognition by Functional Parts,
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Froimovich, G., Rivlin, E., Shimshoni, I.,
Object classification by functional parts,
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Dickinsona, S.J.[Sven J.], Bergevin, R.[Robert], Biederman, I.[Irving], Eklundh, J.O.[Jan-Olof], Munck-Fairwood, R.C.[Roger C.], Jain, A.K.[Anil K.], Pentland, A.P.[Alex P.],
Panel Report: The Potential Of Geons For Generic 3-D Object Recognition,
IVC(15), No. 4, April 1997, pp. 277-292.
Elsevier DOI 9706
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Dickinson, S.J.[Sven J.], Biederman, I., Pentland, A.P.[Alex P.], Eklundh, J.O., Bergevin, R., and Munck-Fairwood, R.C.,
The Use of Geons for Generic 3-D Object Recognition,
IJCAI93(1693-1699). BibRef 9300

Zerroug, M.[Mourad], Medioni, G.[Gérard],
The challenge of generic object recognition,
ORCV94(217-232).
Springer DOI 9412
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Bennett, B.M., Hoffman, D.D.,
Shape Decomposition for Visual Recognition: The Role of Transversality,
IU87(215-256). BibRef 8700

Levine, M.D., Bergevin, R., and Nguyen, Q.L.,
Shape Description Using Geons as 3D Primitives,
VF91(363-377). Geons. BibRef 9100

Nguyen, Q.L., Levine, M.D.,
Representing 3-D Objects in Range Images Using Geons,
CVIU(63), No. 1, January 1996, pp. 158-168.
DOI Link BibRef 9601
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3-D Object Representation in Range Images Using Geons,
ICPR92(I:149-153).
IEEE DOI BibRef

Wu, K.N., Levine, M.D.,
3D Part Segmentation Using Simulated Electrical Charge Distributions,
PAMI(19), No. 11, November 1997, pp. 1223-1235.
IEEE DOI 9712
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Earlier: ICPR96(I: 14-18).
IEEE DOI 9608
(McGill Univ., CDN) From single or multiple view range data, use simulated electical charge densities on the surface to find local charge density minima, decompose at these points. BibRef

Wu, K., Levine, M.D.,
Recovering Parametric Geons from Multiview Range Data,
CVPR94(159-166).
IEEE DOI BibRef 9400
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Shape Approximation: From Multiview Range Images to Parametric Geons,
ICPR94(A:622-625).
IEEE DOI BibRef
Earlier:
3D Object Representation Using Parametric Geons,
McGillCIM-93-13, 1993. BibRef

Tagare, H.D., Vos, F.M., Jaffe, C.C., Duncan, J.S.,
Arrangement: A Spatial Relation Between Parts for Evaluating Similarity of Tomographic Section,
PAMI(17), No. 9, September 1995, pp. 880-893.
IEEE DOI Descriptions, Parts. Voronoi. Database. BibRef 9509

Tagare, H.D., Jaffe, C.C., Duncan, J.S.,
Arrangement: A Spatial Relation for Describing and Comparing Part Embeddings,
ICPR92(I:91-94).
IEEE DOI BibRef 9200

Munck-Fairwood, R.C.[Roger C.], Du, L.[Li],
Shape Using Volumetric Primitives,
IVC(11), No. 6, July-August 1993, pp. 364-371.
Elsevier DOI BibRef 9307

Wang, D.M.[De Min], Haese-Coat, V.[Veronique], Ronsin, J.[Joseph],
Shape Decomposition and Representation Using a Recursive Morphological Operation,
PR(28), No. 11, November 1995, pp. 1783-1792.
Elsevier DOI Use structuring element. BibRef 9511

Ayoung-Chee, N.[Nigel], Dudek, G.[Gregory], Ferrie, F.P.[Frank P.],
A Hybrid Approach to 3D Representation,
ORCV96(321) 9611
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Ferrie, F.P., Mathur, S., Soucy, G.,
Feature Extraction for 3D Model Building and Recognition,
3DORS93(xx). BibRef 9300

Arcelli, C.[Carlo], Serino, L.[Luca],
From Discs to Parts of Visual Form,
IVC(15), No. 1, January 1997, pp. 1-10.
Elsevier DOI 9702
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Wu, K.N.[Ke-Nong], Levine, M.D.[Martin D.],
3-D Shape Approximation Using Parametric Geons,
IVC(15), No. 2, February 1997, pp. 143-158.
Elsevier DOI 9702
Approximate shape by a set of prescribed models. BibRef

Nishida, H.[Hirobumi],
Structural Feature-Extraction Using Multiple Bases,
CVIU(62), No. 1, July 1995, pp. 78-89.
DOI Link BibRef 9507

Nishida, H.[Hirobumi],
A Structural Approach to Representation of Curved Objects,
PR(30), No. 1, January 1997, pp. 45-56.
Elsevier DOI 9702
BibRef

Pilu, M., Fisher, R.B.,
Part Segmentation from 2D Edge Images by the MDL Criterion,
IVC(15), No. 8, August 1997, pp. 563-573.
Elsevier DOI 9708
BibRef
Earlier: BMVC96(Features, Segmentation). 9608
BibRef
And: DAINo. 817, July 1996. BibRef EdinburghUniversity of Edinburgh Filter hypotheses to retain only those likely to correspond to actual parts. BibRef

Pilu, M., Fisher, R.B.,
Recognition of Geons by Parametric Deformable Contour Models,
ECCV96(I:71-82).
Springer DOI BibRef 9600
And:
Recovery of Generic Solid Parts by Parametrically Deformable Aspects,
DAINo. 801. BibRef EdinburghFind the geons. BibRef

Pilu, M., Fisher, R.B.,
Model-Driven Grouping and Recognition of Generic Object Parts from a Single Image,
RobAS(21), 1997, pp. 107-122. BibRef 9700
Earlier: DAINo. 805, May 1996. Perceptual Grouping. BibRef EdinburghGrouping applied to edge images using models of the parts.
PS File. BibRef

Havaldar, P.[Parag], Medioni, G.[Gerard],
Full Volumetric Descriptions from Three Intensity Images,
PAMI(20), No. 5, May 1998, pp. 540-545.
IEEE DOI 9806
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Inference of Segmented, Volumetric Shape from Intensity Images,
CVPR96(278-284).
IEEE DOI BibRef
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PDF File. Three closely spaced images, derive generalized cylinders. Match the views, label the contours as true or limb edges. BibRef

Havaldar, P.[Parag], Medioni, G.[Gerard],
Segmented Shape Description from 3-View Stereo,
ICCV95(102-108).
IEEE DOI Trinocular Stereo. Generalized cylinder descriptions.
PDF File. BibRef 9500

Cucchiara, R.[Rita], Piccardi, M.[Massimo],
Eliciting visual primitives for detection of elongated shapes,
IVC(17), No. 5/6, April 1999, pp. 347-355.
Elsevier DOI BibRef 9904
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Detection of luminosity profiles of elongated shapes,
ICIP96(III: 635-638).
IEEE DOI 9610
BibRef

Cucchiara, R.[Rita], Piccardi, M.[Massimo], Bariani, M.[Michele], Mello, P.[Paola],
Learning for feature selection and shape detection,
CIAP97(I: 535-542).
Springer DOI 9709
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Zerroug, M.[Mourad], Nevatia, R.[Ramakant],
Part-Based 3D Descriptions of Complex Objects from a Single Image,
PAMI(21), No. 9, September 1999, pp. 835-848.
IEEE DOI BibRef 9909 USC Computer Vision Generalized Cylinder. BibRef
Earlier:
From an Intensity Image to 3-D Segmented Descriptions,
ORCV96(11) 9611
BibRef
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IEEE DOI BibRef USC Computer Vision
PDF File. Exploit the properties of generalized cylinders and the intersections between them.
See also Volumetric Descriptions from a Single Intensity Image. BibRef

Nevatia, R.[Ramakant], and Zerroug, M.[Mourad],
Three-Dimensional Part-Based Descriptions from a Real Intensity Image,
ARPA94(II:1367-1374). BibRef 9400 USC Computer Vision BibRef

van der Meiden, H.A.[Hilderick A.], Bronsvoort, W.F.[Willem F.],
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Vasanthanayaki, C., Annadurai, S.,
Optimal Morphological Shape Decomposition Scheme,
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Svensson, S.[Stina],
A decomposition scheme for 3D fuzzy objects based on fuzzy distance information,
PRL(28), No. 2, 15 January 2007, pp. 224-232.
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Svensson, S.[Stina],
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PRL(29), No. 7, 1 May 2008, pp. 888-896.
Elsevier DOI 0804
Fuzzy distance; Region growing; Watershed segmentation BibRef

Amit, Y., and Geman, D.,
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NeurComp(9), 1997, pp. 1545-1588.
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Amit, Y., and Geman, D.,
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NeurComp(11), 1999, pp. 1691-1715.
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Amit, Y.[Yali], Trouvé, A.[Alain],
POP: Patchwork of Parts Models for Object Recognition,
IJCV(75), No. 2, November 2007, pp. 267-282.
Springer DOI 0710
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Generative Models for Labeling Multi-object Configurations in Images,
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Springer DOI 0711
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Bernstein, E.J.[Elliot Joel], Amit, Y.[Yali],
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Dechter, R.[Rina], Mateescu, R.[Robert],
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AI(171), No. 2-3, February 2007, pp. 73-106.
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Sudderth, E.B.[Erik B.], Torralba, A.B.[Antonio B.], Freeman, W.T.[William T.], Willsky, A.S.[Alan S.],
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IJCV(77), No. 1-3, May 2008, pp. 291-330.
Springer DOI 0803
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Depth from Familiar Objects: A Hierarchical Model for 3D Scenes,
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Pan, X.[Xiang], Chen, Q.H.[Qi Hua], Liu, Z.[Zhi],
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Pan, X.[Xiang], You, Q.[Qian], Liu, Z.[Zhi], Chen, Q.H.[Qi Hua],
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3D shape retrieval; Shape descriptor; Poisson histogram; Part structure BibRef

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Object recognition; Discriminative part; Interest point; Prototype feature vector; C4.5 decision tree; Incremental learning BibRef

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Shape decomposition;discrete optimization;shape representation BibRef

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Hierarchical Compositional Representations of Object Structure,
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Learning a hierarchical compositional representation of multiple object classes,
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Optimization framework for learning a hierarchical shape vocabulary for object class detection,
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Similarity-based cross-layered hierarchical representation for object categorization,
CVPR08(1-8).
IEEE DOI 0806
Spatial arrangement of similar objects. BibRef

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Towards Scalable Representations of Object Categories: Learning a Hierarchy of Parts,
CVPR07(1-8).
IEEE DOI 0706
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Using surfaces and surface relations in an Early Cognitive Vision system,
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Hierarchical representation. BibRef

Sirakov, N.[Nikolay], Arslan, A.N.[Abdullah N.], Hempelmann, C.F.[Christian F.], Attardo, S.[Salvatore], Blount, G.P.[Grady P.],
Firearms identification through partonomy,
SPIE(Newsroom), August 11, 2015
DOI Link 1511
Considering individual parts as functional equivalents of the whole helps automatic image recognition of partially hidden weapons for threat assessment. BibRef

Li, D.[Dong], Li, Y.[Yali], Wang, S.J.[Sheng-Jin],
Discriminative Middle-Level Parts Mining for Object Detection,
IEICE(E98-D), No. 11, November 2015, pp. 1950-1957.
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Mettes, P.S.[Pascal S.], van Gemert, J.C.[Jan C.], Snoek, C.G.M.[Cees G.M.],
No spare parts: Sharing part detectors for image categorization,
CVIU(152), No. 1, 2016, pp. 131-141.
Elsevier DOI 1609
Image categorization BibRef

Tang, Y.X.[Yu-Xing], Wang, X.F.[Xiao-Fang], Dellandréa, E.[Emmanuel], Chen, L.M.[Li-Ming],
Weakly Supervised Learning of Deformable Part-Based Models for Object Detection via Region Proposals,
MultMed(19), No. 2, February 2017, pp. 393-407.
IEEE DOI 1702
image classification BibRef

Tang, Y.X.[Yu-Xing], Wang, X.F.[Xiao-Fang], Dellandrea, E.[Emmanuel], Masnou, S.[Simon], Chen, L.M.[Li-Ming],
Fusing generic objectness and deformable part-based models for weakly supervised object detection,
ICIP14(4072-4076)
IEEE DOI 1502
Accuracy BibRef

Yao, H.T.[Han-Tao], Zhang, D.M.[Dong-Ming], Li, J.T.[Jin-Tao], Zhou, J.S.[Jian-She], Zhang, S.L.[Shi-Liang], Zhang, Y.D.[Yong-Dong],
DSP: Discriminative Spatial Part modeling for Fine-Grained Visual Categorization,
IVC(63), No. 1, 2017, pp. 24-37.
Elsevier DOI 1706
Orientational, Spatial, Part model BibRef

Meng, F.M.[Fan-Man], Li, H.L.[Hong-Liang], Wu, Q.B.[Qing-Bo], Luo, B.[Bing], Ngan, K.N.[King Ngi],
Weakly Supervised Part Proposal Segmentation From Multiple Images,
IP(26), No. 8, August 2017, pp. 4019-4031.
IEEE DOI 1707
image matching, image segmentation, pose estimation, shape recognition, MRF-based single-image segmentation term, NCuts-based part segmentation term, approximation solution, graph matching-based part assignment, multiple-images, multiple-local part modeling, object pose variations, shape feature-based foreground consistency term, BibRef

Shi, H.C.[Heng-Can], Li, H.L.[Hong-Liang], Meng, F.M.[Fan-Man], Wu, Q.B.[Qing-Bo],
Key-Word-Aware Network for Referring Expression Image Segmentation,
ECCV18(VI: 38-54).
Springer DOI 1810
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Shi, H.C.[Heng-Can], Li, H.L.[Hong-Liang], Wu, Q.B.[Qing-Bo], Ngan, K.N.[King Ngi],
Query Reconstruction Network for Referring Expression Image Segmentation,
MultMed(23), 2021, pp. 995-1007.
IEEE DOI 2103
Segment from a natural language query. Image segmentation, Image reconstruction, Visualization, Task analysis, Feature extraction, Natural languages, Semantics, reconstruction BibRef

Gonzalez-Garcia, A.[Abel], Modolo, D.[Davide], Ferrari, V.[Vittorio],
Do Semantic Parts Emerge in Convolutional Neural Networks?,
IJCV(126), No. 5, May 2018, pp. 476-494.
Springer DOI 1804
Analyze layers in NN. BibRef

Modolo, D.[Davide], Ferrari, V.[Vittorio],
Learning Semantic Part-Based Models from Google Images,
PAMI(40), No. 6, June 2018, pp. 1502-1509.
IEEE DOI 1805
Adaptation models, Google, Head, Magnetic heads, Predictive models, Semantics, Training, Part detection, curriculum learning, web learning BibRef

Li, Y.L.[Yue-Long], Hancock, E.R.[Edwin R.], Xiao, Z.T.[Zhi-Tao], Geng, L.[Lei], Wu, J.[Jun], Zhang, F.[Fang], Li, C.Q.[Chun-Qing],
Vertex-level three-dimensional shape deformability measurement based on line segment advection,
IET-CV(12), No. 4, June 2018, pp. 520-526.
DOI Link 1805
partition shape into small components. BibRef

Fouhey, D.F.[David F.], Gupta, A.[Abhinav], Zisserman, A.[Andrew],
From Images to 3D Shape Attributes,
PAMI(41), No. 1, January 2019, pp. 93-106.
IEEE DOI 1812
BibRef
Earlier:
3D Shape Attributes,
CVPR16(1516-1524)
IEEE DOI 1612
Shape, Measurement, Solid modeling, Training, 3D understanding, shape perception, convolutional neural networks. Sculptures. BibRef

Li, C.[Chi], Zia, M.Z.[M. Zeeshan], Tran, Q.H.[Quoc-Huy], Yu, X.[Xiang], Hager, G.D.[Gregory D.], Chandraker, M.[Manmohan],
Deep Supervision with Intermediate Concepts,
PAMI(41), No. 8, August 2019, pp. 1828-1843.
IEEE DOI 1907
BibRef
Earlier:
Deep Supervision with Shape Concepts for Occlusion-Aware 3D Object Parsing,
CVPR17(388-397)
IEEE DOI 1711
Add domain structure to CNN analysis. Solid modeling, Task analysis, Shape, Rendering (computer graphics), object pose estimation. Shape. BibRef

Corcoran, P.[Padraig], Žunic, J.[Joviša], Rosin, P.L.[Paul L.],
A multi-scale topological shape model for single and multiple component shapes,
JVCIR(64), 2019, pp. 102617.
Elsevier DOI 1911
Multiple component shapes, Topology, Multi-scale, Persistent homology BibRef

Mordan, T.[Taylor], Thome, N.[Nicolas], Henaff, G.[Gilles], Cord, M.[Matthieu],
End-to-End Learning of Latent Deformable Part-Based Representations for Object Detection,
IJCV(127), No. 11-12, December 2019, pp. 1659-1679.
Springer DOI 1911
BibRef

Zhang, Y.B.[Ya-Bin], Jia, K.[Kui], Wang, Z.X.[Zhi-Xin],
Part-Aware Fine-Grained Object Categorization Using Weakly Supervised Part Detection Network,
MultMed(22), No. 5, May 2020, pp. 1345-1357.
IEEE DOI 2005
Proposals, Detectors, Task analysis, Streaming media, Feature extraction, Benchmark testing, Supervised learning, weakly supervised learning BibRef

Liu, X., Han, Z., Liu, Y.S., Zwicker, M.,
Fine-Grained 3D Shape Classification With Hierarchical Part-View Attention,
IP(30), 2021, pp. 1744-1758.
IEEE DOI 2101
Shape, Semantics, Feature extraction, Proposals, Automobiles, Airplanes, recurrent neural network BibRef

Zhao, Y.F.[Yi-Fan], Li, J.[Jia], Zhang, Y.[Yu], Song, Y.F.[Ya-Fei], Tian, Y.H.[Yong-Hong],
Ordinal Multi-Task Part Segmentation With Recurrent Prior Generation,
PAMI(43), No. 5, May 2021, pp. 1636-1648.
IEEE DOI 2104
Feature extraction, Task analysis, Shape, Automobiles, Solid modeling, Image segmentation, Semantics, part relationship BibRef

Meng, M.[Meng], Zhang, T.Z.[Tian-Zhu], Yang, W.F.[Wen-Fei], Zhao, J.[Jian], Zhang, Y.D.[Yong-Dong], Wu, F.[Feng],
Diverse Complementary Part Mining for Weakly Supervised Object Localization,
IP(31), 2022, pp. 1774-1788.
IEEE DOI 2202
Location awareness, Task analysis, Proposals, Learning systems, Training, Object detection, Detectors, Part discovery, weakly supervised object localization BibRef

Sharma, G.[Gopal], Goyal, R.[Rishabh], Liu, D.[Difan], Kalogerakis, E.[Evangelos], Maji, S.[Subhransu],
Neural Shape Parsers for Constructive Solid Geometry,
PAMI(44), No. 5, May 2022, pp. 2628-2640.
IEEE DOI 2204
BibRef
Earlier:
CSGNet: Neural Shape Parser for Constructive Solid Geometry,
CVPR18(5515-5523)
IEEE DOI 1812
Shape, Grammar, Task analysis, Decoding, Solid modeling, Constructive solid geometry, reinforcement learning, shape parsing. Visualization, Neural networks, Solids BibRef

Dong, J.H.[Jia-Hua], Cong, Y.[Yang], Sun, G.[Gan], Zhang, T.[Tao], Tang, X.[Xu], Xu, X.W.[Xiao-Wei],
Evolving Metric Learning for Incremental and Decremental Features,
CirSysVideo(32), No. 4, April 2022, pp. 2290-2302.
IEEE DOI 2204
Measurement, Data models, Robot sensing systems, Task analysis, Feature extraction, Extraterrestrial measurements, Optimization, low-rank constraint BibRef

Michieli, U.[Umberto], Zanuttigh, P.[Pietro],
Edge-Aware Graph Matching Network for Part-Based Semantic Segmentation,
IJCV(130), No. 11, November 2022, pp. 2797-2821.
Springer DOI 2210
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Chen, W.T.[Wen-Tao], Zhang, Z.[Zhang], Wang, W.[Wei], Wang, L.[Liang], Wang, Z.[Zilei], Tan, T.N.[Tie-Niu],
Few-shot learning with unsupervised part discovery and part-aligned similarity,
PR(133), 2023, pp. 108986.
Elsevier DOI 2210
Few-shot learning, Self-supervised learning, Part discovery network, Part-aligned similarity BibRef

Rao, Y.M.[Yong-Ming], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
PointGLR: Unsupervised Structural Representation Learning of 3D Point Clouds,
PAMI(45), No. 2, February 2023, pp. 2193-2207.
IEEE DOI 2301
BibRef
Earlier:
Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds,
CVPR20(5375-5384)
IEEE DOI 2008
BibRef
Earlier:
Spherical Fractal Convolutional Neural Networks for Point Cloud Recognition,
CVPR19(452-460).
IEEE DOI 2002
Point cloud compression, Cognition, Task analysis, Semantics, Solid modeling, Representation learning, Point cloud, 3D scene understanding. Semantics, Feature extraction, Shape, Measurement BibRef

Li, X.[Xiao], Wang, Z.Q.[Zi-Qi], Zhang, B.[Bo], Sun, F.C.[Fu-Chun], Hu, X.L.[Xiao-Lin],
Recognizing Object by Components with Human Prior Knowledge Enhances Adversarial Robustness of Deep Neural Networks,
PAMI(45), No. 7, July 2023, pp. 8861-8873.
IEEE DOI 2306
Rocks, Birds, Robustness, Object recognition, Image segmentation, Dogs, Adaptation models, Adversarial robustness, part-based model BibRef

Tertikas, K.[Konstantinos], Paschalidou, D.[Despoina], Pan, B.X.[Bo-Xiao], Park, J.J.[Jeong Joon], Uy, M.A.[Mikaela Angelina], Emiris, I.[Ioannis], Avrithis, Y.[Yannis], Guibas, L.J.[Leonidas J.],
Generating Part-Aware Editable 3D Shapes without 3D Supervision,
CVPR23(4466-4478)
IEEE DOI 2309
BibRef

Ma, Y.C.[Yin-Chao], He, J.F.[Jian-Feng], Yang, D.W.[Da-Wei], Zhang, T.Z.[Tian-Zhu], Wu, F.[Feng],
Adaptive Part Mining for Robust Visual Tracking,
PAMI(45), No. 10, October 2023, pp. 11443-11457.
IEEE DOI 2310
Get parts for tracking. BibRef

Song, X.H.[Xin-Hang], Liu, C.L.[Chen-Long], Zeng, H.T.[Hai-Tao], Zhu, Y.H.[Yao-Hui], Chen, G.W.[Gong-Wei], Qin, X.R.[Xiao-Rong], Jiang, S.Q.[Shu-Qiang],
Composite Object Relation Modeling for Few-Shot Scene Recognition,
IP(32), 2023, pp. 5678-5691.
IEEE DOI 2310
BibRef

Mishra, S.[Samarth], Zhu, P.[Pengkai], Saligrama, V.[Venkatesh],
Interpretable Compositional Representations for Robust Few-Shot Generalization,
PAMI(46), No. 3, March 2024, pp. 1496-1512.
IEEE DOI 2402
Image recognition, Task analysis, Image coding, Semantics, Cognition, Training, Predictive models, Explainable AI, few-shot learning, computer vision BibRef

Han, X.[Xuan], You, M.Y.[Ming-Yu], Lu, P.[Ping],
Improving the Conditional Fine-Grained Image Generation With Part Perception,
MultMed(26), 2024, pp. 4792-4804.
IEEE DOI 2403
Image synthesis, Task analysis, Semantics, Generators, Training, Benchmark testing, Indexes, Fine-grained image generation, part perception BibRef

Xia, J.H.[Jia-Hao], Huang, W.J.[Wen-Jian], Xu, M.[Min], Zhang, J.G.[Jian-Guo], Zhang, H.[Haimin], Sheng, Z.Y.[Zi-Yu], Xu, D.[Dong],
Unsupervised Part Discovery via Dual Representation Alignment,
PAMI(46), No. 12, December 2024, pp. 10597-10613.
IEEE DOI 2411
Semantics, Task analysis, Image segmentation, Generative adversarial networks, Feature extraction, Layout, vision transformer BibRef

Swaminathan, A.[Archana], Gupta, A.[Anubhav], Gupta, K.[Kamal], Maiya, S.R.[Shishira R.], Agarwal, V.[Vatsal], Shrivastava, A.[Abhinav],
LEIA: Latent View-invariant Embeddings for Implicit 3d Articulation,
ECCV24(XVI: 210-227).
Springer DOI 2412
BibRef

Xie, Y.F.[Yun-Fei], Xie, C.[Cihang], Yuille, A.L.[Alan L.], Mei, J.[Jieru],
From Pixels to Objects: A Hierarchical Approach for Part and Object Segmentation Using Local and Global Aggregation,
ECCV24(LXVI: 341-356).
Springer DOI 2412
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Li, S.Q.[Si-Qi], Chen, X.X.[Xiao-Xue], Cheng, H.Y.[Hao-Yu], Zhou, G.[Guyue], Zhao, H.[Hao], Tian, G.Z.[Guan-Zhong],
Locate N' Rotate: Two-stage Openable Part Detection with Foundation Model Priors,
ACCV24(VII: 93-108).
Springer DOI 2412
BibRef

Wu, X.J.[Xin-Jian], Zhang, R.[Ruisong], Qin, J.[Jie], Ma, S.J.[Shi-Jie], Liu, C.L.[Cheng-Lin],
WPS-SAM: Towards Weakly-supervised Part Segmentation with Foundation Models,
ECCV24(XLIV: 314-333).
Springer DOI 2412
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Wang, R.Q.[Rui-Qi], Patil, A.G.[Akshay Gadi], Yu, F.G.[Feng-Gen], Zhang, H.[Hao],
Active Coarse-to-fine Segmentation of Moveable Parts from Real Images,
ECCV24(XXXIV: 111-127).
Springer DOI 2412
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Kim, H.[Hyunjin], Sung, M.[Minhyuk],
Partstad: 2d-to-3d Part Segmentation Task Adaptation,
ECCV24(V: 422-439).
Springer DOI 2412
BibRef

Ng, K.W.[Kam Woh], Zhu, X.T.[Xia-Tian], Song, Y.Z.[Yi-Zhe], Xiang, T.[Tao],
Partcraft: Crafting Creative Objects by Parts,
ECCV24(IX: 420-437).
Springer DOI 2412
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Thai, A.[Anh], Wang, W.Y.[Wei-Yao], Tang, H.[Hao], Stojanov, S.[Stefan], Rehg, J.M.[James M.], Feiszli, M.[Matt],
3X2: 3d Object Part Segmentation by 2d Semantic Correspondences,
ECCV24(XXXVIII: 149-166).
Springer DOI 2412
BibRef

Lei, J.[Jiahui], Wang, Y.[Yufu], Pavlakos, G.[Georgios], Liu, L.J.[Ling-Jie], Daniilidis, K.[Kostas],
GART: Gaussian Articulated Template Models,
CVPR24(19876-19887)
IEEE DOI 2410
Deformable models, Training, Geometry, Deformation, Computational modeling BibRef

Cheng, J.F.[Jun-Feng], Stathaki, T.[Tania],
G-FARS: Gradient-Field-Based Auto-Regressive Sampling for 3D Part Grouping,
CVPR24(27642-27651)
IEEE DOI Code:
WWW Link. 2410
Training, Codes, Shape, Graph neural networks, 3D Point Cloud Processing, 3D Part Grouping, Score-based Models BibRef

Sun, X.H.[Xiao-Hao], Jiang, H.X.[Han-Xiao], Savva, M.[Manolis], Chang, A.[Angel],
OPDMulti: Openable Part Detection for Multiple Objects,
3DV24(169-178)
IEEE DOI 2408
Correlation, Transformers, Task analysis, Artificial intelligence, Robots BibRef

Gaarsdal, J.[Jesper], Haurum, J.B.[Joakim Bruslund], Wolff, S.[Sune], Madsen, C.B.[Claus Brøndgaard],
AssemblyNet: A Point Cloud Dataset and Benchmark for Predicting Part Directions in an Exploded Layout,
WACV24(5824-5833)
IEEE DOI Code:
WWW Link. 2404
Point cloud compression, Solid modeling, Manuals, Benchmark testing, Predictive models, Network architecture, Datasets and evaluations BibRef

Wu, R.[Ruihai], Tie, C.R.[Chen-Rui], Du, Y.S.[Yu-Shi], Zhao, Y.[Yan], Dong, H.[Hao],
Leveraging SE(3) Equivariance for Learning 3D Geometric Shape Assembly,
ICCV23(14265-14274)
IEEE DOI Code:
WWW Link. 2401
BibRef

Li, A.[Abiao], Lv, C.L.[Chen-Lei], Fang, Y.M.[Yu-Ming], Zuo, Y.F.[Yi-Fan],
Laptran: Transformer Embedding Graph Laplacian for Point Cloud Part Segmentation,
ICIP23(3070-3074)
IEEE DOI 2312
BibRef

Tabib, R.A.[Ramesh Ashok], Upasi, N.[Nitishkumar], Anvekar, T.[Tejas], Hegde, D.[Dikshit], Mudenagudi, U.[Uma],
IPD-Net: SO(3) Invariant Primitive Decompositional Network for 3D Point Clouds,
StruCo3D23(2736-2744)
IEEE DOI 2309
BibRef

Wang, L.[Likang], Chen, L.[Lei],
Dionysus: Recovering Scene Structures by Dividing into Semantic Pieces,
CVPR23(12576-12587)
IEEE DOI 2309
BibRef

Li, Y.H.[Yu-Han], Dou, Y.[Yishun], Chen, X.H.[Xuan-Hong], Ni, B.B.[Bing-Bing], Sun, Y.L.[Yi-Lin], Liu, Y.T.[Yu-Tian], Wang, F.Z.[Fu-Zhen],
Generalized Deep 3D Shape Prior via Part-Discretized Diffusion Process,
CVPR23(16784-16794)
IEEE DOI 2309
BibRef

Tang, C.[Chuan], Yang, X.[Xi], Wu, B.J.[Bo-Jian], Han, Z.Z.[Zhi-Zhong], Chang, Y.[Yi],
Parts2Words: Learning Joint Embedding of Point Clouds and Texts by Bidirectional Matching Between Parts and Words,
CVPR23(6884-6893)
IEEE DOI 2309
BibRef

Pan, T.Y.[Tai-Yu], Liu, Q.[Qing], Chao, W.L.[Wei-Lun], Price, B.[Brian],
Towards Open-World Segmentation of Parts,
CVPR23(15392-15401)
IEEE DOI 2309
BibRef

Ramanathan, V.[Vignesh], Kalia, A.[Anmol], Petrovic, V.[Vladan], Wen, Y.[Yi], Zheng, B.X.[Bai-Xue], Guo, B.[Baishan], Wang, R.[Rui], Marquez, A.[Aaron], Kovvuri, R.[Rama], Kadian, A.[Abhishek], Mousavi, A.[Amir], Song, Y.W.[Yi-Wen], Dubey, A.[Abhimanyu], Mahajan, D.[Dhruv],
PACO: Parts and Attributes of Common Objects,
CVPR23(7141-7151)
IEEE DOI 2309
BibRef

Geng, H.R.[Hao-Ran], Li, Z.M.[Zi-Ming], Geng, Y.R.[Yi-Ran], Chen, J.Y.[Jia-Yi], Dong, H.[Hao], Wang, H.[He],
PartManip: Learning Cross-Category Generalizable Part Manipulation Policy from Point Cloud Observations,
CVPR23(2978-2988)
IEEE DOI 2309
BibRef

Xu, X.H.[Xiang-Hao], Guerrero, P.[Paul], Fisher, M.[Matthew], Chaudhuri, S.[Siddhartha], Ritchie, D.[Daniel],
Unsupervised 3D Shape Reconstruction by Part Retrieval and Assembly,
CVPR23(8559-8567)
IEEE DOI 2309
BibRef

He, J.[Ju], Chen, J.[Jieneng], Lin, M.X.[Ming-Xian], Yu, Q.H.[Qi-Hang], Yuille, A.L.[Alan L.],
Compositor: Bottom-Up Clustering and Compositing for Robust Part and Object Segmentation,
CVPR23(11259-11268)
IEEE DOI 2309
BibRef

Wu, C.Z.[Cheng-Zhi], Zheng, J.W.[Jun-Wei], Pfrommer, J.[Julius], Beyerer, J.[Jürgen],
Attention-based Part Assembly for 3D Volumetric Shape Modeling,
StruCo3D23(2717-2726)
IEEE DOI 2309
BibRef

Alsudays, N.[Njuod], Wu, J.[Jing], Lai, Y.K.[Yu-Kun], Ji, Z.[Ze],
AFPSNet: Multi-Class Part Parsing based on Scaled Attention and Feature Fusion,
WACV23(4022-4031)
IEEE DOI 2302
Training, Location awareness, Fuses, Semantics, Focusing, Benchmark testing BibRef

Kawana, Y.[Yuki], Mukuta, Y.[Yusuke], Harada, T.[Tatsuya],
Unsupervised Pose-aware Part Decomposition for Man-Made Articulated Objects,
ECCV22(III:558-575).
Springer DOI 2211
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Chen, Y.C.[Yun-Chun], Li, H.[Haoda], Turpin, D.[Dylan], Jacobson, A.[Alec], Garg, A.[Animesh],
Neural Shape Mating: Self-Supervised Object Assembly with Adversarial Shape Priors,
CVPR22(12714-12723)
IEEE DOI 2210
Point cloud compression, Training, Surface reconstruction, Shape, Semantics, Pipelines, Visual reasoning, Datasets and evaluation BibRef

Jones, R.K.[R. Kenny], Habib, A.[Aalia], Hanocka, R.[Rana], Ritchie, D.[Daniel],
The Neurally-Guided Shape Parser: Grammar-based Labeling of 3D Shape Regions with Approximate Inference,
CVPR22(11604-11613)
IEEE DOI 2210
Training, Solid modeling, Shape, Semantics, Neural networks, Search problems, Segmentation, grouping and shape analysis, Vision+graphics BibRef

Singh, R.[Rishubh], Gupta, P.[Pranav], Shenoy, P.[Pradeep], Sarvadevabhatla, R.[Ravikiran],
FLOAT: Factorized Learning of Object Attributes for Improved Multi-object Multi-part Scene Parsing,
CVPR22(1435-1445)
IEEE DOI 2210
Codes, Scalability, Semantics, Focusing, Benchmark testing, Segmentation, grouping and shape analysis, Scene analysis and understanding BibRef

Ziegler, A.[Adrian], Asano, Y.M.[Yuki M.],
Self-Supervised Learning of Object Parts for Semantic Segmentation,
CVPR22(14482-14491)
IEEE DOI 2210
Image segmentation, Semantics, Merging, Self-supervised learning, Benchmark testing, Image representation, Transformers, retrieval BibRef

Zoran, D.[Daniel], Kabra, R.[Rishabh], Lerchner, A.[Alexander], Rezende, D.J.[Danilo J.],
PARTS: Unsupervised segmentation with slots, attention and independence maximization,
ICCV21(10419-10427)
IEEE DOI 2203
Solid modeling, Visualization, Analytical models, Image color analysis, Motion segmentation, Predictive models, Neural generative models BibRef

Yao, C.H.[Chun-Han], Hung, W.C.[Wei-Chih], Jampani, V.[Varun], Yang, M.H.[Ming-Hsuan],
Discovering 3D Parts from Image Collections,
ICCV21(12961-12970)
IEEE DOI 2203
Geometry, Codes, Shape, Cognition, Task analysis, 3D from a single image and shape-from-x, BibRef

Roberts, D.[Dominic], Danielyan, A.[Ara], Chu, H.[Hang], Golparvar-Fard, M.[Mani], Forsyth, D.A.[David A.],
LSD-StructureNet: Modeling Levels of Structural Detail in 3D Part Hierarchies,
ICCV21(5816-5825)
IEEE DOI 2203
Fabrication, Solid modeling, Limiting, Shape, Computational modeling, Neural generative models, Representation learning, Vision applications and systems BibRef

Gadre, S.Y.[Samir Yitzhak], Ehsani, K.[Kiana], Song, S.[Shuran],
Act the Part: Learning Interaction Strategies for Articulated Object Part Discovery,
ICCV21(15732-15741)
IEEE DOI 2203
Couplings, Codes, Motion segmentation, Computational modeling, Semantics, Data models, Vision + other modalities BibRef

Wang, X.G.[Xiao-Gang], Sun, X.[Xun], Cao, X.Y.[Xin-Yu], Xu, K.[Kai], Zhou, B.[Bin],
Learning Fine-Grained Segmentation of 3D Shapes without Part Labels,
CVPR21(10271-10280)
IEEE DOI 2111
Training, Solid modeling, Shape, Semantics, Graph neural networks BibRef

Braun, S.[Sandro], Esser, P.[Patrick], Ommer, B.[Björn],
Unsupervised Part Discovery by Unsupervised Disentanglement,
GCPR20(345-359).
Springer DOI 2110
BibRef

Naha, S.[Shujon], Xiao, Q.Y.[Qing-Yang], Banik, P.[Prianka], Reza, M.A.[Md Alimoor], Crandall, D.J.[David J.],
Part Segmentation of Unseen Objects using Keypoint Guidance,
WACV21(1741-1749)
IEEE DOI 2106
Training, Annotations, Animals, Transfer learning, Data models BibRef

Hayden, D.S., Pacheco, J., Fisher, III, J.W.,
Nonparametric Object and Parts Modeling With Lie Group Dynamics,
CVPR20(7424-7433)
IEEE DOI 2008
Hidden Markov models, Dynamics, Computational modeling, Bayes methods, Indexes BibRef

Deng, B.Y.[Bo-Yang], Genova, K.[Kyle], Yazdani, S.[Soroosh], Bouaziz, S.[Sofien], Hinton, G.[Geoffrey], Tagliasacchi, A.[Andrea],
CvxNet: Learnable Convex Decomposition,
CVPR20(31-41)
IEEE DOI 2008
Shape, Geometry, Google, Training, Image reconstruction, Computational modeling BibRef

Gal, R.[Rinon], Bermano, A.[Amit], Zhang, H.[Hao], Cohen-Or, D.[Daniel],
MRGAN: Multi-Rooted 3D Shape Representation Learning with Unsupervised Part Disentanglement,
StruCo3D21(2039-2048)
IEEE DOI 2112
Training, Measurement, Codes, Shape, Semantics, Generative adversarial networks BibRef

Schor, N.[Nadav], Katzir, O.[Oren], Zhang, H.[Hao], Cohen-Or, D.[Daniel],
CompoNet: Learning to Generate the Unseen by Part Synthesis and Composition,
ICCV19(8758-8767)
IEEE DOI 2004
learning (artificial intelligence), neural nets, object recognition, CompoNet, data-driven generative modeling, Neural networks BibRef

Zhao, X.Y.[Xiang-Yun], Yang, Y.[Yi], Zhou, F.[Feng], Tan, X.[Xiao], Yuan, Y.C.[Yu-Chen], Bao, Y.Z.[Ying-Ze], Wu, Y.[Ying],
Recognizing Part Attributes With Insufficient Data,
ICCV19(350-360)
IEEE DOI 2004
image annotation, image recognition, image representation, learning (artificial intelligence), Feature extraction BibRef

Rampini, A.[Arianna], Tallini, I.[Irene], Ovsjanikov, M.[Maks], Bronstein, A.M.[Alex M.], Rodolà, E.[Emanuele],
Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment,
3DV19(37-46)
IEEE DOI 1911
localizing relevant subsets of non-rigid geometric shapes given only a partial 3D query as the input. Shape, Eigenvalues and eigenfunctions, Geometry, Laplace equations, Spectral geometry BibRef

Yao, Q.[Qi], Gong, X.J.[Xiao-Jin],
Exploiting LSTM for Joint Object and Semantic Part Detection,
ACCV18(V:498-512).
Springer DOI 1906
BibRef

Xie, S.N.[Sai-Ning], Liu, S.N.[Sai-Nan], Chen, Z.Y.[Ze-Yu], Tu, Z.W.[Zhuo-Wen],
Attentional ShapeContextNet for Point Cloud Recognition,
CVPR18(4606-4615)
IEEE DOI 1812
Shape, Kernel, Neural networks BibRef

Lu, C., Su, H., Li, Y., Lu, Y., Yi, L., Tang, C., Guibas, L.J.,
Beyond Holistic Object Recognition: Enriching Image Understanding with Part States,
CVPR18(6955-6963)
IEEE DOI 1812
Semantics, Image segmentation, Task analysis, Visualization, Training, Image color analysis, Object recognition BibRef

Yang, L.W.[Lu-Wei], Zhu, L.G.[Li-Geng], Wei, Y.C.[Yi-Chen], Liang, S.[Shuang], Tan, P.[Ping],
Attribute Recognition from Adaptive Parts,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Kirillov, A.[Alexander], Gavrikov, M.[Mikhail], Lobacheva, E.[Ekaterina], Osokin, A.[Anton], Vetrov, D.[Dmitry],
Deep Part-Based Generative Shape Model with Latent Variables,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Vu, H., Pho, K., Le, B.,
Flexible 3D neighborhood cascade deformable part models for object detection,
ICIP17(910-914)
IEEE DOI 1803
Computational modeling, Deformable models, Image resolution, Object detection, Solid modeling, Strain, Object Detection BibRef

Cheng, H.C., Varshney, A.,
Volume segmentation using convolutional neural networks with limited training data,
ICIP17(590-594)
IEEE DOI 1803
Encoding, Image segmentation, Kernel, Microscopy, Training, volume segmentation BibRef

Song, Y., Chen, X., Li, J., Zhao, Q.,
Embedding 3D Geometric Features for Rigid Object Part Segmentation,
ICCV17(580-588)
IEEE DOI 1802
feature extraction, image segmentation, teaching, 2-stream CNN, 2-stream FCN, 2D appearance features, BibRef

Shih, Y.F.[Ya-Fang], Yeh, Y.M.[Yang-Ming], Lin, Y.Y.[Yen-Yu], Weng, M.F.[Ming-Fang], Lu, Y.C.[Yi-Chang], Chuang, Y.Y.[Yung-Yu],
Deep Co-occurrence Feature Learning for Visual Object Recognition,
CVPR17(7302-7311)
IEEE DOI 1711
Convolutional codes, Correlation, Feature extraction, Neurons, Object recognition, Strain, Visualization BibRef

Sicre, R., Rabin, J., Avrithis, Y., Furon, T., Jurie, F., Kijak, E.,
Automatic Discovery of Discriminative Parts as a Quadratic Assignment Problem,
CEFR-LCV17(1059-1068)
IEEE DOI 1802
Entropy, Linear programming, Minimization, Optimization, Training BibRef

Sicre, R., Avrithis, Y., Kijak, E., Jurie, F.,
Unsupervised Part Learning for Visual Recognition,
CVPR17(3116-3124)
IEEE DOI 1711
Computational modeling, Image recognition, Image retrieval, Neural networks, Training BibRef

Yi, L., Su, H., Guo, X., Guibas, L.J.,
SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation,
CVPR17(6584-6592)
IEEE DOI 1711
Convolution, Kernel, Laplace equations, Shape, Solid modeling, Spectral analysis, BibRef

Ganapathi-Subramanian, V.[Vignesh], Diamanti, O.[Olga], Pirk, S.[Soeren], Tang, C.C.[Cheng-Cheng], Niessner, M.[Matthias], Guibas, L.J.[Leonidas J.],
Parsing Geometry Using Structure-Aware Shape Templates,
3DV18(672-681)
IEEE DOI 1812
image colour analysis, image reconstruction, neural nets, object recognition, parsing geometry, Template Fitting BibRef

Tulsiani, S.[Shubham], Su, H., Guibas, L.J.[Leonidas J.], Efros, A.A.[Alexei A.], Malik, J.[Jitendra],
Learning Shape Abstractions by Assembling Volumetric Primitives,
CVPR17(1466-1474)
IEEE DOI 1711
Image reconstruction, Shape, Visualization BibRef

Sarvadevabhatla, R.K.[Ravi Kiran], Venkatraman, S.[Shanthakumar], Babu, R.V.[R. Venkatesh],
Partly First Among Equals: Semantic Part-Based Benchmarking for State-of-the-Art Object Recognition Systems,
ACCV16(V: 181-197).
Springer DOI 1704
BibRef

Hoschl, C., Flusser, J.,
Decomposition of 3D Binary Objects into Rectangular Blocks,
DICTA16(1-8)
IEEE DOI 1701
Algorithm design and analysis BibRef

Kulkarni, P.[Praveen], Jurie, F.[Frédéric], Zepeda, J.[Joaquin], Pérez, P.[Patrick], Chevallier, L.[Louis],
SPLeaP: Soft Pooling of Learned Parts for Image Classification,
ECCV16(VIII: 329-345).
Springer DOI 1611
BibRef

Ntouskos, V.[Valsamis], Sanzari, M.[Marta], Cafaro, B.[Bruno], Nardi, F.[Federico], Natola, F.[Fabrizio], Pirri, F.[Fiora], Ruiz, M.[Manuel],
Component-Wise Modeling of Articulated Objects,
ICCV15(2327-2335)
IEEE DOI 1602
Computational modeling. Model component parts. BibRef

Ren, Z., Wang, C., Yuille, A.L.,
Scene-Domain Active Part Models for Object Representation,
ICCV15(2497-2505)
IEEE DOI 1602
Cameras BibRef

Yang, L.X.[Ling-Xiao], Xie, X.H.[Xiao-Hua],
Max-margin analysis based patch sampling for discovery of mid-level parts,
ICIP15(2214-2218)
IEEE DOI 1512
Mid-level part; bag-of-parts; scene classification; visual code-book BibRef

Rubio, J.C.[Jose C.], Ommer, B.[Bjorn],
Regularizing max-margin exemplars by reconstruction and generative models,
CVPR15(4213-4221)
IEEE DOI 1510
BibRef

Kitano, Y., Takiguchi, T., Ariki, Y.,
Estimation of object functions using deformable part model,
FCV15(1-4)
IEEE DOI 1506
object recognition BibRef

Delabarre, B.[Bertrand], Marchand, E.[Eric],
Dense non-rigid visual tracking with a robust similarity function,
ICIP14(4942-4946)
IEEE DOI 1502
Equations BibRef

Zhang, Y.H.[Ying-Hua], Cai, L.[Ling], Chen, L.Y.[Lu-Yan], Zhao, Y.M.[Yu-Ming],
A scene-specific deformable part-based model for object detection,
ICIP14(2324-2328)
IEEE DOI 1502
Adaptation models BibRef

Jeong, H.[Hawook], Yun, S.D.[Sang-Doo], Yi, K.M.[Kwang Moo], Choi, J.Y.[Jin Young],
Category Attentional Search for Fast Object Detection by Mimicking Human Visual Perception,
WACV15(829-836)
IEEE DOI 1503
Computational modeling BibRef

Yun, S.D.[Sang-Doo], Jeong, H.[Hawook], Kang, W.S.[Woo-Sung], Heo, B.H.[Byeong-Ho], Choi, J.Y.[Jin Young],
Self-Organizing Cascaded Structure of Deformable Part Models for Fast Object Detection,
ICPR14(4246-4250)
IEEE DOI 1412
Accuracy BibRef

Riabchenko, E.[Ekaterina], Kamarainen, J.K.[Joni-Kristian], Chen, K.[Ke],
Learning Generative Models of Object Parts from a Few Positive Examples,
ICPR14(2287-2292)
IEEE DOI 1412
Estimation BibRef

Boussaid, H.[Haithem], Kokkinos, I.[Iasonas],
Fast and Exact: ADMM-Based Discriminative Shape Segmentation with Loopy Part Models,
CVPR14(4058-4065)
IEEE DOI 1409
ADMM: Alternating Direction Method of Multipliers. Segment organs. BibRef

Liu, J.X.[Jiong-Xin], Li, Y.X.[Yin-Xiao], Belhumeur, P.N.[Peter N.],
Part-Pair Representation for Part Localization,
ECCV14(II: 456-471).
Springer DOI 1408
BibRef

Sun, C.B.[Chao-Bo], Wang, X.J.[Xiao-Jie],
A Ranking Part Model for Object Detection,
SSSPR14(414-423).
Springer DOI 1408
BibRef

Fouhey, D.F.[David Ford], Hussain, W., Gupta, A.[Abhinav], Hebert, M.[Martial],
Single Image 3D without a Single 3D Image,
ICCV15(1053-1061)
IEEE DOI 1602
Detectors BibRef

Fouhey, D.F.[David Ford], Gupta, A.[Abhinav], Hebert, M.[Martial],
Unfolding an Indoor Origami World,
ECCV14(VI: 687-702).
Springer DOI 1408
BibRef
Earlier:
Data-Driven 3D Primitives for Single Image Understanding,
ICCV13(3392-3399)
IEEE DOI 1403
What primitives to use. BibRef

Xie, L.X.[Ling-Xi], Tian, Q.[Qi], Hong, R.C.[Ri-Chang], Yan, S.C.[Shui-Cheng], Zhang, B.[Bo],
Hierarchical Part Matching for Fine-Grained Visual Categorization,
ICCV13(1641-1648)
IEEE DOI 1403
Fine-Grained Visual Categorization BibRef

Shrivastava, A.[Abhinav], Gupta, A.[Abhinav],
Building Part-Based Object Detectors via 3D Geometry,
ICCV13(1745-1752)
IEEE DOI 1403
3D object detection
See also Enriching Visual Knowledge Bases via Object Discovery and Segmentation. BibRef

Girshick, R.[Ross], Malik, J.[Jitendra],
Training Deformable Part Models with Decorrelated Features,
ICCV13(3016-3023)
IEEE DOI 1403
BibRef

Zhang, N.[Ning], Farrell, R.[Ryan], Iandola, F.[Forrest], Darrell, T.J.[Trevor J.],
Deformable Part Descriptors for Fine-Grained Recognition and Attribute Prediction,
ICCV13(729-736)
IEEE DOI 1403
BibRef

Chai, Y.N.[Yu-Ning], Lempitsky, V.[Victor], Zisserman, A.[Andrew],
Symbiotic Segmentation and Part Localization for Fine-Grained Categorization,
ICCV13(321-328)
IEEE DOI 1403
Detection; Fine-Grained; Object Recognition; Segmentation BibRef

Xie, L.X.[Ling-Xi], Tian, Q.[Qi], Zhang, B.[Bo],
Feature normalization for part-based image classification,
ICIP13(2607-2611)
IEEE DOI 1402
Experiments BibRef

Xiong, H.C.[Han-Chen], Szedmak, S.[Sandor], Piater, J.H.[Justus H.],
3D Object Class Geometry Modeling with Spatial Latent Dirichlet Markov Random Fields,
GCPR13(51-60).
Springer DOI 1311
part-based geometry model BibRef

Jiang, F.Y.[Fang-Yuan], Enqvist, O.[Olof], Kahl, F.[Fredrik], Åström, K.[Kalle],
Improved Object Detection and Pose Using Part-Based Models,
SCIA13(396-407).
Springer DOI 1311
BibRef

Levi, D.[Dan], Silberstein, S.[Shai], Bar-Hillel, A.[Aharon],
Fast Multiple-Part Based Object Detection Using KD-Ferns,
CVPR13(947-954)
IEEE DOI 1309
Object Detection BibRef

Wetzler, A.[Aaron], Aflalo, Y.[Yonathan], Dubrovina, A.[Anastasia], Kimmel, R.[Ron],
The Laplace-Beltrami Operator: A Ubiquitous Tool for Image and Shape Processing,
ISMM13(302-316).
Springer DOI 1305
Filtering BibRef

Ma, C.[Chang], Dong, Z.Q.[Zhong-Qian], Jiang, T.T.[Ting-Ting], Wang, Y.Z.[Yi-Zhou], Gao, W.[Wen],
A Method of Perceptual-Based Shape Decomposition,
ICCV13(873-880)
IEEE DOI 1403
BibRef
Earlier: A3, A2, A1, A4, Only:
Toward Perception-Based Shape Decomposition,
ACCV12(II:188-201).
Springer DOI 1304
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Wang, X., Gillibert, L., Flin, F., Coeurjolly, D.,
Curvature-driven volumetric segmentation of binary shapes: An application to snow microstructure analysis,
ICPR12(742-745).
WWW Link. 1302
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Zhang, H.G.[Hui-Gang], Bai, X.[Xiao], Cheng, J.[Jian], Zhou, J.[Jun], Zhao, H.J.[Hui-Jie],
An Incremental Structured Part Model for Image Classification,
SSSPR12(483-491).
Springer DOI 1211
incremental, using part model BibRef

Maji, S.[Subhransu],
Discovering a Lexicon of Parts and Attributes,
WPA12(III: 21-30).
Springer DOI 1210
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Litany, O.[Or], Bronstein, A.M.[Alexander M.], Bronstein, M.M.[Michael M.],
Putting the Pieces Together: Regularized Multi-part Shape Matching,
NORDIA12(I: 1-11).
Springer DOI 1210
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Mottaghi, R.[Roozbeh],
Augmenting deformable part models with irregular-shaped object patches,
CVPR12(3116-3123).
IEEE DOI 1208
BibRef

Mottaghi, R.[Roozbeh], Ranganathan, A.[Ananth], Yuille, A.L.[Alan L.],
A compositional approach to learning part-based models of objects,
3DRR11(561-568).
IEEE DOI 1201
BibRef

Pandey, M.[Megha], Lazebnik, S.[Svetlana],
Scene recognition and weakly supervised object localization with deformable part-based models,
ICCV11(1307-1314).
IEEE DOI 1201
BibRef

Parkhi, O.M.[Omkar M.], Vedaldi, A.[Andrea], Zisserman, A.[Andrew], Jawahar, C.V.,
Cats and dogs,
CVPR12(3498-3505).
IEEE DOI 1208
BibRef
Earlier: A1, A2, A4, A3:
The truth about cats and dogs,
ICCV11(1427-1434).
IEEE DOI 1201
Use templates for parts of highly deformable objects, to get best of templates and bag of words. BibRef

Ott, P.[Patrick], Everingham, M.[Mark],
Shared parts for deformable part-based models,
CVPR11(1513-1520).
IEEE DOI 1106
BibRef

Venkateshkumar, S.K., Sridhar, M., Ott, P.,
Latent Hierarchical Part Based Models for Road Scene Understanding,
CVRoads15(115-123)
IEEE DOI 1602
Detectors BibRef

Varanasi, K.[Kiran], Boyer, E.[Edmond],
Temporally coherent segmentation of 3D reconstructions,
3DPVT10(xx-yy).
WWW Link. 1005
3D from multiple views and silhouettes. Describe motions of convex parts. BibRef

Akcay, H.G.[Huseyin Gokhan], Aksoy, S.[Selim], Soille, P.[Pierre],
Hierarchical Segmentation of Complex Structures,
ICPR10(1120-1123).
IEEE DOI 1008
BibRef

Lu, W.H.[Wen-Hao], Wang, S.J.[Sheng-Jin], Ding, X.Q.[Xiao-Qing],
Part Detection, Description and Selection Based on Hidden Conditional Random Fields,
ICPR10(657-660).
IEEE DOI 1008
BibRef

Lai, R.J.[Rong-Jie], Shi, Y.G.[Yong-Gang], Scheibel, K.[Kevin], Fears, S.[Scott], Woods, R.[Roger], Toga, A.W.[Arthur W.], Chan, T.F.[Tony F.],
Metric-induced optimal embedding for intrinsic 3D shape analysis,
CVPR10(2871-2878).
IEEE DOI 1006
Laplace-Beltrami (LB) embedding has problems. BibRef

Xia, X.Z.[Xiao-Zhen], Yang, W.Y.[Wu-Yi], Li, H.P.[He-Ping], Zhang, S.W.[Shu-Wu],
Part-Based Object Detection Using Cascades of Boosted Classifiers,
ACCV09(II: 556-565).
Springer DOI 0909
BibRef

Kumar, M.P.[M. Pawan], Zisserman, A.[Andrew], Torr, P.H.S.[Philip H.S.],
Efficient discriminative learning of parts-based models,
ICCV09(552-559).
IEEE DOI 0909
BibRef

Cheng, X.G.[Xian-Gang], Hu, Y.Q.[Yi-Qun], Chia, L.T.[Liang-Tien],
Hierarchical word image representation for parts-based object recognition,
ICIP09(301-304).
IEEE DOI 0911
BibRef

Sullivan, J., Danielsson, O., Carlsson, S.,
Exploiting Part-Based Models and Edge Boundaries for Object Detection,
DICTA08(199-206).
IEEE DOI 0812
BibRef

Artner, N.M.[Nicole M.], Ion, A.[Adrian], Kropatsch, W.G.[Walter G.],
Spatio-Temporal Extraction of Articulated Models in a Graph Pyramid,
GbRPR11(215-224).
Springer DOI 1105
BibRef
Earlier:
Rigid Part Decomposition in a Graph Pyramid,
CIARP09(758-765).
Springer DOI 0911
BibRef

Stommel, M., Herzog, O.,
SIFT-based object recognition with fast alphabet creation and reduced curse of dimensionality,
IVCNZ09(136-141).
IEEE DOI 0911
BibRef

Stommel, M., Kuhnert, K.D.,
Part aggregation in a compositional model based on the evaluation of feature cooccurrence statistics,
IVCNZ08(1-6).
IEEE DOI 0811
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Ma, W.[Wei], Xiang, B.[Bo], Zhang, X.P.[Xiao-Peng], Zha, H.B.[Hong-Bin],
Decomposition of branching volume data by tip detection,
ICIP08(1948-1951).
IEEE DOI 0810
BibRef

Karlinsky, L.[Leonid], Ullman, S.[Shimon],
Using Linking Features in Learning Non-parametric Part Models,
ECCV12(III: 326-339).
Springer DOI 1210
BibRef

Karlinsky, L.[Leonid], Dinerstein, M.[Michael], Harari, D.[Daniel], Ullman, S.[Shimon],
The chains model for detecting parts by their context,
CVPR10(25-32).
IEEE DOI Video of talk:
WWW Link. 1006
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Karlinsky, L.[Leonid], Dinerstein, M.[Michael], Ullman, S.[Shimon],
Unsupervised feature optimization (UFO): Simultaneous selection of multiple features with their detection parameters,
CVPR09(1263-1270).
IEEE DOI 0906
BibRef

Karlinsky, L.[Leonid], Dinerstein, M.[Michael], Levi, D.[Dan], Ullman, S.[Shimon],
Combined Model for Detecting, Localizing, Interpreting, and Recognizing Faces,
Faces08(xx-yy). 0810
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Karlinsky, L.[Leonid], Dinerstein, M.[Michael], Levi, D.[Dan], Ullman, S.[Shimon],
Unsupervised Classification and Part Localization by Consistency Amplification,
ECCV08(II: 321-335).
Springer DOI 0810
Find images that contain the unknown object. BibRef

Cour, T.[Timothee], Shi, J.B.[Jian-Bo],
Recognizing objects by piecing together the Segmentation Puzzle,
CVPR07(1-8).
IEEE DOI 0706
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Wu, T.F.[Tian-Fu], Xia, G.S.[Gui-Song], Zhu, S.C.[Song-Chun],
Compositional Boosting for Computing Hierarchical Image Structures,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Cinque, L., Sangineto, E., Tanimoto, S.,
Articulated Object Recognition: A General Framework and a Case Study,
AVSBS06(12-12).
IEEE DOI 0611
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Li, F.Y.[Fa-Yin], Ko¡secka, J.[Jana], Wechsler, H.[Harry],
Strangeness Based Feature Selection for Part Based Recognition,
BP06(22).
IEEE DOI 0609
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Kapoor, A.[Ashish], Winn, J.[John],
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection,
ECCV06(III: 302-315).
Springer DOI 0608
Part-based segmentation of objects. BibRef

Xie, L.X.[Le-Xing], Perez, P.[Patrick],
Slightly Supervised Learning of Part-Based Appearance Models,
LCV04(107).
IEEE DOI 0406
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Al-Shaher, A.A.[Abdullah A.], Hancock, E.R.[Edwin R.],
A Hierarchical Framework for Shape Recognition Using Articulated Shape Mixtures,
ICIAR04(I: 335-343).
Springer DOI 0409
BibRef
And:
Articulated Shape Mixtures for Object Recognition,
BMVC04(xx-yy).
HTML Version. 0508
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And:
A Probabilistic Framework for Articulated Shape Recognition,
AMDO04(62-75).
Springer DOI 0505

See also Arabic Character Recognition Using Structural Shape Decomposition. BibRef

Kim, G.H.[Gun-Hee], Huber, D.F.[Daniel F.], Hebert, M.[Martial],
Segmentation of Salient Regions in Outdoor Scenes Using Imagery and 3-D Data,
WACV08(1-8).
IEEE DOI 0801
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Donamukkala, R., Huber, D.F., Kapuria, A., Hebert, M.,
Automatic Class Selection and Prototyping for 3-D Object Classification,
3DIM05(64-71).
IEEE DOI 0508
BibRef
Earlier: A2, A3, A1, A4:
Parts-based 3D object classification,
CVPR04(II: 82-89).
IEEE DOI 0408
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Svensson, S.[Stina], Sanniti di Baja, G.[Gabriella],
A Tool for Decomposing 3D Discrete Objects,
CVPR01(I:850-855).
IEEE DOI 0110
3d Model decomposition. BibRef

Schnitzspan, P.[Paul], Roth, S.[Stefan], Schiele, B.[Bernt],
Automatic discovery of meaningful object parts with latent CRFs,
CVPR10(121-128).
IEEE DOI 1006
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Kruppa, H., Schiele, B.,
Hierarchical Combination of Object Models using Mutual Information,
BMVC01(Poster Session 1).
HTML Version. ETH Zurich 0110
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de Vries, G., Verbeek, P.W.,
Scale-adaptive Landmark Detection, Classification and Size Estimation in 3d Object-background Images,
ICPR00(Vol III: 1014-1017).
IEEE DOI 0009
Gradient Square Tensor, based on rods, plates and surfaces. Medical images. BibRef

Bueno, G., Nikou, C., Musse, O., Heitz, F., Armspach, J.P.,
Construction of a 3d Physically-based Multi-object Deformable Model,
ICIP00(Vol I: 268-271).
IEEE DOI 0008
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Cutzu, F.[Florin],
Computing 3D Object Parts from Similarities among Object Views,
CVPR00(II: 95-100).
IEEE DOI 0005
Segmented 3-D model BibRef

Borges, D.L., Fisher, R.B.,
Segmentation of 3D Articulated Objects by Dynamic Grouping of Discontinuities,
BMVC93(279-287).
PDF File. BibRef 9300 Edinburghrange data segmentation, articulated objects BibRef

Lee, S.H.[Sun-Ho], Hong, H.K.[Hyun-Ki], Choi, J.S.[Jong-Soo],
A Study on Assembly Part Recognition using Part-based Superquadric Model,
ICIP99(IV:78-82).
IEEE DOI BibRef 9900

Hauck, A., Lanser, S., Zierl, C.,
Hierarchical Recognition of Articulated Objects from Single Perspective Views,
CVPR97(870-876).
IEEE DOI 9704
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Forsyth, D.A., Fleck, M.M.,
Body Plans,
CVPR97(678-683).
IEEE DOI 9704
Human and animal descriptions, texture and color. BibRef

Ashbrook, A.P., Fisher, R.B.,
Constructing Models of Articulating Objects: Range Data Partitioning,
3DIM97(7 - Geometric Processing) 9702
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And: DAINo. 844. January 1997. BibRef EdinburghRegister the range data from several viewpoints after segmenting the object into the rigid parts. BibRef

Du, L., Munck-Fairwood, R.C.,
Geon Recognition Through Robust Feature Grouping,
SCIA95(715-722). BibRef 9500

Rom, H.[Hillel], and Medioni, G.[Gerard],
Part Decomposition and Description of 3D Shapes,
ARPA94(II:1505-1512). BibRef 9400
And: ICPR94(A:629-632).
IEEE DOI
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Burns, J.B.[J. Brian], Nishihara, H.K.[H. Keith], and Rosenschein, S.J.[Stanley J.],
Appropriate-Scale Local Centers: A Foundation for Parts-Based Recognition,
SCV95(317-322).
IEEE DOI BibRef 9500
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Kanehara, F., Satoh, S., Hamada, T.,
Shape Decomposition Based on Erosion Model,
PBMCV95(SESSION 5) BibRef 9500

Paulus, D.W.R.[Dietrich W. R.], Wolf, M.[Matthias],
Object-oriented volume segmentation,
CAIP93(669-673).
Springer DOI 9309
BibRef

Biederman, I.[Irving], Cooper, E.E.[Eric E.], Hummel, J.E.[John E.], Fiser, J.[Jozsef],
Geon Theory as an Account of Shape Recognition in Mind, Brain and Machine,
BMVC93(xx-yy).
PDF File. 9309
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Chen, L.H., Lin, W.C.,
Part Segmentation for Object Recognition,
ICPR92(I:272-275).
IEEE DOI BibRef 9200

Walker, N.[Nicholas],
Using neural networks to learn shape decomposition by successive prototypication,
ECCV90(610-612).
Springer DOI 9004
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Aubry, S.[Stephane], and Hayward, V.[Vincent],
Building Hierarchical Solid Models from Sensor Data,
CRA89(196-201). BibRef 8900

Pentland, A.P.[Alex P.],
Recognition by Parts,
ICCV87(612-620). BibRef 8700

Adelfeld, B.,
Automatic 3D Reconstruction from 2D geometric Part Descriptions,
CVPR83(66-72). BibRef 8300

Hebert, M., Ponce, J.,
A New Method for Segmenting 3-D Scenes into Primitives,
ICPR82(836-838). BibRef 8200

Turner, K.J.,
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Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Descriptions Based on Relational Network Structures .