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Semi-Supervised 3D Hand Shape and Pose Estimation with Label Propagation
[article]
2021
Preserved Fulltext
To tackle this issue in the context of semi-supervised 3D hand shape and pose estimation, we propose the Pose Alignment network to propagate 3D annotations from labelled frames to nearby unlabelled frames ...
We show that incorporating the alignment supervision on pairs of labelled-unlabelled frames allows us to improve the pose estimation accuracy. ...
The checkmarks show that the methods include 6D object pose estimation. 7 1 4 Fig. 1 . 41 Fig. 1. Overview of our framework for semi-supervised 3D hand pose and shape prediction. ...
doi:10.48550/arxiv.2111.15199
fatcat:5c6ndvux3fhjrjzfnm7k7kdriq
Monocular 3D Human Pose Estimation with a Semi-supervised Graph-Based Method
2015
2015 International Conference on 3D Vision
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In this paper, a semi-supervised graph-based method for estimating 3D body pose from a sequence of silhouettes, is presented. ...
Furthermore, by exploiting the relationships between labeled and unlabeled data, the proposed method can estimate the 3D body poses, with a small set of labeled data. ...
On one hand, generative approaches require a 3D human body model with parameters such as 3D joint angles, 3D joint positions, and 3D shapes, which constitutes the parameter space. ...
doi:10.1109/3dv.2015.64
dblp:conf/3dim/AbbasiRG15
fatcat:si3an5t66bdt3hgiveqvpmsbry
Joint Affinity Propagation for Multiple View Segmentation
2007
2007 IEEE 11th International Conference on Computer Vision
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Third, a semi-supervised affinity propagation algorithm is proposed to refine the automatic results with the user assistance. ...
Then, we propose a hierarchical sparse affinity propagation algorithm to automatically and jointly segment 2D images and group 3D points. ...
Acknowledgements The work is supported by Hong Kong RGC projects 619005, 619006 and 619107, and NSFC/RGC Joint Grant N-HKUST602/05. ...
doi:10.1109/iccv.2007.4408928
dblp:conf/iccv/XiaoWTQ07
fatcat:pahxtrvjjjdczhx5zxeyjqpy2y
3D Object Structure Recovery via Semi-supervised Learning on Videos
2018
British Machine Vision Conference
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In this work, we propose a semi-supervised learning strategy to build a robust 3D object interpreter, which exploits rich object videos for better generalization under large pose variations and noisy 2D ...
This paper addresses the problem of joint 3D object structure and camera pose estimation from a single RGB image. ...
Our semi-supervised learning strategy allows the 2D-to-3D module to cope with the inaccurate 2D estimations in a more robust manner and thus produces better 3D predictions. ...
dblp:conf/bmvc/HeZH18
fatcat:djlnrdjtorattfv5in2rtisho4
Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels
[article]
2020
arXiv
pre-print
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The training of deep-learning-based 3D object detectors requires large datasets with 3D bounding box labels for supervision that have to be generated by hand-labeling. ...
We propose a network architecture and training procedure for learning monocular 3D object detection without 3D bounding box labels. ...
This work has been presented at the German Conference for Pattern Recognition (GCPR) 2020 and the final paper will be published in LNCS (Springer). ...
arXiv:2010.03506v1
fatcat:mrqr2gth4nhurjrcl7bjqzk7kq
Dual Grid Net: hand mesh vertex regression from single depth maps
[article]
2019
arXiv
pre-print
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We present a method for recovering the dense 3D surface of the hand by regressing the vertex coordinates of a mesh model from a single depth map. ...
With multi-camera rig during training to resolve self-occlusion, it can perform competitively with strongly supervised methods Without any human annotation. ...
Introduction We consider the problem of estimating the 3D object shape and pose from single depth images. ...
arXiv:1907.10695v1
fatcat:67ln42zlujf73kgiwddedplruu
Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset
[article]
2022
arXiv
pre-print
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We utilize this data to generalize category-level 6D object pose estimation in the wild with semi-supervised learning. ...
Project page with Wild6D data: https://oasisyang.github.io/semi-pose . ...
The RePoNet is composed of two branches of networks with a Pose Network to estimate the 6D object pose and a Shape Network to estimate the 3D object shape. ...
arXiv:2206.15436v1
fatcat:qygwkazj7vetbpa25qj4mwx3te
Learning Pose Specific Representations by Predicting Different Views
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
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That is, given only the pose and shape parameters of a hand, the hand's appearance from any viewpoint can be approximated. ...
Moreover, when training the proposed method jointly with labeled and unlabeled data, it consistently surpasses the performance of its fully supervised counterpart, while reducing the amount of needed labeled ...
for manually labeling hand poses. ...
doi:10.1109/cvpr.2018.00014
dblp:conf/cvpr/PoierSB18
fatcat:iwsnpeyhj5gsrapwqzivokqicu
3D AffordanceNet: A Benchmark for Visual Object Affordance Understanding
[article]
2021
arXiv
pre-print
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In this work, we present a 3D AffordanceNet dataset, a benchmark of 23k shapes from 23 semantic object categories, annotated with 18 visual affordance categories. ...
In addition we also investigate a semi-supervised learning setup to explore the possibility to benefit from unlabeled data. ...
The words Full-Shape and VAT represent full-shape estimation and semi-supervised affordance estimation with virtual adversarial training. Wrap. is the abbreviation of Wrap-Grasp. ...
arXiv:2103.16397v2
fatcat:5iqpr46jbndmjkw3b46hymbaku
Hand Pose Estimation through Semi-Supervised and Weakly-Supervised Learning
[article]
2017
arXiv
pre-print
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We propose a method for hand pose estimation based on a deep regressor trained on two different kinds of input. ...
The mapping from raw depth to segmentation maps is learned in a semi/weakly-supervised way from two different datasets: (i) a synthetic dataset created through a rendering pipeline including densely labeled ...
Taylor acknowledges the support of NSERC, CFI, and NVIDIA. ...
arXiv:1511.06728v4
fatcat:r4jbkd6poffs3h2ow6xmou4ej4
Author Index
2010
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
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Workshop: Automated Pose Estimation in 3D Point Clouds Applying Annealing Particle Filters and
Inverse Kinematics on a GPU
Leistner, Christian
Online Multi-Class LPBoost
On-line Semi-supervised Multiple-Instance ...
Object and Human Pose in Human-Object Interaction Activities
Connecting Modalities: Semi-supervised Segmentation and Annotation of Images Using Unaligned
Text Corpora
Felzenszwalb, Pedro F. ...
doi:10.1109/cvpr.2010.5539913
fatcat:y6m5knstrzfyfin6jzusc42p54
Learning Pose Specific Representations by Predicting Different Views
[article]
2018
arXiv
pre-print
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That is, given only the pose and shape parameters of a hand, the hand's appearance from any viewpoint can be approximated. ...
Moreover, when training the proposed method jointly with labeled and unlabeled data, it consistently surpasses the performance of its fully supervised counterpart, while reducing the amount of needed labeled ...
the dataset, and Anna Micheler-Hofer, Stefan Ainetter and Florian Ziessler for manually labeling hand poses. ...
arXiv:1804.03390v2
fatcat:3fxeyrxgbfbwtd2nu2gon7cuzy
Recent Advances in Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective
[article]
2021
arXiv
pre-print
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We believe this survey will provide the readers with a deep and insightful understanding of monocular human pose estimation. ...
Estimation of the human pose from a monocular camera has been an emerging research topic in the computer vision community with many applications. ...
Moreover, with the rapid development of 3D pose and shape estimation, it is necessary to have a deeper survey on the human pose estimation from 2D to 3D. ...
arXiv:2104.11536v1
fatcat:tdag2jq2vjdrjekwukm5nu7l6a
Survey on depth and RGB image-based 3D hand shape and pose estimation
2021
Virtual Reality & Intelligent Hardware
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hand shape and pose estimation. ...
In this study, we present a comprehensive survey of state-of-the-art 3D hand shape and pose estimation approaches using RGB-D cameras. ...
Discriminative approaches: Weakly-supervised and semi-supervised learning The increased number of real-world datasets with complete 3D annotations has been attributed to the fast growth of 3D hand shape ...
doi:10.1016/j.vrih.2021.05.002
fatcat:4tbhftt3ira6fporaqlscqhsse
Appearance Consensus Driven Self-Supervised Human Mesh Recovery
[article]
2020
arXiv
pre-print
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We achieve state-of-the-art results on the standard model-based 3D pose estimation benchmarks at comparable supervision levels. ...
We present a self-supervised human mesh recovery framework to infer human pose and shape from monocular images in the absence of any paired supervision. ...
Note that at test time, we perform single image inference to estimate 3D human pose and shape. ...
arXiv:2008.01341v1
fatcat:jyqhw3pwjrcxxpozwetd36r6ay
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