22.4.2.3.4 Depth Based, Stereo, Hand Pose, Hand Posture, Hand Shape

Liang, H.[Hui], Yuan, J.S.[Jun-Song], Thalmann, D.,
Parsing the Hand in Depth Images,
MultMed(16), No. 5, August 2014, pp. 1241-1253.
IEEE DOI 1410
Markov processes BibRef

Ge, L.H.[Liu-Hao], Liang, H.[Hui], Yuan, J.S.[Jun-Song], Thalmann, D.[Daniel],
Robust 3D Hand Pose Estimation From Single Depth Images Using Multi-View CNNs,
IP(27), No. 9, September 2018, pp. 4422-4436.
IEEE DOI 1807
BibRef
Earlier:
3D Convolutional Neural Networks for Efficient and Robust Hand Pose Estimation from Single Depth Images,
CVPR17(5679-5688)
IEEE DOI 1711
BibRef
Earlier:
Robust 3D Hand Pose Estimation in Single Depth Images: From Single-View CNN to Multi-View CNNs,
CVPR16(3593-3601)
IEEE DOI 1612
neural nets, pose estimation, probability, regression analysis, articulated hand pose estimation, depth information, multi-view CNNs. Feature extraction, Real-time systems, Robustness, Solid modeling, BibRef

Ge, L.H.[Liu-Hao], Liang, H.[Hui], Yuan, J.S.[Jun-Song], Thalmann, D.[Daniel],
Real-Time 3D Hand Pose Estimation with 3D Convolutional Neural Networks,
PAMI(41), No. 4, April 2019, pp. 956-970.
IEEE DOI 1903
Pose estimation, Feature extraction, Solid modeling, deep learning BibRef

Xu, C.[Chi], Nanjappa, A.[Ashwin], Zhang, X.W.[Xiao-Wei], Cheng, L.[Li],
Estimate Hand Poses Efficiently from Single Depth Images,
IJCV(116), No. 1, January 2016, pp. 21-45.
Springer DOI 1601
BibRef

Xu, C.[Chi], Govindarajan, L.N.[Lakshmi Narasimhan], Zhang, Y.[Yu], Stewart, J.[James], Bichler, Z.[Zoë], Jesuthasan, S.[Suresh], Claridge-Chang, A.[Adam], Mathuru, A.S.[Ajay Sriram], Tang, W.L.[Wen-Long], Zhu, P.X.[Pei-Xin], Cheng, L.[Li],
Lie-X: Depth Image Based Articulated Object Pose Estimation, Tracking, and Action Recognition on Lie Groups,
IJCV(123), No. 3, July 2017, pp. 454-478.
Springer DOI 1706
BibRef
And: Author List Corrected: IJCV(126), No. 8, August 2018, pp. 897.
Springer DOI 1807
BibRef

Supancic, III, J.S.[James Steven], Rogez, G.[Grégory], Yang, Y.[Yi], Shotton, J.[Jamie], Ramanan, D.[Deva],
Depth-Based Hand Pose Estimation: Methods, Data, and Challenges,
IJCV(126), No. 11, November 2018, pp. 1180-1198.
Springer DOI 1809
BibRef
Earlier:
Depth-Based Hand Pose Estimation: Data, Methods, and Challenges,
ICCV15(1868-1876)
IEEE DOI 1602
BibRef
Earlier: A2, A1, A5, Only:
Understanding Everyday Hands in Action from RGB-D Images,
ICCV15(3889-3897)
IEEE DOI 1602
Benchmark testing; Clutter; Data models; Training data. Cameras BibRef

Basaru, R.R.[Rilwan Remilekun], Child, C.[Chris], Alonso, E.[Eduardo], Slabaugh, G.[Gregory],
Data-driven recovery of hand depth using CRRF on stereo images,
IET-CV(12), No. 5, August 2018, pp. 666-678.
DOI Link 1807
BibRef

Wang, P.C.[Pi-Chao], Li, W.Q.[Wan-Qing], Ogunbona, P.O.[Philip O.], Gao, Z.M.[Zhi-Min], Zhang, H.L.[Han-Ling],
Mining Mid-Level Features for Action Recognition Based on Effective Skeleton Representation,
DICTA14(1-8)
IEEE DOI 1502
computer graphics BibRef

Gomez-Donoso, F.[Francisco], Orts-Escolano, S.[Sergio], Cazorla, M.[Miguel],
Large-scale multiview 3D hand pose dataset,
IVC(81), 2019, pp. 25-33.
Elsevier DOI 1902
3D hand pose, Multiview, Dataset, Deep learning BibRef

Wang, G.J.[Gui-Jin], Chen, X.H.[Xing-Hao], Guo, H.K.[Heng-Kai], Zhang, C.R.[Cai-Rong],
Region ensemble network: Towards good practices for deep 3D hand pose estimation,
JVCIR(55), 2018, pp. 404-414.
Elsevier DOI 1809
Convolutional network, Hand pose estimation, Human pose estimation, Fingertip detection, Ensemble learning, Depth imaging BibRef

Guo, H., Wang, G., Chen, X., Zhang, C., Qiao, F., Yang, H.,
Region ensemble network: Improving convolutional network for hand pose estimation,
ICIP17(4512-4516)
IEEE DOI 1803
Bagging, Convolution, Pose estimation, Testing, Training, Convolutional Network, Hand Pose Estimation BibRef

Wu, Y., Ji, W., Li, X., Wang, G., Yin, J., Wu, F.,
Context-Aware Deep Spatiotemporal Network for Hand Pose Estimation From Depth Images,
Cyber(50), No. 2, February 2020, pp. 787-797.
IEEE DOI 1912
Feature extraction, Pose estimation, Spatiotemporal phenomena, Image sequences, Context modeling, Adaptation models, Data mining, hand pose estimation BibRef

Oberweger, M.[Markus], Wohlhart, P.[Paul], Lepetit, V.[Vincent],
Generalized Feedback Loop for Joint Hand-Object Pose Estimation,
PAMI(42), No. 8, August 2020, pp. 1898-1912.
IEEE DOI 2007
BibRef
Earlier:
Training a Feedback Loop for Hand Pose Estimation,
ICCV15(3316-3324)
IEEE DOI 1602
Pose estimation, Solid modeling, Optimization, Feedback loop, Training data, Data models, hand-object manipulation BibRef

Oberweger, M., Riegler, G., Wohlhart, P., Lepetit, V.,
Efficiently Creating 3D Training Data for Fine Hand Pose Estimation,
CVPR16(4957-4965)
IEEE DOI 1612
Data models BibRef

Wang, L., Cao, Z., Cui, Z., Cao, C., Pi, Y.,
Negative Latency Recognition Method for Fine-Grained Gestures Based on Terahertz Radar,
GeoRS(58), No. 11, November 2020, pp. 7955-7968.
IEEE DOI 2011
Gesture recognition, Doppler radar, Radar imaging, Indexes, Human computer interaction, Acoustics, Gesture recognition, terahertz radar BibRef

Yang, J.[Jian], Ma, X.H.[Xiao-Hong], Sun, Y.[Yi], Lin, X.B.[Xiang-Bo],
LPPM-Net: Local-aware point processing module based 3D hand pose estimation for point cloud,
SP:IC(90), 2021, pp. 116036.
Elsevier DOI 2012
Hand pose estimation, Point cloud, Deep learning, Local-aware point processing module BibRef

Deng, X., Zhu, Y., Zhang, Y., Cui, Z., Tan, P., Qu, W., Ma, C., Wang, H.,
Weakly Supervised Learning for Single Depth-Based Hand Shape Recovery,
IP(30), 2021, pp. 532-545.
IEEE DOI 2012
Shape, Skeleton, Solid modeling, Image reconstruction, Pose estimation, Data models, gesture recognition BibRef

Zhang, Y.[Yu], Mi, S.[Siya], Wu, J.X.[Jian-Xin], Geng, X.[Xin],
Simultaneous 3D hand detection and pose estimation using single depth images,
PRL(140), 2020, pp. 43-48.
Elsevier DOI 2012
3D hand pose estimation, Hand detection, 3D region proposal BibRef

Sun, J.[Jin], Zhang, Z.[Zhe], Yang, L.[Liutao], Zheng, J.P.[Ji-Ping],
Multi-view hand gesture recognition via pareto optimal front,
IET-IPR(14), No. 14, December 2020, pp. 3579-3587.
DOI Link 2012
BibRef

Xu, L., Hu, C., Tao, J., Xue, J., Mei, K.,
Improve Regression Network on Depth Hand Pose Estimation With Auxiliary Variable,
CirSysVideo(31), No. 3, March 2021, pp. 890-904.
IEEE DOI 2103
Pose estimation, Feature extraction, Kinematics, Task analysis, Training, variational autoencoder BibRef

Kumar, A.K.[Amit Krishan], Kumar, A.K.[Abhishek Kaushal], Guo, S.[Shuli],
Two viewpoints based real-time recognition for hand gestures,
IET-IPR(14), No. 17, 24 December 2020, pp. 4606-4613.
DOI Link 2104
BibRef

Xia, Z.Y.[Zhao-Yang], Luomei, Y.X.[Yi-Xiang], Zhou, C.L.[Cheng-Long], Xu, F.[Feng],
Multidimensional Feature Representation and Learning for Robust Hand-Gesture Recognition on Commercial Millimeter-Wave Radar,
GeoRS(59), No. 6, June 2021, pp. 4749-4764.
IEEE DOI 2106
Gesture recognition, Feature extraction, Robustness, Radar imaging, Signal resolution, Scattering, Detection and tracking, multidimensional feature BibRef

Madadi, M.[Meysam], Escalera, S.[Sergio], Baró, X.[Xavier], Gonzàlez, J.[Jordi],
End-to-end global to local convolutional neural network learning for hand pose recovery in depth data,
IET-CV(16), No. 1, 2022, pp. 50-66.
DOI Link 2202
data acquisition, human computer interaction, learning (artificial intelligence), pose estimation BibRef

Wang, Y.[Yong], Wang, D.[Di], Fu, Y.H.[Yun-Hai], Yao, D.[Dengke], Xie, L.B.[Liang-Bo], Zhou, M.[Mu],
Multi-Hand Gesture Recognition Using Automotive FMCW Radar Sensor,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Ren, P.F.[Peng-Fei], Sun, H.F.[Hai-Feng], Hao, J.[Jiachang], Qi, Q.[Qi], Wang, J.Y.[Jing-Yu], Liao, J.X.[Jian-Xin],
A Dual-Branch Self-Boosting Framework for Self-Supervised 3D Hand Pose Estimation,
IP(31), 2022, pp. 5052-5066.
IEEE DOI 2208
Solid modeling, Pose estimation, Data models, Shape, Gesture recognition, Training, 3D hand pose estimation, gesture recognition BibRef

Zheng, X.Z.[Xiao-Zheng], Wen, C.[Chao], Xue, Z.[Zhou], Ren, P.F.[Peng-Fei], Wang, J.Y.[Jing-Yu],
HaMuCo: Hand Pose Estimation via Multiview Collaborative Self-Supervised Learning,
ICCV23(20706-20716)
IEEE DOI 2401
BibRef

Deng, X.M.[Xiao-Ming], Zuo, D.[Dexin], Zhang, Y.[Yinda], Cui, Z.P.[Zhao-Peng], Cheng, J.[Jian], Tan, P.[Ping], Chang, L.[Liang], Pollefeys, M.[Marc], Fanello, S.[Sean], Wang, H.A.[Hong-An],
Recurrent 3D Hand Pose Estimation Using Cascaded Pose-Guided 3D Alignments,
PAMI(45), No. 1, January 2023, pp. 932-945.
IEEE DOI 2212
Pose estimation, Feature extraction, Point cloud compression, Solid modeling, Data models, Data mining, Hand pose estimation, recurrent model BibRef

Ren, P.F.[Peng-Fei], Sun, H.F.[Hai-Feng], Hao, J.C.[Jia-Chang], Qi, Q.[Qi], Wang, J.Y.[Jing-Yu], Liao, J.X.[Jian-Xin],
Pose-Guided Hierarchical Graph Reasoning for 3-D Hand Pose Estimation From a Single Depth Image,
Cyber(53), No. 1, January 2023, pp. 315-328.
IEEE DOI 2301
Convolution, Feature extraction, Pose estimation, Bones, Visualization, Joints, Germanium, 3-D hand pose estimation, graph convolutions BibRef

Xing, H.Q.[Hui-Qin], Yang, J.Y.[Jian-Yu], Xiao, Y.[Yang],
Learning dynamic relationship between joints for 3D hand pose estimation from single depth map,
JVCIR(92), 2023, pp. 103803.
Elsevier DOI 2303
Hand pose estimation, Dynamic anchor, Hand gesture, Depth map BibRef

Sun, S.Q.[Shu-Qiao], Liu, R.[Rongke], Yang, X.X.[Xin-Xin],
Depth-Hand: 3D Hand Keypoint Detection With Dense Depth Estimation,
SPLetters(30), 2023, pp. 962-966.
IEEE DOI 2308
Estimation, Feature extraction, Crops, Costs, Task analysis, Multitasking, Depth estimation, stereoscopic vision, multi-task BibRef

Xiang, D.H.[Dong-Hai], Xu, W.[Wei], Zhang, Y.T.[Yu-Ting], Peng, B.[Bei], Wang, G.[Guotai], Li, K.[Kang],
MTMVC: Semi-supervised 3D hand pose estimation using multi-task and multi-view consistency,
JVCIR(95), 2023, pp. 103902.
Elsevier DOI 2309
Hand pose estimation, Semi-supervised learning, Deep learning, Consistency constraint BibRef

Sun, H.F.[Hai-Feng], Zheng, X.Z.[Xiao-Zheng], Ren, P.F.[Peng-Fei], Wang, J.Y.[Jing-Yu], Qi, Q.[Qi], Liao, J.X.[Jian-Xin],
SMR: Spatial-Guided Model-Based Regression for 3D Hand Pose and Mesh Reconstruction,
CirSysVideo(34), No. 1, January 2024, pp. 299-314.
IEEE DOI 2401
BibRef

Zhou, J.[Jun], Xu, C.[Chi], Ge, Y.T.[Yu-Ting], Cheng, L.[Li],
Realistic Depth Image Synthesis for 3D Hand Pose Estimation,
MultMed(26), 2024, pp. 5246-5256.
IEEE DOI 2404
Pose estimation, Cameras, Training, Noise measurement, Image synthesis, Engines, Depth noise modeling, realistic depth synthesis BibRef

Xu, C.[Chi], Cheng, L.[Li],
Efficient Hand Pose Estimation from a Single Depth Image,
ICCV13(3456-3462)
IEEE DOI 1403
hand pose estimation; random forest; realtime BibRef

Jin, B.[Biao], Ma, X.[Xiao], Hu, B.[Bojun], Zhang, Z.K.[Zhen-Kai], Lian, Z.[Zhuxian], Wang, B.[Biao],
Gesture-mmWAVE: Compact and Accurate Millimeter-Wave Radar-Based Dynamic Gesture Recognition for Embedded Devices,
HMS(54), No. 3, June 2024, pp. 337-347.
IEEE DOI 2405
Convolution, Feature extraction, Millimeter wave radar, Gesture recognition, Transformers, Radar, Scattering, Deep learning, transformer BibRef

Wang, J.[Jiye], Xiang, X.Z.[Xue-Zhi], Ding, S.[Shuai], El Saddik, A.[Abdulmotaleb],
3D hand pose estimation and reconstruction based on multi-feature fusion,
JVCIR(101), 2024, pp. 104160.
Elsevier DOI 2406
Hand pose estimation, Shape reconstruction, Multi-feature fusion, Multi-scale, Multi-root loss BibRef

Jiang, J.P.[Jian-Ping], Li, J.[Jiahe], Zhang, B.[Baowen], Deng, X.M.[Xiao-Ming], Shi, B.X.[Bo-Xin],
EvHandPose: Event-Based 3D Hand Pose Estimation With Sparse Supervision,
PAMI(46), No. 9, September 2024, pp. 6416-6430.
IEEE DOI 2408
Pose estimation, Cameras, Annotations, Streaming media, Optical flow, Shape, 3D hand pose estimation, event camera BibRef

Cheng, W.C.[Wen-Can], Tang, H.[Hao], Van Gool, L.J.[Luc J.], Ko, J.H.[Jong Hwan],
HandDiff: 3D Hand Pose Estimation with Diffusion on Image-Point Cloud,
CVPR24(2274-2284)
IEEE DOI Code:
WWW Link. 2410
Point cloud compression, Location awareness, Human computer interaction, Accuracy, Pose estimation BibRef

Millerdurai, C.[Christen], Luvizon, D.[Diogo], Rudnev, V.[Viktor], Jonas, A.[André], Wang, J.Y.[Jia-Yi], Theobalt, C.[Christian], Golyanik, V.[Vladislav],
3D Pose Estimation of Two Interacting Hands from a Monocular Event Camera,
3DV24(291-301)
IEEE DOI Code:
WWW Link. 2408
Image segmentation, Visualization, Tracking, Motion segmentation, Pose estimation, Benchmark testing, hand pose estimation, event-based vision BibRef

Zhang, S.[Shujie], Zheng, T.Y.[Tian-Yue], Chen, Z.[Zhe], Hu, J.Z.[Jing-Zhi], Khamis, A.[Abdelwahed], Liu, J.J.[Jia-Jun], Luo, J.[Jun],
OCHID-Fi: Occlusion-Robust Hand Pose Estimation in 3D via RF-Vision,
ICCV23(15066-15075)
IEEE DOI 2401
BibRef

Wirth, V.[Vanessa], Liphardt, A.M.[Anna-Maria], Coppers, B.[Birte], Bräunig, J.[Johanna], Heinrich, S.[Simon], Leyendecker, S.[Sigrid], Kleyer, A.[Arnd], Schett, G.[Georg], Vossiek, M.[Martin], Egger, B.[Bernhard], Stamminger, M.[Marc],
ShaRPy: Shape Reconstruction and Hand Pose Estimation from RGB-D with Uncertainty,
CVAMD23(2617-2625)
IEEE DOI 2401
BibRef

Song, Y.Q.[Yu-Qing], Wu, L.[Longwen], Zhao, Y.Q.[Ya-Qin], Liu, P.[Puqiu], Lv, R.[Ruchen], Ullah, H.[Hikmat],
High-Accuracy Gesture Recognition using Mm-Wave Radar Based on Convolutional Block Attention Module,
ICIP23(1485-1489)
IEEE DOI 2312
BibRef

Wang, Y.[Yintong], Chen, L.[LiLi], Li, J.[Jiamao], Zhang, X.L.[Xiao-Lin],
HandGCNFormer: A Novel Topology-Aware Transformer Network for 3D Hand Pose Estimation,
WACV23(5664-5673)
IEEE DOI 2302
Head, Network topology, Pose estimation, Kinematics, Transformers, Topology, Algorithms: Biometrics, face, gesture, body pose, 3D computer vision BibRef

Meng, H.[Hao], Jin, S.[Sheng], Liu, W.T.[Wen-Tao], Qian, C.[Chen], Lin, M.X.[Meng-Xiang], Ouyang, W.L.[Wan-Li], Luo, P.[Ping],
3D Interacting Hand Pose Estimation by Hand De-occlusion and Removal,
ECCV22(VI:380-397).
Springer DOI 2211
BibRef

Ren, P.F.[Peng-Fei], Sun, H.F.[Hai-Feng], Hao, J.[Jiachang], Wang, J.Y.[Jing-Yu], Qi, Q.[Qi], Liao, J.X.[Jian-Xin],
Mining Multi-View Information: A Strong Self-Supervised Framework for Depth-based 3D Hand Pose and Mesh Estimation,
CVPR22(20523-20533)
IEEE DOI 2210
Training, Convolution, Aggregates, Semantics, Pose estimation, Face and gestures, 3D from multi-view and sensors, Self- semi- meta- unsupervised learning BibRef

Chen, Z.[Zheng], Wang, S.[Sihan], Sun, Y.[Yi], Ma, X.H.[Xiao-Hong],
Self-supervised Transfer Learning for Hand Mesh Recovery from Binocular Images,
ICCV21(11606-11614)
IEEE DOI 2203
Training, Adaptation models, Annotations, Shape, Computational modeling, Transfer learning, 3D from multiview and other sensors BibRef

Xu, H.[Hao], Wang, T.Y.[Tian-Yu], Tang, X.[Xiao], Fu, C.W.[Chi-Wing],
H2ONet: Hand-Occlusion-and-Orientation-Aware Network for Real-Time 3D Hand Mesh Reconstruction,
CVPR23(17048-17058)
IEEE DOI 2309
BibRef
Earlier: A3, A2, A4, Only:
Towards Accurate Alignment in Real-time 3D Hand-Mesh Reconstruction,
ICCV21(11678-11687)
IEEE DOI 2203
Shape, Pipelines, Predictive models, Benchmark testing, Real-time systems, Gestures and body pose, BibRef

Rudnev, V.[Viktor], Golyanik, V.[Vladislav], Wang, J.Y.[Jia-Yi], Seidel, H.P.[Hans-Peter], Mueller, F.[Franziska], Elgharib, M.[Mohamed], Theobalt, C.[Christian],
EventHands: Real-Time Neural 3D Hand Pose Estimation from an Event Stream,
ICCV21(12365-12375)
IEEE DOI 2203
Image color analysis, Pose estimation, Vision sensors, Cameras, Throughput, 3D from a single image and shape-from-x, Motion and tracking BibRef

Cheng, W.C.[Wen-Can], Park, J.H.[Jae Hyun], Ko, J.H.[Jong Hwan],
HandFoldingNet: A 3D Hand Pose Estimation Network Using Multiscale-Feature Guided Folding of a 2D Hand Skeleton,
ICCV21(11240-11249)
IEEE DOI 2203
Point cloud compression, Human computer interaction, Solid modeling, Computational modeling, Pose estimation, Efficient training and inference methods BibRef

Yang, J.[John], Bhalgat, Y.[Yash], Chang, S.[Simyung], Porikli, F.M.[Fatih M.], Kwak, N.[Nojun],
Dynamic Iterative Refinement for Efficient 3D Hand Pose Estimation,
WACV22(2703-2713)
IEEE DOI 2202
Training, Uncertainty, Protocols, Pose estimation, Refining, Neural networks, Real-time Tracking Virtual and Augmented Reality BibRef

Bigalke, A.[Alexander], Heinrich, M.P.[Mattias P.],
Fusing Posture and Position Representations for Point Cloud-Based Hand Gesture Recognition,
3DV21(617-626)
IEEE DOI 2201
Point cloud compression, Codes, Tracking, Gesture recognition, Computer architecture, Feature extraction, point cloud analysis BibRef

Müller, M.[Markus], Poier, G.[Georg], Possegger, H.[Horst], Bischof, H.[Horst],
Semi-Supervised Learning of Monocular 3D Hand Pose Estimation from Multi-View Images,
ICIP21(1104-1108)
IEEE DOI 2201
Training, Annotations, Image processing, Pose estimation, Semisupervised learning, hand pose estimation, semi-supervised training BibRef

Chen, L.J.[Liang-Jian], Lin, S.Y.[Shih-Yao], Xie, Y.S.[Yu-Sheng], Lin, Y.Y.[Yen-Yu], Xie, X.H.[Xiao-Hui],
MVHM: A Large-Scale Multi-View Hand Mesh Benchmark for Accurate 3D Hand Pose Estimation,
WACV21(836-845)
IEEE DOI 2106
Training, Annotations, Fuses, Pose estimation, Pipelines BibRef

Chen, L.J.[Liang-Jian], Lin, S.Y.[Shih-Yao], Xie, Y.S.[Yu-Sheng], Lin, Y.Y.[Yen-Yu], Xie, X.H.[Xiao-Hui],
Temporal-Aware Self-Supervised Learning for 3D Hand Pose and Mesh Estimation in Videos,
WACV21(1049-1058)
IEEE DOI 2106
Training, Solid modeling, Annotations, Computational modeling, BibRef

Caramalau, R.[Razvan], Bhattarai, B.[Binod], Kim, T.K.[Tae-Kyun],
Active Learning for Bayesian 3D Hand Pose Estimation,
WACV21(3418-3427)
IEEE DOI 2106
Deep learning, Uncertainty, Pose estimation, Redundancy BibRef

Kok, F.[Felix], Charles, J.[James], Cipolla, R.[Roberto],
Footnet: An Efficient Convolutional Network for Multiview 3d Foot Reconstruction,
ACCV20(VI:36-51).
Springer DOI 2103
BibRef

Jaswal, G.[Gaurav], Srirangarajan, S.[Seshan], Roy, S.D.[Sumantra Dutta],
Range-doppler Hand Gesture Recognition Using Deep Residual-3dcnn with Transformer Network,
MPRSS20(759-772).
Springer DOI 2103
BibRef

Wang, J., Mueller, F., Bernard, F., Theobalt, C.,
Generative Model-Based Loss to the Rescue: A Method to Overcome Annotation Errors for Depth-Based Hand Pose Estimation,
FG20(101-108)
IEEE DOI 2102
Gesture recognition, Face recognition, hand pose estimation, annotation bias, generative loss, depth image BibRef

Fang, L.P.[Lin-Pu], Liu, X.Y.[Xing-Yan], Liu, L.[Li], Xu, H.[Hang], Kang, W.X.[Wen-Xiong],
JGR-P2O: Joint Graph Reasoning Based Pixel-to-offset Prediction Network for 3d Hand Pose Estimation from a Single Depth Image,
ECCV20(VI:120-137).
Springer DOI 2011
BibRef

Yang, J.[John], Chang, H.J.[Hyung Jin], Lee, S.[Seungeui], Kwak, N.J.[No-Jun],
Seqhand: RGB-sequence-based 3d Hand Pose and Shape Estimation,
ECCV20(XII: 122-139).
Springer DOI 2010
BibRef

Wan, C.D.[Cheng-De], Probst, T.[Thomas], Van Gool, L.J.[Luc J.], Yao, A.[Angela],
Dual Grid Net: Hand Mesh Vertex Regression from Single Depth Maps,
ECCV20(XXX: 442-459).
Springer DOI 2010
BibRef

Min, Y., Zhang, Y., Chai, X., Chen, X.,
An Efficient PointLSTM for Point Clouds Based Gesture Recognition,
CVPR20(5760-5769)
IEEE DOI 2008
Gesture recognition, Feature extraction, Task analysis, Data mining, Logic gates BibRef

Gu, J., Wang, Z., Ouyang, W., Zhang, W., Li, J., Zhuo, L.,
3D Hand Pose Estimation with Disentangled Cross-Modal Latent Space,
WACV20(380-389)
IEEE DOI 2006
Pose estimation, Task analysis, Solid modeling, Decoding BibRef

Chen, L., Lin, S., Xie, Y., Lin, Y., Fan, W., Xie, X.,
DGGAN: Depth-image Guided Generative Adversarial Networks for Disentangling RGB and Depth Images in 3D Hand Pose Estimation,
WACV20(400-408)
IEEE DOI 2006
Training, Image reconstruction, Pose estimation, Task analysis, Solid modeling BibRef

Zhu, T., Sun, Y., Ma, X., Lin, X.,
Hand Pose Ensemble Learning Based on Grouping Features of Hand Point Sets,
Hands19(2856-2865)
IEEE DOI 2004
feature extraction, feature selection, learning (artificial intelligence), pose estimation, Ensemble learning BibRef

Ge, L., Cai, Y., Weng, J., Yuan, J.,
Hand PointNet: 3D Hand Pose Estimation Using Point Sets,
CVPR18(8417-8426)
IEEE DOI 1812
Pose estimation, Feature extraction, Cameras, Neural networks, Sensitivity BibRef

Malik, J., Elhayek, A., Nunnari, F., Varanasi, K., Tamaddon, K., Heloir, A., Stricker, D.,
DeepHPS: End-to-end Estimation of 3D Hand Pose and Shape by Learning from Synthetic Depth,
3DV18(110-119)
IEEE DOI 1812
image classification, image motion analysis, image segmentation, learning (artificial intelligence), convolutional neural networks BibRef

Baek, S., Kim, K.I., Kim, T.,
Augmented Skeleton Space Transfer for Depth-Based Hand Pose Estimation,
CVPR18(8330-8339)
IEEE DOI 1812
Skeleton, Shape, Training, Cameras, Pose estimation, Databases BibRef

Li, J., Wang, Z.,
Local Regression Based Hourglass Network for Hand Pose Estimation from a Single Depth Image,
ICPR18(1767-1772)
IEEE DOI 1812
Feature extraction, Task analysis, Pose estimation, Convolutional neural networks, Sensors BibRef

Yuan, S., Garcia-Hernando, G., Stenger, B., Moon, G., Chang, J.Y., Lee, K.M., Molchanov, P., Kautz, J., Honari, S., Ge, L., Yuan, J., Chen, X., Wang, G., Yang, F., Akiyama, K., Wu, Y., Wan, Q., Madadi, M., Escalera, S., Li, S., Lee, D., Oikonomidis, I., Argyros, A., Kim, T.,
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals,
CVPR18(2636-2645)
IEEE DOI 1812
Task analysis, Pose estimation, Joints, Training, Solid modeling BibRef

Wan, C., Probst, T., Van Gool, L.J., Yao, A.,
Dense 3D Regression for Hand Pose Estimation,
CVPR18(5147-5156)
IEEE DOI 1812
Pose estimation, Heating systems, Skeleton, Correlation BibRef

Zhou, Y.[Yidan], Lu, J.[Jian], Du, K.[Kuo], Lin, X.B.[Xiang-Bo], Sun, Y.[Yi], Ma, X.H.[Xiao-Hong],
HBE: Hand Branch Ensemble Network for Real-Time 3D Hand Pose Estimation,
ECCV18(XIV: 521-536).
Springer DOI 1810
BibRef

Zhang, J., Jiao, J., Chen, M., Qu, L., Xu, X., Yang, Q.,
A hand pose tracking benchmark from stereo matching,
ICIP17(982-986)
IEEE DOI 1803
Benchmark testing, Cameras, Image color analysis, Image segmentation, Noise measurement, Skin, Training, stereo matching and hand pose tracking BibRef

Basaru, R.R., Child, C., Alonso, E., Slabaugh, G.,
Hand Pose Estimation Using Deep Stereovision and Markov-Chain Monte Carlo,
Hands17(595-603)
IEEE DOI 1802
Cameras, Monte Carlo methods, Pose estimation, Proposals, Robustness BibRef

Otberdout, N., Ballihi, L., Aboutajdine, D.,
Hand pose estimation based on deep learning depth map for hand gesture recognition,
ISCV17(1-8)
IEEE DOI 1710
Gesture recognition, Neural networks, Neurons, Pose estimation, Solid modeling, Three-dimensional, displays BibRef

Goudie, D., Galata, A.,
3D Hand-Object Pose Estimation from Depth with Convolutional Neural Networks,
FG17(406-413)
IEEE DOI 1707
Cost function, Image segmentation, Neural networks, Pose estimation, Sensors, Training BibRef

Madadi, M., Escalera, S., Carruesco, A., Andujar, C., Baró, X., Gonzàlez, J.,
Occlusion Aware Hand Pose Recovery from Sequences of Depth Images,
FG17(230-237)
IEEE DOI 1707
Cameras, Computational modeling, Feature extraction, Pose estimation, Shape, Solid modeling, Three-dimensional, displays BibRef

Asad, M.[Muhammad], Gentet, E.[Enguerrand], Basaru, R.R.[Rilwan Remilekun], Slabaugh, G.[Greg],
Generatinga 3D hand model from frontal color and range scans,
ICIP15(4589-4593)
IEEE DOI 1512
Hand model; pose estimation; reconstruction BibRef

Guo, H., Wang, G., Chen, X.,
Two-stream convolutional neural network for accurate RGB-D fingertip detection using depth and edge information,
ICIP16(2608-2612)
IEEE DOI 1610
BibRef
And: A3, A2, A1:
Accurate fingertip detection from binocular mask images,
VCIP16(1-4)
IEEE DOI 1701
Image edge detection BibRef

Khamis, S.[Sameh], Taylor, J.[Jonathan], Shotton, J.[Jamie], Keskin, C.[Cem], Izadi, S.[Shahram], Fitzgibbon, A.W.[Andrew W.],
Learning an efficient model of hand shape variation from depth images,
CVPR15(2540-2548)
IEEE DOI 1510
BibRef

Fan, C.Y.[Chin-Yun], Lin, M.H.[Meng-Hsuan], Su, T.F.[Te-Feng], Lai, S.H.[Shang-Hong], Yu, C.H.[Chih-Hsiang],
3D hand skeleton model estimation from a depth image,
MVA15(489-492)
IEEE DOI 1507
Computational modeling BibRef

Sohn, M.K.[Myoung-Kyu], Kim, D.J.[Dong-Ju], Kim, H.[Hyunduk],
Hand Part Classification Using Single Depth Images,
UCCV14(253-261).
Springer DOI 1504
BibRef

Rogez, G.[Grégory], Khademi, M.[Maryam], Supancic, III, J.S., Montiel, J.M.M., Ramanan, D.[Deva],
3D Hand Pose Detection in Egocentric RGB-D Images,
CDC4CV14(356-371).
Springer DOI 1504
BibRef

Taylor, J.[Jonathan], Stebbing, R.[Richard], Ramakrishna, V.[Varun], Keskin, C.[Cem], Shotton, J.[Jamie], Izadi, S.[Shahram], Hertzmann, A.[Aaron], Fitzgibbon, A.W.[Andrew W.],
User-Specific Hand Modeling from Monocular Depth Sequences,
CVPR14(644-651)
IEEE DOI 1409
BibRef

Kang, B.[Byungkyu], Rodrigue, M., Hollerer, T., Lim, H.[Hwasup],
Real time hand pose recognition with depth sensors for mixed reality interfaces,
3DUI13(171-172)
IEEE DOI 1406
decision trees BibRef

Bagdanov, A.D.[Andrew D.], del Bimbo, A.[Alberto], Seidenari, L.[Lorenzo], Usai, L.[Lorenzo],
Real-time hand status recognition from RGB-D imagery,
ICPR12(2456-2459).
WWW Link. 1302
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Wang, Q.[Qi], Chen, X.L.[Xi-Lin], Gao, W.[Wen],
Skin Color Weighted Disparity Competition for Hand Segmentation from Stereo Camera,
BMVC10(xx-yy).
HTML Version. 1009
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Tran, C.[Cuong], Trivedi, M.M.[Mohan M.],
Hand modeling and tracking from voxel data: An integrated framework with automatic initialization,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Delamarre, Q., Faugeras, O.D.,
Finding Pose of Hand in Video Images: A Stereo-Based Approach,
AFGR98(585-590).
IEEE DOI
PS File. BibRef 9800

Chapter on Face Recognition, Human Pose, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Hand Tracking for Gestures .