11.10 Representation of Parts, Part-Based Models

Chapter Contents (Back)
Part Segmentation. Descriptions, Parts. Representation by Parts. Representation, Parts -- 3D. Part-Based.

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Earlier: BMVC96(Features, Segmentation). 9608
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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.,
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And:
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Pilu, M., Fisher, R.B.,
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Earlier: DAINo. 805, May 1996. Perceptual Grouping. BibRef EdinburghGrouping applied to edge images using models of the parts.
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Multi-part object detection; Segmented contour map; Grouping constraints; Global shape grouping criteria BibRef

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Learning a hierarchical compositional representation of multiple object classes,
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Earlier:
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IEEE DOI 0806
Spatial arrangement of similar objects. BibRef

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Firearms identification through partonomy,
SPIE(Newsroom), August 11, 2015
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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],
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IEICE(E98-D), No. 11, November 2015, pp. 1950-1957.
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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.[Zhitao], 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.
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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.[Boxiao], 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
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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
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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


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
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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.[Yilin], 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
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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.[Yiwen], 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, Pattern recognition 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.], Rodolŕ, 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
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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).
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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.[Luyan], 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], Ĺström, 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
BibRef

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
BibRef

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
BibRef

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
BibRef

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
BibRef

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
BibRef

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
BibRef

Li, F.Y.[Fa-Yin], Koˇsecka, J.[Jana], Wechsler, H.[Harry],
Strangeness Based Feature Selection for Part Based Recognition,
BP06(22).
IEEE DOI 0609
BibRef

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
BibRef

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
BibRef
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
BibRef

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
BibRef

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
BibRef

Kruppa, H., Schiele, B.,
Hierarchical Combination of Object Models using Mutual Information,
BMVC01(Poster Session 1).
HTML Version. ETH Zurich 0110
BibRef

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
BibRef

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
See also Hierarchical Decomposition and Axial Shape Description. BibRef

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
And: ARPA94(II:1281-1286). Recognition by Parts. Teleos Research. Local centers circles that fit the object. BibRef

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
BibRef

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.,
Computer Perception of Curved Objects Using a Television Camera,
Ph.D.Thesis, Univ. of Edinburgh, 1974. BibRef 7400

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


Last update:Mar 16, 2024 at 20:36:19