22.4.1.8 Articulated Human Pose Desicriptions

Herbison-Evans, D., Richardson, D.S.,
Control of round-off propagation in articulating the human figure,
CGIP(17), No. 4, December 1981, pp. 386-393.
Elsevier DOI 0501
BibRef

Ling, H.B.[Hai-Bin], Jacobs, D.W.[David W.],
Shape Classification Using the Inner-Distance,
PAMI(29), No. 2, February 2007, pp. 286-299.
IEEE DOI 0701
BibRef
Earlier:
Using the Inner-Distance for Classification of Articulated Shapes,
CVPR05(II: 719-726).
IEEE DOI 0507
Distances between landmark points. Inner-distance is shortest path. Articulation independent. BibRef

Bronstein, A.M.[Alexander M.], Bronstein, M.M.[Michael M.], Bruckstein, A.M.[Alfred M.], Kimmel, R.[Ron],
Analysis of Two-Dimensional Non-Rigid Shapes,
IJCV(78), No. 1, June 2008, pp. 67-88.
Springer DOI 0803
BibRef
Earlier:
Matching Two-Dimensional Articulated Shapes Using Generalized Multidimensional Scaling,
AMDO06(48-57).
Springer DOI 0607
BibRef

Ross, D.A.[David A.], Tarlow, D.[Daniel], Zemel, R.S.[Richard S.],
Learning Articulated Structure and Motion,
IJCV(88), No. 2, June 2010, pp. xx-yy.
Springer DOI 1003
BibRef
Earlier:
Unsupervised Learning of Skeletons from Motion,
ECCV08(III: 560-573).
Springer DOI 0810
BibRef

Li, Y.J.[Yu-Jia], Tarlow, D.[Daniel], Zemel, R.S.[Richard S.],
Exploring Compositional High Order Pattern Potentials for Structured Output Learning,
CVPR13(49-56)
IEEE DOI 1309
BibRef

Meeds, E.W.[Edward W.], Ross, D.A.[David A.], Zemel, R.S.[Richard S.], Roweis, S.T.[Sam T.],
Learning stick-figure models using nonparametric Bayesian priors over trees,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Yang, Y.[Yi], Ramanan, D.[Deva],
Articulated Human Detection with Flexible Mixtures of Parts,
PAMI(35), No. 12, 2013, pp. 2878-2890.
IEEE DOI 1311
BibRef
Earlier:
Articulated pose estimation with flexible mixtures-of-parts,
CVPR11(1385-1392).
IEEE DOI 1106
Computational modeling BibRef

Yang, S.F.[Song-Fan], Ramanan, D.[Deva],
Multi-scale Recognition with DAG-CNNs,
ICCV15(1215-1223)
IEEE DOI 1602
Benchmark testing BibRef

Ding, M.[Meng], Fan, G.L.[Guo-Liang],
Articulated and Generalized Gaussian Kernel Correlation for Human Pose Estimation,
IP(25), No. 2, February 2016, pp. 776-789.
IEEE DOI 1601
BibRef
Earlier:
Articulated Gaussian kernel correlation for human pose estimation,
PBVS15(57-64)
IEEE DOI 1510
Computational modeling. Correlation BibRef

Ukita, N.[Norimichi],
Part-Segment Features with Optimized Shape Priors for Articulated Pose Estimation,
IEICE(E99-D), No. 1, January 2016, pp. 248-256.
WWW Link. 1601
BibRef
Earlier:
Part-segment features for articulated pose estimation,
MVA15(114-117)
IEEE DOI 1507
BibRef
And:
Articulated pose estimation with parts connectivity using discriminative local oriented contours,
CVPR12(3154-3161).
IEEE DOI 1208
Estimation BibRef

Kawana, Y.[Yuki], Ukita, N.[Norimichi],
Occluded Appearance Modeling with Sample Weighting for Human Pose Estimation,
IEICE(E100-D), No. 10, October 2017, pp. 2627-2634.
WWW Link. 1710
BibRef

Ukita, N.[Norimichi], Uematsu, Y.[Yusuke],
Semi- and weakly-supervised human pose estimation,
CVIU(170), 2018, pp. 67-78.
Elsevier DOI 1806
Human pose estimation, Semi-supervised learning, Weakly-supervised learning, Pose clustering BibRef

Kawana, Y.[Yuki], Ukita, N.[Norimichi], Hagita, N.[Norihiro],
Occlusion-free appearance modeling of body parts for human pose estimation,
MVA15(321-324)
IEEE DOI 1507
Biological system modeling BibRef

Marinoiu, E.[Elisabeta], Papava, D.[Dragos], Sminchisescu, C.[Cristian],
Pictorial Human Spaces: A Computational Study on the Human Perception of 3D Articulated Poses,
IJCV(119), No. 2, September 2016, pp. 194-215.
Springer DOI 1608
BibRef
Earlier:
Pictorial Human Spaces: How Well Do Humans Perceive a 3D Articulated Pose?,
ICCV13(1289-1296)
IEEE DOI 1403
BibRef

Han, F.[Fei], Reily, B.[Brian], Hoff, W.[William], Zhang, H.[Hao],
Space-time representation of people based on 3D skeletal data: A review,
CVIU(158), No. 1, 2017, pp. 85-105.
Elsevier DOI 1704
Human representation BibRef

Fu, L.R.[Lian-Rui], Zhang, J.[Junge], Huang, K.Q.[Kai-Qi],
ORGM: Occlusion Relational Graphical Model for Human Pose Estimation,
IP(26), No. 2, February 2017, pp. 927-941.
IEEE DOI 1702
BibRef
Earlier:
Beyond Tree Structure Models: A New Occlusion Aware Graphical Model for Human Pose Estimation,
ICCV15(1976-1984)
IEEE DOI 1602
BibRef
Earlier:
Context aware model for articulated human pose estimation,
ICIP15(991-995)
IEEE DOI 1512
Brain modeling. Articulation BibRef

Nishi, K., Miura, J.,
Generation of human depth images with body part labels for complex human pose recognition,
PR(71), No. 1, 2017, pp. 402-413.
Elsevier DOI 1707
Human, depth, image BibRef

Wan, J.[Jun], Escalera, S.[Sergio], Perales, F.J.[Francisco J.], Kittler, J.V.[Josef V.],
Articulated motion and deformable objects,
PR(79), 2018, pp. 55-64.
Elsevier DOI 1804
Articulated motion and deformable Objects, Pose estimation, Action recognition, Gesture recognition, Face analysis BibRef

Dogan, E.[Emre], Eren, G.[Gonen], Wolf, C.[Christian], Lombardi, E.[Eric], Baskurt, A.[Atilla],
Multi-view pose estimation with mixtures of parts and adaptive viewpoint selection,
IET-CV(12), No. 4, June 2018, pp. 403-411.
DOI Link 1805
BibRef
Earlier:
Multi-view Pose Estimation with Flexible Mixtures-of-Parts,
ACIVS17(180-190).
Springer DOI 1712
BibRef

Huang, M.Y.[Mei-Yu], Xiang, X.S.[Xue-Shuang], Chen, Y.Q.[Yi-Qiang], Fan, D.[Da],
Weighted Large Margin Nearest Center Distance-Based Human Depth Recovery With Limited Bandwidth Consumption,
IP(27), No. 12, December 2018, pp. 5728-5743.
IEEE DOI 1810
autoregressive moving average processes, image sampling, pose estimation, state-of-the-art depth recovery methods, distance learning BibRef

Mehrizi, R., Peng, X., Metaxas, D.N., Xu, X., Zhang, S., Li, K.,
Predicting 3-D Lower Back Joint Load in Lifting: A Deep Pose Estimation Approach,
HMS(49), No. 1, February 2019, pp. 85-94.
IEEE DOI 1901
Task analysis, Videos, Biomechanics, Neural networks, Back, Sensors, Kinetic theory, Deep neural network, lifting, lower back loading, occupational biomechanics BibRef

Mehrizi, R., Peng, X., Tang, Z., Xu, X., Metaxas, D.N., Li, K.,
Toward Marker-Free 3D Pose Estimation in Lifting: A Deep Multi-View Solution,
FG18(485-491)
IEEE DOI 1806
Biomechanics, Heating systems, Pose estimation, Shape, Task analysis, markerless 3D human pose estimation BibRef

Yang, B., Ma, A.J., Yuen, P.C.,
Body Parts Synthesis for Cross-Quality Pose Estimation,
CirSysVideo(29), No. 2, February 2019, pp. 461-474.
IEEE DOI 1902
Pose estimation, Image quality, Training, Testing, Dictionaries, Adaptation models, Skeleton, Pose estimation, domain adaptation BibRef

Yu, L.Y.[Ling-Yun], Yu, J.[Jun], Ling, Q.A.[Qi-Ang],
BLTRCNN-Based 3-D Articulatory Movement Prediction: Learning Articulatory Synchronicity From Both Text and Audio Inputs,
MultMed(21), No. 7, July 2019, pp. 1621-1632.
IEEE DOI 1906
BibRef
Earlier:
Deep Neural Network Based 3D Articulatory Movement Prediction Using Both Text and Audio Inputs,
MMMod19(I:68-79).
Springer DOI 1901
Acoustics, Linguistics, Feature extraction, Animation, articulatory movement prediction BibRef

Liang, G.Q.[Guo-Qiang], Lan, X.G.[Xu-Guang], Wang, J.[Jiang], Wang, J.J.[Jian-Ji], Zheng, N.N.[Nan-Ning],
A Limb-Based Graphical Model for Human Pose Estimation,
SMCS(48), No. 7, July 2018, pp. 1080-1092.
IEEE DOI 1806
BibRef
Earlier: A1, A2, A3, A5, Only:
Human pose estimation based on human limbs,
ICPR16(913-918)
IEEE DOI 1705
Elbow, Feature extraction, Graphical models, Joining processes, Pose estimation, Shape, Visual systems, limbs detection. Adaptation models, Heating systems, ConvNet, Graphical model. BibRef

Chen, T.L.[Tian-Lang], Fang, C.[Chen], Shen, X.H.[Xiao-Hui], Zhu, Y.H.[Yi-Heng], Chen, Z.[Zhili], Luo, J.B.[Jie-Bo],
Anatomy-Aware 3D Human Pose Estimation With Bone-Based Pose Decomposition,
CirSysVideo(32), No. 1, January 2022, pp. 198-209.
IEEE DOI 2201
Bones, Videos, Joints, Task analysis, Pose estimation, 3D pose, bone, length, long skip connections BibRef

Liu, L.[Liu], Xue, H.[Han], Xu, W.Q.[Wen-Qiang], Fu, H.Y.[Hao-Yuan], Lu, C.[Cewu],
Toward Real-World Category-Level Articulation Pose Estimation,
IP(31), 2022, pp. 1072-1083.
IEEE DOI 2201
Joints, Kinematics, Pose estimation, Solid modeling, Task analysis, Annotations, articulation parsing BibRef

You, Y.[Yang], Shi, R.X.[Ruo-Xi], Wang, W.M.[Wei-Ming], Lu, C.[Cewu],
CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wild,
CVPR22(6856-6865)
IEEE DOI 2210
Training, Pose estimation, Sociology, Training data, Predictive models, Prediction algorithms, grouping and shape analysis BibRef

Li, J.F.[Jie-Feng], Bian, S.Y.[Si-Yuan], Liu, Q.[Qi], Tang, J.S.[Jia-Sheng], Wang, F.[Fan], Lu, C.[Cewu],
NIKI: Neural Inverse Kinematics with Invertible Neural Networks for 3D Human Pose and Shape Estimation,
CVPR23(12933-12942)
IEEE DOI 2309
BibRef

Li, J.F.[Jie-Feng], Xu, C.[Chao], Chen, Z.C.[Zhi-Cun], Bian, S.Y.[Si-Yuan], Yang, L.X.[Li-Xin], Lu, C.[Cewu],
HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation,
CVPR21(3382-3392)
IEEE DOI 2111
Solid modeling, Visualization, Shape, Biological system modeling, Estimation, Kinematics BibRef

Xue, Y.[Youze], Chen, J.S.[Jian-Sheng], Gu, X.M.[Xiang-Ming], Ma, H.M.[Hui-Min], Ma, H.B.[Hong-Bing],
Boosting Monocular 3D Human Pose Estimation With Part Aware Attention,
IP(31), 2022, pp. 4278-4291.
IEEE DOI 2207
Skeleton, Dictionaries, Correlation, Pose estimation, Transformers, Convolution, 3D human pose estimation, part aware attention, dictionary attention BibRef

Zhang, Z.W.[Zi-Wei], Su, C.[Chi], Zheng, L.[Liang], Xie, X.D.[Xiao-Dong], Li, Y.[Yuan],
On the Correlation Among Edge, Pose and Parsing,
PAMI(44), No. 11, November 2022, pp. 8492-8507.
IEEE DOI 2210
Task analysis, Image edge detection, Correlation, Pose estimation, Feature extraction, Semantics, Fuses, Correlation machine, human body edge detection BibRef

Fernandes, F.[Francisco], Roupa, I.[Ivo], Gonçalves, S.B.[Sérgio B.], Moita, G.[Gonçalo], da Silva, M.T.[Miguel Tavares], Pereira, J.[João], Jorge, J.[Joaquim], Neptune, R.R.[Richard R.], Lopes, D.S.[Daniel Simões],
Sticks and STONES may build my bones: Deep learning reconstruction of limb rotations in stick figures,
PRL(165), 2023, pp. 138-145.
Elsevier DOI 2301
Stick figure, Pose estimation, Longitudinal rotations, Machine learning, Neural networks BibRef

Nie, Q.[Qiang], Liu, Z.W.[Zi-Wei], Liu, Y.H.[Yun-Hui],
Lifting 2D Human Pose to 3D with Domain Adapted 3D Body Concept,
IJCV(131), No. 5, May 2023, pp. 1250-1268.
Springer DOI 2305
BibRef

Zhou, H.Y.[Hua-Yi], Jiang, F.[Fei], Si, J.X.[Jia-Xin], Ding, Y.[Yue], Lu, H.T.[Hong-Tao],
BPJDet: Extended Object Representation for Generic Body-Part Joint Detection,
PAMI(46), No. 6, June 2024, pp. 4314-4330.
IEEE DOI 2405
Detectors, Task analysis, Magnetic heads, Face recognition, Pedestrians, Training, Quadrupedal robots, Body-part association, object representation BibRef

Yan, R.[Ruoke], Yin, Q.[Qian], Zhang, X.F.[Xin-Feng], Zhang, Q.[Qi], Zhang, G.[Gai], Ma, S.W.[Si-Wei],
Pose-Driven Compression for Dynamic 3D Human via Human Prior Models,
PAMI(46), No. 8, August 2024, pp. 5820-5834.
IEEE DOI 2407
Point cloud compression, Bit rate, Image coding, Dynamics, Solid modeling, Data models, Dynamic 3D human compression, pose-driven representation BibRef

Shan, W.K.[Wen-Kang], Liu, Z.H.[Zhen-Hua], Zhang, X.F.[Xin-Feng], Wang, Z.[Zhao], Han, K.[Kai], Wang, S.S.[Shan-She], Ma, S.W.[Si-Wei], Gao, W.[Wen],
Diffusion-Based 3D Human Pose Estimation with Multi-Hypothesis Aggregation,
ICCV23(14715-14725)
IEEE DOI Code:
WWW Link. 2401
BibRef

Du, S.[Songlin], Zhang, Z.W.[Zhi-Wen], Ikenaga, T.[Takeshi],
AnatPose: Bidirectionally learning anatomy-aware heatmaps for human pose estimation,
PR(155), 2024, pp. 110654.
Elsevier DOI 2408
Human pose estimation, Human body structure modeling, Anatomical features, Bidirectional recurrent neural networks, Heatmap regression BibRef

Liu, H.[Hai], Liu, T.T.[Ting-Ting], Chen, Y.[Yu], Zhang, Z.L.[Zhao-Li], Li, Y.F.[You-Fu],
EHPE: Skeleton Cues-Based Gaussian Coordinate Encoding for Efficient Human Pose Estimation,
MultMed(26), 2024, pp. 8464-8475.
IEEE DOI 2408
Heating systems, Encoding, Biological system modeling, Task analysis, Pose estimation, Feature extraction, Skeleton, skeleton direction BibRef

Aggarwal, A.[Ayush], Stolkin, R.[Rustam], Marturi, N.[Naresh],
Local Region-to-Region Mapping-based Approach to Classify Articulated Objects,
CRV23(177-183)
IEEE DOI 2406
Point cloud compression, Pose estimation, Benchmark testing, Reliability engineering, Data models, Object recognition, Articu-lated Classification BibRef

Sun, P.Z.[Peng-Zhan], Gu, K.[Kerui], Wang, Y.S.[Yun-Song], Yang, L.L.[Lin-Lin], Yao, A.[Angela],
Rethinking Visibility in Human Pose Estimation: Occluded Pose Reasoning via Transformers,
WACV24(5891-5900)
IEEE DOI 2404
Visualization, Correlation, Pose estimation, Transformers, Cognition, Context modeling, Algorithms, Biometrics, face, gesture, body pose, Image recognition and understanding BibRef

Heppert, N.[Nick], Irshad, M.Z.[Muhammad Zubair], Zakharov, S.[Sergey], Liu, K.[Katherine], Ambrus, R.A.[Rares Andrei], Bohg, J.[Jeannette], Valada, A.[Abhinav], Kollar, T.[Thomas],
CARTO: Category and Joint Agnostic Reconstruction of ARTiculated Objects,
CVPR23(21201-21210)
IEEE DOI 2309
BibRef

Vo, K.[Khoa], Pham, T.T.[Trong-Thang], Yamazaki, K.[Kashu], Tran, M.[Minh], Le, N.[Ngan],
DNA: Deformable Neural Articulations Network for Template-free Dynamic 3D Human Reconstruction from Monocular RGB-D Video,
Precognition23(3676-3685)
IEEE DOI 2309
BibRef

Yao, C.H.[Chun-Han], Hung, W.C.[Wei-Chih], Li, Y.Z.[Yuan-Zhen], Rubinstein, M.[Michael], Yang, M.H.[Ming-Hsuan], Jampani, V.[Varun],
Hi-LASSIE: High-Fidelity Articulated Shape and Skeleton Discovery from Sparse Image Ensemble,
CVPR23(4853-4862)
IEEE DOI 2309
BibRef

Wan, D.[Duo], Xiao, S.[Shanzhu],
A Fast Heterogeneous Image Registration Method Based on the Human Skeleton Points,
ICIVC22(329-334)
IEEE DOI 2301
Image registration, Pose estimation, Feature extraction, Cameras, Skeleton, Image sequences, Security, visible-infrared image, multi-person pose estimation BibRef

Song, B.[Bo], Ji, C.J.[Chang-Jiang], Fan, S.[Shuo],
Exploiting Static and Dynamic Human Joint Relations for 3D Pose Estimation via Cascade Transformers,
ICPR22(4522-4528)
IEEE DOI 2212
Computational modeling, Pose estimation, joint relations BibRef

Su, S.Y.[Shih-Yang], Bagautdinov, T.[Timur], Rhodin, H.[Helge],
DANBO: Disentangled Articulated Neural Body Representations via Graph Neural Networks,
ECCV22(II:107-124).
Springer DOI 2211
BibRef

Wang, S.F.[Shao-Fei], Schwarz, K.[Katja], Geiger, A.[Andreas], Tang, S.[Siyu],
ARAH: Animatable Volume Rendering of Articulated Human SDFs,
ECCV22(XXXII:1-19).
Springer DOI 2211
BibRef

Noguchi, A.[Atsuhiro], Sun, X.[Xiao], Lin, S.[Stephen], Harada, T.[Tatsuya],
Unsupervised Learning of Efficient Geometry-Aware Neural Articulated Representations,
ECCV22(XVII:597-614).
Springer DOI 2211
BibRef

Noguchi, A.[Atsuhiro], Iqbal, U.[Umar], Tremblay, J.[Jonathan], Harada, T.[Tatsuya], Gallo, O.[Orazio],
Watch It Move: Unsupervised Discovery of 3D Joints for Re-Posing of Articulated Objects,
CVPR22(3667-3677)
IEEE DOI 2210
Photography, Solid modeling, Tracking, Virtual reality, Animation, Rendering (computer graphics), Motion and tracking BibRef

Mihajlovic, M.[Marko], Saito, S.[Shunsuke], Bansal, A.[Aayush], Zollhoefer, M.[Michael], Tang, S.[Siyu],
COAP: Compositional Articulated Occupancy of People,
CVPR22(13191-13200)
IEEE DOI 2210
Geometry, Deformable models, Solid modeling, Shape, Biological system modeling, Pose estimation, Pose estimation and tracking BibRef

Liu, L.[Liu], Xu, W.Q.[Wen-Qiang], Fu, H.Y.[Hao-Yuan], Qian, S.[Sucheng], Yu, Q.[Qiaojun], Han, Y.[Yang], Lu, C.[Cewu],
AKB-48: A Real-World Articulated Object Knowledge Base,
CVPR22(14789-14798)
IEEE DOI 2210
Solid modeling, Visualization, Pipelines, Knowledge based systems, Semantics, Pose estimation, Robot vision, Datasets and evaluation BibRef

Wei, F.[Fangyin], Chabra, R.[Rohan], Ma, L.[Lingni], Lassner, C.[Christoph], Zollhoefer, M.[Michael], Rusinkiewicz, S.[Szymon], Sweeney, C.[Chris], Newcombe, R.[Richard], Slavcheva, M.[Mira],
Self-supervised Neural Articulated Shape and Appearance Models,
CVPR22(15795-15805)
IEEE DOI 2210
Geometry, Image sensors, Solid modeling, Shape, Semantics, 3D from multi-view and sensors, Image and video synthesis and generation BibRef

Xu, Z.[Zhan], Fisher, M.[Matthew], Zhou, Y.[Yang], Aneja, D.[Deepali], Dudhat, R.[Rushikesh], Yi, L.[Li], Kalogerakis, E.[Evangelos],
APES: Articulated Part Extraction from Sprite Sheets,
CVPR22(11625-11634)
IEEE DOI 2210
Torso, Codes, Animation, Pattern recognition, Sprites (computer), Segmentation, grouping and shape analysis BibRef

Qian, S.Y.[Sheng-Yi], Jin, L.[Linyi], Rockwell, C.[Chris], Chen, S.[Siyi], Fouhey, D.F.[David F.],
Understanding 3D Object Articulation in Internet Videos,
CVPR22(1589-1599)
IEEE DOI 2210
Computers, Shape, Surveillance, Internet, Pattern recognition, 3D from single images, Scene analysis and understanding BibRef

Mu, J.T.[Ji-Teng], Qiu, W.C.[Wei-Chao], Kortylewski, A.[Adam], Yuille, A.L.[Alan L.], Vasconcelos, N.M.[Nuno M.], Wang, X.L.[Xiao-Long],
A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation,
ICCV21(12981-12991)
IEEE DOI 2203
Point cloud compression, Adaptation models, Codes, Shape, Inference algorithms, Representation learning BibRef

Kim, H.[Hyomin], Kim, J.[Jungeon], Kam, J.W.[Jae-Won], Park, J.[Jaesik], Lee, S.Y.[Seung-Yong],
Deep Virtual Markers for Articulated 3D Shapes,
ICCV21(11595-11605)
IEEE DOI 2203
Training, Point cloud compression, Location awareness, Solid modeling, Shape, Surface texture, Gestures and body pose, Vision applications and systems BibRef

Sahbi, H.[Hichem],
Lightweight Connectivity In Graph Convolutional Networks for Skeleton-Based Recognition,
ICIP21(2329-2333)
IEEE DOI 2201
Deep learning, Image recognition, Network topology, Convolution, Redundancy, Graph convolutional networks, skeleton-based recognition BibRef

Panda, A.[Aditya], Mukherjee, D.P.[Dipti Prasad],
Monocular 3D Human Pose Estimation by Multiple Hypothesis Prediction and Joint Angle Supervision,
ICIP21(3243-3247)
IEEE DOI 2201
Art, Inverse problems, Image processing, Pose estimation, Benchmark testing, 3D Human Pose, Pose Estimation BibRef

Müller, L.[Lea], Osman, A.A.A.[Ahmed A. A.], Tang, S.[Siyu], Huang, C.H.P.[Chun-Hao P.], Black, M.J.[Michael J.],
On Self-Contact and Human Pose,
CVPR21(9985-9994)
IEEE DOI 2111
Training, Legged locomotion, Shape, Pose estimation, Optimization methods, Training data BibRef

Schmidtke, L.[Luca], Vlontzos, A.[Athanasios], Ellershaw, S.[Simon], Lukens, A.[Anna], Arichi, T.[Tomoki], Kainz, B.[Bernhard],
Unsupervised Human Pose Estimation through Transforming Shape Templates,
CVPR21(2484-2494)
IEEE DOI 2111
Pediatrics, Shape, Tracking, Surveillance, Pose estimation BibRef

Li, C.X.[Chen-Xi], Cohen, F.[Fernand],
3D Articulated Body Model Using Anthropometric Control Points and an Articulation Video,
ISVC20(I:554-565).
Springer DOI 2103
BibRef

Cao, X.[Xin], Zhao, X.[Xu],
Anatomy and Geometry Constrained One-stage Framework for 3d Human Pose Estimation,
ACCV20(I:227-243).
Springer DOI 2103
BibRef

Osman, A.A.A.[Ahmed A. A.], Bolkart, T.[Timo], Black, M.J.[Michael J.],
STAR: Sparse Trained Articulated Human Body Regressor,
ECCV20(VI:598-613).
Springer DOI 2011
BibRef

He, Y.H.[Yi-Hui], Yan, R.[Rui], Fragkiadaki, K.[Katerina], Yu, S.I.[Shoou-I],
Epipolar Transformers,
CVPR20(7776-7785)
IEEE DOI 2008
Joints. Feature extraction, Detectors, Pose estimation, Fuses, Cameras BibRef

Kulkarni, N., Gupta, A., Fouhey, D.F., Tulsiani, S.,
Articulation-Aware Canonical Surface Mapping,
CVPR20(449-458)
IEEE DOI 2008
Shape, Task analysis, Cameras, Solid modeling, Head BibRef

Weng, Y.J.[Yi-Jia], Wang, H.[He], Zhou, Q.[Qiang], Qin, Y.Z.[Yu-Zhe], Duan, Y.Q.[Yue-Qi], Fan, Q.N.[Qing-Nan], Chen, B.Q.[Bao-Quan], Su, H.[Hao], Guibas, L.J.[Leonidas J.],
CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Clouds,
ICCV21(13189-13198)
IEEE DOI 2203
Point cloud compression, Pipelines, Benchmark testing, Motion and tracking, Detection and localization in 2D and 3D, grouping and shape BibRef

Li, X.L.[Xiao-Long], Wang, H.[He], Yi, L.[Li], Guibas, L.J.[Leonidas J.], Abbott, A.L.[A. Lynn], Song, S.[Shuran],
Category-Level Articulated Object Pose Estimation,
CVPR20(3703-3712)
IEEE DOI 2008
Joints, Pose estimation, Kinematics, Solid modeling, Cameras, Task analysis BibRef

Weinzaepfel, P.[Philippe], Brégier, R.[Romain], Combaluzier, H.[Hadrien], Leroy, V.[Vincent], Rogez, G.[Grégory],
DOPE: Distillation of Part Experts for Whole-body 3d Pose Estimation in the Wild,
ECCV20(XXVI:380-397).
Springer DOI 2011
BibRef

Makris, A., Argyros, A.,
Robust 3D Human Pose Estimation Guided by Filtered Subsets of Body Keypoints,
MVA19(1-6)
DOI Link 1806
gradient methods, neural nets, object tracking, optimisation, pose estimation, stereo image processing, User experience BibRef

Pfeiffer, K.[Kilian], Hermans, A.[Alexander], Sárándi, I.[István], Weber, M.[Mark], Leibe, B.[Bastian],
Visual Person Understanding Through Multi-task and Multi-dataset Learning,
GCPR19(551-566).
Springer DOI 1911
Learning a single model for person re-identification, attribute classification, body part segmentation, and pose estimation. BibRef

Vats, K.[Kanav], Neher, H.[Helmut], Wong, A.[Alexander], Clausi, D.A.[David A.], Zelek, J.[John],
KPTransfer: Improved Performance and Faster Convergence from Keypoint Subset-Wise Domain Transfer in Human Pose Estimation,
ICIAR19(II:220-231).
Springer DOI 1909
BibRef

Li, X.J.[Xiao-Jie], Yang, L.[Lu], Song, Q.[Qing], Zhou, F.Q.[Fu-Qiang],
Detector-in-Detector: Multi-level Analysis for Human-Parts,
ACCV18(II:228-240).
Springer DOI 1906
BibRef

Sagawa, R.[Ryusuke], Ayusawa, K.[Ko], Yoshiyasu, Y.[Yusuke], Murai, A.[Akihiko],
Predicting Muscle Activity and Joint Angle from Skin Shape,
3D-Wild18(I:488-502).
Springer DOI 1905
BibRef

Ning, G.H.[Guang-Han], Liu, P.[Ping], Fan, X.C.[Xiao-Chuan], Zhang, C.[Chi],
A Top-Down Approach to Articulated Human Pose Estimation and Tracking,
PoseTrack18(II:227-234).
Springer DOI 1905
BibRef

Carissimi, N.[Nicolò], Rota, P.[Paolo], Beyan, C.[Cigdem], Murino, V.[Vittorio],
Filling the Gaps: Predicting Missing Joints of Human Poses Using Denoising Autoencoders,
HBU18(II:364-379).
Springer DOI 1905
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Yao, S.H., Thomas, D., Sugimoto, A., Lai, S., Kyushu, R.T.,
SegmentedFusion: 3D Human Body Reconstruction Using Stitched Bounding Boxes,
3DV18(190-198)
IEEE DOI 1812
cameras, image fusion, image reconstruction, image representation, image segmentation, motion estimation, solid modelling, skeleton BibRef

Sekii, T.[Taiki],
Pose Proposal Networks,
ECCV18(XIII: 350-366).
Springer DOI 1810
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Kim, J.[Jaehwan], Kim, H.[Howon],
Robust Geodesic Skeleton Estimation from Body Single Depth,
ACIVS18(342-353).
Springer DOI 1810
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Xu, J.H.[Jia-Hui], Hu, X.P.[Xiao-Ping],
A Study on the Differences of Male Youth Physical Characteristics Between South China and Northwest China,
DHM18(126-134).
Springer DOI 1807
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Qammaz, A., Michel, D., Argyros, A.,
A Hybrid Method for 3D Pose Estimation of Personalized Human Body Models,
WACV18(456-465)
IEEE DOI 1806
pose estimation, stochastic programming, 3D pose estimation, RGBD camera, RGBD data, articulated human body model, BibRef

Vu, H.T., Wilkinson, R.H., Lech, M., Cheng, E.,
A Comparison between Anatomy-Based and Data-Driven Tree Models for Human Pose Estimation,
DICTA17(1-7)
IEEE DOI 1804
convolution, learning (artificial intelligence), neural nets, pose estimation, trees (mathematics), Transforms BibRef

Jahangiri, E., Yuille, A.L.,
Generating Multiple Diverse Hypotheses for Human 3D Pose Consistent with 2D Joint Detections,
CMBFH17(805-814)
IEEE DOI 1802
Detectors, Pose estimation, Solid modeling, Torso BibRef

Nguyen, D.T., Tran, M.K., Yeung, S.K.,
An MRF-Poselets Model for Detecting Highly Articulated Humans,
ICCV15(1967-1975)
IEEE DOI 1602
Biological system modeling BibRef

Zhu, A.[Aichun], Snoussi, H., Cherouat, A.,
Articulated pose estimation via multiple mixture parts model,
AVSS15(1-5)
IEEE DOI 1511
pose estimation BibRef

Park, D.[Dennis], Ramanan, D.[Deva],
Articulated pose estimation with tiny synthetic videos,
ChaLearn15(58-66)
IEEE DOI 1510
Engines BibRef

Toshev, A.[Alexander], Szegedy, C.[Christian],
DeepPose: Human Pose Estimation via Deep Neural Networks,
CVPR14(1653-1660)
IEEE DOI 1409
cascades;deep learning;human pose estimation;neural networks BibRef

Sapp, B.[Benjamin], Toshev, A.[Alexander], Taskar, B.[Ben],
Cascaded Models for Articulated Pose Estimation,
ECCV10(II: 406-420).
Springer DOI 1009
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Ramakrishna, V.[Varun], Munoz, D.[Daniel], Hebert, M.[Martial], Bagnell, J.A.[James Andrew], Sheikh, Y.[Yaser],
Pose Machines: Articulated Pose Estimation via Inference Machines,
ECCV14(II: 33-47).
Springer DOI 1408
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Oleinikov, G.[Georgii], Miller, G.[Gregor], Little, J.J.[James J.], Fels, S.[Sidney],
Task-based control of articulated human pose detection for OpenVL,
WACV14(682-689)
IEEE DOI 1406
Clutter BibRef

Gkioxari, G.[Georgia], Arbelaez, P.[Pablo], Bourdev, L.[Lubomir], Malik, J.[Jitendra],
Articulated Pose Estimation Using Discriminative Armlet Classifiers,
CVPR13(3342-3349)
IEEE DOI 1309
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Bourdev, L.[Lubomir], Maji, S.[Subhransu], Brox, T.[Thomas], Malik, J.[Jitendra],
Detecting People Using Mutually Consistent Poselet Activations,
ECCV10(VI: 168-181).
Springer DOI 1009
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Bourdev, L.[Lubomir], Malik, J.[Jitendra],
Poselets: Body Part Detectors Trained Using 3D Human Pose Annotations,
ICCV09(1365-1372).
IEEE DOI
WWW Link. 0909
BibRef

Radwan, I.[Ibrahim], Dhall, A.[Abhinav], Goecke, R.[Roland],
Correcting pose estimation with implicit occlusion detection and rectification,
ICPR12(3496-3499).
WWW Link. 1302
Articulated pose. BibRef

Roig, G.[Gemma], Boix, X.[Xavier], de la Torre, F.[Fernando], Serrat, J.[Joan], Vilella, C.[Carles],
Hierarchical CRF with product label spaces for parts-based models,
FG11(657-664).
IEEE DOI 1103
Conditional Random Fields (CRF). Non-rigid objects (facial features, articulated body, pose) BibRef

Wang, S.[Sheng], Ai, H.Z.[Hai-Zhou], Yamashita, T.[Takayoshi], Lao, S.H.[Shi-Hong],
Combined Top-Down/Bottom-Up Human Articulated Pose Estimation Using AdaBoost Learning,
ICPR10(3670-3673).
IEEE DOI 1008
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Gopalan, R.[Raghuraman], Turaga, P.K.[Pavan K.], Chellappa, R.[Rama],
Articulation-Invariant Representation of Non-planar Shapes,
ECCV10(III: 286-299).
Springer DOI 1009
Articulated models. BibRef

Johnson, S.[Sam], Everingham, M.R.[Mark R.],
Learning effective human pose estimation from inaccurate annotation,
CVPR11(1465-1472).
IEEE DOI 1106
BibRef
Earlier:
Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation,
BMVC10(xx-yy).
HTML Version. 1009
BibRef
Earlier:
Combining discriminative appearance and segmentation cues for articulated human pose estimation,
MLMotion09(405-412).
IEEE DOI 0910
BibRef

Mateus, D.[Diana], Horaud, R.[Radu], Knossow, D.[David], Cuzzolin, F.[Fabio], Boyer, E.[Edmond],
Articulated shape matching using Laplacian eigenfunctions and unsupervised point registration,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Ren, X.F.[Xiao-Feng],
Learning and Matching Line Aspects for Articulated Objects,
CVPR07(1-8).
IEEE DOI 0706
Aspects for articulated objects. BibRef

Sigal, L.[Leonid], Black, M.J.[Michael J.],
Measure Locally, Reason Globally: Occlusion-sensitive Articulated Pose Estimation,
CVPR06(II: 2041-2048).
IEEE DOI 0606
BibRef
And:
Predicting 3D People from 2D Pictures,
AMDO06(185-195).
Springer DOI 0607
Award, AMDO. BibRef

Navaratnam, R., Thayananthan, A., Torr, P.H.S., Cipolla, R.,
Hierarchical Part-Based Human Body Pose Estimation,
BMVC05(xx-yy).
HTML Version. 0509

See also Model-Based Hand Tracking Using a Hierarchical Bayesian Filter. BibRef

Demirdjian, D.[David],
Combining Geometric- and View-Based Approaches for Articulated Pose Estimation,
ECCV04(Vol III: 183-194).
Springer DOI 0405
BibRef

Holstein, H., Li, B.,
Low Density Feature Point Matching for Articulated Pose Identification,
BMVC02(Industrial Applications). 0208
BibRef

Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Human Pose from Silhouettes .