Mori, G.[Greg], and
Malik, J.[Jitendra],
Recovering 3D Human Body Configurations Using Shape Contexts,
PAMI(28), No. 7, July 2006, pp. 1052-1062.
IEEE DOI
0606
BibRef
Earlier:
Estimating Human Body Configurations Using Shape Context Matching,
ECCV02(III: 666 ff.).
Springer DOI Or:
PDF File.
0205
From a single image, locate body parts, estimate joint positions, then
get 3-D pose.
See also Efficient Shape Matching Using Shape Contexts.
BibRef
Mori, G.,
Ren, X.F.[Xiao-Feng],
Efros, A.A.,
Malik, J.,
Recovering Human Body Configurations:
Combining Segmentation and Recognition,
CVPR04(II: 326-333).
IEEE DOI
0408
BibRef
Wang, Y.[Yang],
Mori, G.[Greg],
Multiple Tree Models for Occlusion and Spatial Constraints in Human
Pose Estimation,
ECCV08(III: 710-724).
Springer DOI
0810
BibRef
Earlier:
Boosted Multiple Deformable Trees for Parsing Human Poses,
HUMO07(16-27).
Springer DOI
0710
BibRef
Chen, B.[Bo],
Nguyen, N.[Nhan],
Mori, G.[Greg],
Human Pose Estimation with Rotated Geometric Blur,
WACV08(1-6).
IEEE DOI
0801
BibRef
Fathi, A.[Alireza],
Mori, G.[Greg],
Human Pose Estimation using Motion Exemplars,
ICCV07(1-8).
IEEE DOI
0710
BibRef
Ren, X.F.[Xiao-Feng],
Berg, A.C.[Alexander C.],
Malik, J.[Jitendra],
Recovering Human Body Configurations Using Pairwise Constraints between
Parts,
ICCV05(I: 824-831).
IEEE DOI
0510
BibRef
Wachs, J.P.[Juan P.],
Kölsch, M.[Mathias],
Goshorn, D.[Deborah],
Human posture recognition for intelligent vehicles,
RealTimeIP(5), No. 4, December 2010, pp. 231-244.
WWW Link.
1101
BibRef
Earlier: A3, A1, A2:
The Multi-level Learning and Classification of Multi-class Parts-Based
Representations of U.S. Marine Postures,
CIARP09(505-512).
Springer DOI
0911
BibRef
Hsieh, J.W.[Jun-Wei],
Chuang, C.H.,
Chen, S.Y.,
Chen, C.C.A.[Chih-Chi-Ang],
Fan, K.C.,
Segmentation of Human Body Parts Using Deformable Triangulation,
SMC-A(40), No. 3, May 2010, pp. 596-610.
IEEE DOI
1003
BibRef
Chen, C.C.A.[Chih-Chi-Ang],
Hsieh, J.W.[Jun-Wei],
Hsu, Y.T.[Yung-Tai],
Huang, C.Y.[Chuan-Yu],
Segmentation of Human Body Parts Using Deformable Triangulation 2,
ICPR06(I: 355-358).
IEEE DOI
0609
BibRef
Li, S.F.[Shi-Feng],
Lu, H.C.[Hu-Chuan],
Ruan, X.[Xiang],
Chen, Y.W.[Yen-Wei],
Human body segmentation based on independent component analysis with
reference at two-scale superpixel,
IET-IPR(6), No. 6, 2012, pp. 770-777.
DOI Link
1210
BibRef
Earlier:
Pose estimation and body segmentation based on hierarchical searching
tree,
ICIP11(1289-1292).
IEEE DOI
1201
BibRef
Li, S.F.[Shi-Feng],
Yao, M.[Meng],
Lu, H.C.[Hu-Chuan],
Human Body Segmentation in a Static Image with On-Line Adaboost at
Multiscale Superpixels,
IJIG(12), No. 3, July 2012, pp. 1250018.
DOI Link
1210
BibRef
Lu, H.C.[Hu-Chuan],
Shao, X.Q.[Xin-Qing],
Xiao, Y.[Yi],
Pose Estimation With Segmentation Consistency,
IP(22), No. 10, 2013, pp. 4040-4048.
IEEE DOI
1309
Human Segmentation
BibRef
Li, S.F.[Shi-Feng],
Lu, H.C.[Hu-Chuan],
Shao, X.Q.[Xing-Qing],
Human Body Segmentation via Data-Driven Graph Cut,
Cyber(44), No. 11, November 2014, pp. 2099-2108.
IEEE DOI
1411
computer vision
BibRef
Chen, M.[Ming],
Tan, X.Y.[Xiao-Yang],
Part-based pose estimation with local and non-local contextual
information,
IET-CV(8), No. 6, 2014, pp. 475-486.
DOI Link
1502
optimisation.
part-based human pose estimation.
improve the accuracies for leaf parts locations.
BibRef
Xiao, Y.,
Lu, H.,
Sun, C.,
Pose Estimation Based on Pose Cluster and Candidates Recombination,
CirSysVideo(25), No. 6, June 2015, pp. 935-943.
IEEE DOI
1506
Biological system modeling
pose clustering and body-part candidates.
BibRef
Park, S.[Seyoung],
Nie, B.X.[Bruce Xiaohan],
Zhu, S.C.[Song-Chun],
Attribute And-Or Grammar for Joint Parsing of Human Pose, Parts and
Attributes,
PAMI(40), No. 7, July 2018, pp. 1555-1569.
IEEE DOI
1806
Geometry, Glass, Grammar, Head, Magnetic heads, Pose estimation,
Predictive models, And-Or grammar, Attribute grammar,
pose estimation
BibRef
Nie, B.X.,
Wei, P.,
Zhu, S.C.,
Monocular 3D Human Pose Estimation by Predicting Depth on Joints,
ICCV17(3467-3475)
IEEE DOI
1802
image motion analysis, pose estimation, recurrent neural nets,
2D human joint locations, HHOI dataset, Human3.6M dataset,
BibRef
Jiang, Y.,
Chi, Z.,
A CNN Model for Semantic Person Part Segmentation With Capacity
Optimization,
IP(28), No. 5, May 2019, pp. 2465-2478.
IEEE DOI
1903
computational complexity, convolutional neural nets,
image segmentation, learning (artificial intelligence),
capacity optimization
BibRef
Yang, L.[Lu],
Song, Q.[Qing],
Wang, Z.H.[Zhi-Hui],
Hu, M.J.[Meng-Jie],
Liu, C.[Chun],
Hier R-CNN: Instance-Level Human Parts Detection and A New Benchmark,
IP(30), 2021, pp. 39-54.
IEEE DOI
2011
Annotations, Faces, Visualization, Proposals, Benchmark testing,
Task analysis, Human parts detection, COCO human parts,
Hier R-CNN
BibRef
Chen, Z.R.[Ze-Rui],
Huang, Y.[Yan],
Yu, H.Y.[Hong-Yuan],
Wang, L.[Liang],
Learning a Robust Part-Aware Monocular 3D Human Pose Estimator via
Neural Architecture Search,
IJCV(130), No. 1, January 2022, pp. 56-75.
Springer DOI
2201
BibRef
Chen, Z.R.[Ze-Rui],
Huang, Y.[Yan],
Yu, H.Y.[Hong-Yuan],
Xue, B.[Bin],
Han, K.[Ke],
Guo, Y.[Yiru],
Wang, L.[Liang],
Towards Part-aware Monocular 3d Human Pose Estimation:
An Architecture Search Approach,
ECCV20(III:715-732).
Springer DOI
2012
BibRef
Wangni, J.Q.[Jian-Qiao],
Lin, D.[Dahua],
Liu, J.[Ji],
Daniilidis, K.[Kostas],
Shi, J.B.[Jian-Bo],
Towards Statistically Provable Geometric 3D Human Pose Recovery,
SIIMS(14), No. 1, 2021, pp. 246-270.
DOI Link
2104
BibRef
Zhao, L.,
Xu, J.,
Gong, C.,
Yang, J.,
Zuo, W.,
Gao, X.,
Learning to Acquire the Quality of Human Pose Estimation,
CirSysVideo(31), No. 4, April 2021, pp. 1555-1568.
IEEE DOI
2104
Pose estimation, Heating systems, Computational modeling,
Task analysis, Detectors, Computer science,
end to end learning
BibRef
Zhang, J.[Jing],
Chen, Z.[Zhe],
Tao, D.C.[Da-Cheng],
Towards High Performance Human Keypoint Detection,
IJCV(129), No. 9, September 2021, pp. 2639-2662.
Springer DOI
2108
BibRef
Liu, T.[Ting],
Sun, J.J.[Jennifer J.],
Zhao, L.[Long],
Zhao, J.P.[Jia-Ping],
Yuan, L.Z.[Liang-Zhe],
Wang, Y.X.[Yu-Xiao],
Chen, L.C.[Liang-Chieh],
Schroff, F.[Florian],
Adam, H.[Hartwig],
View-Invariant, Occlusion-Robust Probabilistic Embedding for Human Pose,
IJCV(130), No. 1, January 2022, pp. 111-135.
Springer DOI
2201
BibRef
Earlier: A2, A4, A7, A8, A9, A1, Only:
View-invariant Probabilistic Embedding for Human Pose,
ECCV20(V:53-70).
Springer DOI
2011
BibRef
Wu, L.[Lele],
Yu, Z.[Zhenbo],
Liu, Y.[Yijiang],
Liu, Q.S.[Qing-Shan],
Limb Pose Aware Networks for Monocular 3D Pose Estimation,
IP(31), 2022, pp. 906-917.
IEEE DOI
2201
Pose estimation, Joints, Bones,
Trajectory, Kinematics, Transformers, Monocular 3D pose estimation,
hierarchical transformer
BibRef
Kundu, J.N.,
Seth, S.,
Jampani, V.,
Rakesh, M.,
Babu, R.V.[R. Venkatesh],
Chakraborty, A.,
Self-Supervised 3D Human Pose Estimation via Part Guided Novel Image
Synthesis,
CVPR20(6151-6161)
IEEE DOI
2008
Pose estimation, Cameras, Shape, Solid modeling, Task analysis
BibRef
Cahill-Lane, J.,
Mills, S.,
Duncan, S.,
Body Part Labelling with Minkowski Networks,
IVCNZ19(1-6)
IEEE DOI
2004
feature extraction, image classification,
image representation, learning (artificial intelligence),
Minkowski networks
BibRef
Rong, Y.,
Liu, Z.,
Li, C.,
Cao, K.,
Loy, C.C.[Chen Change],
Delving Deep Into Hybrid Annotations for 3D Human Recovery in the
Wild,
ICCV19(5339-5347)
IEEE DOI
2004
feature extraction, image annotation, image reconstruction,
image segmentation, learning (artificial intelligence),
BibRef
Zhang, S.H.[Song-Hai],
Li, R.L.[Rui-Long],
Dong, X.[Xin],
Rosin, P.[Paul],
Cai, Z.[Zixi],
Han, X.[Xi],
Yang, D.C.[Ding-Cheng],
Huang, H.Z.[Hao-Zhi],
Hu, S.M.[Shi-Min],
Pose2Seg: Detection Free Human Instance Segmentation,
CVPR19(889-898).
IEEE DOI
2002
BibRef
Wang, D.[Dan],
Sheng, Y.[Yun],
Zhang, G.[Gui_Xu],
A New Female Body Segmentation and Feature Localisation Method for
Image-Based Anthropometry,
MMMod19(I:567-577).
Springer DOI
1901
BibRef
Fang, H.,
Lu, G.,
Fang, X.,
Xie, J.,
Tai, Y.,
Lu, C.,
Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided
Knowledge Transfer,
CVPR18(70-78)
IEEE DOI
1812
Transforms, Pattern recognition,
Knowledge transfer, Image segmentation
BibRef
Yang, Z.,
Luo, J.,
Personalized pose estimation for body language understanding,
ICIP17(126-130)
IEEE DOI
1803
Heating systems, Pose estimation, Reliability, Task analysis, Videos,
Visualization, Wrist, Body Parts Tracking,
Pose Estimation
BibRef
Handrich, S.,
Al-Hamadi, A.,
Localizing body joints from single depth images using geodetic
distances and random tree walk,
ICIP17(146-150)
IEEE DOI
1803
Pose estimation, Regression tree analysis, Skeleton,
Training,
Random Tree Walk
BibRef
Handrich, S.,
Al-Hamadi, A.,
Lilienblum, E.,
Liu, Z.,
Human bodypart classification using geodesic descriptors and random
forests,
MVA17(318-321)
DOI Link
1708
Cameras, Feature extraction, Solid modeling,
Training data, Vegetation
BibRef
Wei, K.Q.[Kai-Qiang],
Zhao, X.[Xu],
Multiple-Branches Faster RCNN for Human Parts Detection and Pose
Estimation,
BEST16(III: 453-462).
Springer DOI
1704
BibRef
Bulat, A.[Adrian],
Tzimiropoulos, G.[Georgios],
Human Pose Estimation via Convolutional Part Heatmap Regression,
ECCV16(VII: 717-732).
Springer DOI
1611
See also Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources.
BibRef
Mao, W.T.[Wen-Tao],
Wang, Q.A.[Qi-Ang],
Wang, X.T.[Xiao-Tao],
Guo, P.[Ping],
Wang, S.D.[Shan-Dong],
Shao, G.Q.[Guang-Qi],
Lee, K.[Kyoobin],
Park, P.K.J.[Paul K.J.],
Real-time human body parts localization from dynamic vision sensor,
ICIP15(4783-4787)
IEEE DOI
1512
BibRef
Chen, X.J.[Xian-Jie],
Mottaghi, R.[Roozbeh],
Liu, X.B.[Xiao-Bai],
Fidler, S.[Sanja],
Urtasun, R.[Raquel],
Yuille, A.L.[Alan L.],
Detect What You Can: Detecting and Representing Objects Using
Holistic Models and Body Parts,
CVPR14(1979-1986)
IEEE DOI
1409
Humans, animals
BibRef
Cherian, A.[Anoop],
Mairal, J.[Julien],
Alahari, K.[Karteek],
Schmid, C.[Cordelia],
Mixing Body-Part Sequences for Human Pose Estimation,
CVPR14(2361-2368)
IEEE DOI
1409
Human pose estimation
BibRef
Kiefel, M.[Martin],
Gehler, P.V.[Peter Vincent],
Human Pose Estimation with Fields of Parts,
ECCV14(V: 331-346).
Springer DOI
1408
BibRef
Ladicky, L.[Lubor],
Torr, P.H.S.[Philip H.S.],
Zisserman, A.[Andrew],
Human Pose Estimation Using a Joint Pixel-wise and Part-wise
Formulation,
CVPR13(3578-3585)
IEEE DOI
1309
Conditional Random Fields; Pictorial Structures; Pose Estimation
BibRef
Puertas, E.,
Bautista, M.Á.[Miguel Ángel],
Sanchez, D.,
Escalera, S.[Sergio],
Pujol, O.[Oriol],
Learning to Segment Humans by Stacking Their Body Parts,
ChaLearn14(685-697).
Springer DOI
1504
BibRef
Wang, H.[Huayan],
Koller, D.[Daphne],
Multi-level inference by relaxed dual decomposition for human pose
segmentation,
CVPR11(2433-2440).
IEEE DOI
1106
BibRef
Su, Y.C.[Yan-Chao],
Ai, H.Z.[Hai-Zhou],
Yamashita, T.[Takayoshi],
Lao, S.H.[Shi-Hong],
Human Pose Estimation Using Exemplars and Part Based Refinement,
ACCV10(II: 174-185).
Springer DOI
1011
See also Multi-View Face Alignment Using 3D Shape Model for View Estimation.
BibRef
Singh, V.K.[Vivek Kumar],
Nevatia, R.[Ram],
Huang, C.[Chang],
Efficient Inference with Multiple Heterogeneous Part Detectors for
Human Pose Estimation,
ECCV10(III: 314-327).
Springer DOI
1009
See also Action recognition in cluttered dynamic scenes using Pose-Specific Part Models.
BibRef
Jeanne, V.[Vincent],
Unay, D.[Devrim],
Jacquet, V.[Vincent],
Automatic detection of body parts in x-ray images,
MMBIA09(25-30).
IEEE DOI
0906
BibRef
Walther, T.[Thomas],
Würtz, R.P.[Rolf P.],
Learning Generic Human Body Models,
AMDO10(98-107).
Springer DOI
1007
BibRef
Earlier:
Learning to Look at Humans: What Are the Parts of a Moving Body?,
AMDO08(xx-yy).
Springer DOI
0807
BibRef
Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Human Body Shape .