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HOnnotate: A method for 3D Annotation of Hand and Object Poses
[article]
2020
arXiv
pre-print
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We propose a method for annotating images of a hand manipulating an object with the 3D poses of both the hand and the object, together with a dataset created using this method. ...
With this method, we created HO-3D, the first markerless dataset of color images with 3D annotations for both the hand and object. ...
object from our proposed dataset, HO-3D. 10 objects of the YCB dataset [70] that we use for our dataset HO-3D. ...
arXiv:1907.01481v6
fatcat:cgqanwhwp5ch3jqvnnyhqwru7y
HOnnotate: A Method for 3D Annotation of Hand and Object Poses
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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We propose a method for annotating images of a hand manipulating an object with the 3D poses of both the hand and the object, together with a dataset created using this method. ...
With this method, we created HO-3D, the first markerless dataset of color images with 3D annotations for both the hand and object. ...
As illustrated in Fig. 1 and Table 1 , our HO-3D dataset is the first markerless dataset providing both 3D hand joints and 3D object pose annotations for real images, while the hand and the object are ...
doi:10.1109/cvpr42600.2020.00326
dblp:conf/cvpr/HampaliROL20
fatcat:3vqj2f5lvfbyjgcncygjepsbzu
Efficient Annotation and Learning for 3D Hand Pose Estimation: A Survey
[article]
2022
arXiv
pre-print
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In 3D hand pose estimation, collecting 3D hand pose annotation is a key step in developing hand pose estimators and their applications, such as video understanding, AR/VR, and robotics. ...
In particular, we study recent approaches for 3D hand pose annotation and learning methods with limited annotated data. ...
YouTube3DHands [27] used the MANO model to fit estimated 2D hand poses in YouTube videos. HO-3D [19] and H2O [28] attempted to jointly annotate 3D hand and object poses. ...
arXiv:2206.02257v2
fatcat:6qaf2sieaffurl3z7bfdxpwcu4
Joint-Aware Regression: Rethinking Regression-Based Method for 3D Hand Pose Estimation
2021
British Machine Vision Conference
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3D hand pose estimation approaches can be divided into two categories, including regression-based methods and detection-based methods. ...
Our approach outperforms state-of-the-art methods on four public benchmarks, including FreiHAND, HO-3D, RHD, and STB. ...
We evaluate JAR on four publicly available 3D hand pose datasets, including FreiHAND [38] , HO-3D [11] , RHD [37] , and STB [36] . ...
dblp:conf/bmvc/ZhengRSW0L21
fatcat:4qpq4yat55h3xfuvckevjo7rta
Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction
[article]
2020
arXiv
pre-print
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2020 pre-print arXiv:2003.13764v1 fatcat:wmr674bphjdppojrh4vzhfdpda
We study how well different types of approaches generalise in the task of 3D hand pose estimation under single hand scenarios and hand-object interaction. ...
To address these issues, we designed a public challenge (HANDS'19) to evaluate the abilities of current 3D hand pose estimators (HPEs) to interpolate and extrapolate the poses of a training set. ...
Task 3: RGB-Based 3D Hand Pose Estimation while Interacting with Objects: This task builds on the HO-3D [9] dataset. ...
arXiv:2003.13764v2
fatcat:kycs43pstbffbnitvcangzg4gy
Consistent 3D Hand Reconstruction in Video via self-supervised Learning
[article]
2022
arXiv
pre-print
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We present a method for reconstructing accurate and consistent 3D hands from a monocular video. ...
Thus we propose S^2HAND, a self-supervised 3D hand reconstruction model, that can jointly estimate pose, shape, texture, and the camera viewpoint from a single RGB input through the supervision of easily ...
The HO-3D dataset [75] collects color images of a hand interacting with an object. ...
arXiv:2201.09548v1
fatcat:sv6463vtzndkdlv2jhsq2itpim
Survey on depth and RGB image-based 3D hand shape and pose estimation
2021
Virtual Reality & Intelligent Hardware
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In this study, we present a comprehensive survey of state-of-the-art 3D hand shape and pose estimation approaches using RGB-D cameras. ...
hand shape and pose estimation. ...
HO-3D dataset This dataset is a recently published hand-object interaction dataset that contains sequences with hands interacting with objects from a third-person point of view. ...
doi:10.1016/j.vrih.2021.05.002
fatcat:4tbhftt3ira6fporaqlscqhsse
PeCLR: Self-Supervised 3D Hand Pose Estimation from monocular RGB via Equivariant Contrastive Learning
[article]
2022
arXiv
pre-print
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Encouraged by the success of contrastive learning on image classification tasks, we propose a new self-supervised method for the structured regression task of 3D hand pose estimation. ...
For 3D hand pose estimation, it too is desirable to have invariance to appearance transformation such as color jitter. ...
We are grateful to Thomas Langerak for the aid in figure creation and Marcel Bühler for helpful discussions and comments. ...
arXiv:2106.05953v5
fatcat:aulbmneizba4th6lafeetk4rf4
A Survey on 3D Hand Skeleton and Pose Estimation by Convolutional Neural Network
2020
Advances in Science, Technology and Engineering Systems
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The estimation process followed two directions: (a) using the 2D CNNs to predict 2D hand pose, and (b) using the 3D synthetic dataset (3D annotations/ ground truth) to regress 3D hand pose or using the ...
collection technologies, datasets of 3D hand pose estimation. ...
The title is "Using the Lie algebra, Lie group to improve the skeleton hand presentation". ...
doi:10.25046/aj050418
fatcat:tzpjnmpwtjbh7m6ld3nucyvxia
Recent Advances in 3D Object and Hand Pose Estimation
[article]
2020
arXiv
pre-print
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3D object and hand pose estimation have huge potentials for Augmented Reality, to enable tangible interfaces, natural interfaces, and blurring the boundaries between the real and virtual worlds. ...
In this chapter, we present the recent developments for 3D object and hand pose estimation using cameras, and discuss their abilities and limitations and the possible future development of the field. ...
The annotations are only in 2D but can still be useful for multi-view pose estimation.
Datasets for Object and Hand Pose Estimation GANerated Hand Dataset. ...
arXiv:2006.05927v1
fatcat:ttroutu7ljgzvf4joqexpz6rai
Visual Methods for Sign Language Recognition: A Modality-Based Review
[article]
2020
arXiv
pre-print
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In each section, we will detail and compare the related datasets, approaches then distinguish the still open contribution paths suitable for the creation of sign language related services. ...
They are then prone to creating interactive services for the deaf and hearing-impaired communities. A population that is expected to grow considerably in the years to come. ...
and additional 45 action labels, and (iii) HO-3D offering 16 joint positions and 3 object models for the challenging task of coupled hands and objects pose estimation. ...
arXiv:2009.10370v1
fatcat:jkqtzid6qndhnijs5axhfom4ia
THE TWENTY NINETH PROFESSOR CHIN FUNG KEE MEMORIAL LECTURE
2020
The Journal of The Institution of Engineers, Malaysia
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For example, the 1996 Keningau debris flow in Sabah recorded the highest level of fatality (>300 deaths) for a single landslide in Malaysia. ...
systems approach to manage landslide risk holistically, championed the development of novel methodologies for landslide risk assessment, and pioneered new design approaches for landslide prevention and ...
KEN HO 3D measurements. ...
doi:10.54552/v80i2.67
fatcat:kyhxmp5ftfechgdrh4sqcfd6vu
GRAB: A Dataset of Whole-Body Human Grasping of Objects
[article]
2020
pre-print
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Training computers to understand, model, and synthesize human grasping requires a rich dataset containing complex 3D object shapes, detailed contact information, hand pose and shape, and the 3D body motion ...
Given MoCap markers, we fit the full 3D body shape and pose, including the articulated face and hands, as well as the 3D object pose. ...
Landry (ML) for the MoCap facility. We thank F. Mattioni, D. Hieber, and A. Valis for MoCap cleaning. We thank ML and T. Alexiadis for trial coordination, MH and F. Grimminger for 3D printing, V. ...
doi:10.1007/978-3-030-58548-8_34
arXiv:2008.11200v1
fatcat:uh6it7agdvhhdokekfjgbjk3yq
Hybrid Architectures for Object Pose and Velocity Tracking at the Intersection of Kalman Filtering and Machine Learning
2022
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tasks, such as object pose estimation and tracking. ...
The proposed methods exhibit interesting performance on computer vision benchmarks and robotic tasks, e.g. using object pose estimation for grasp planning purposes. ...
Lorenzo Natale for giving me the ...
doi:10.15167/piga-nicola-agostino_phd2022-04-13
fatcat:w4l2lpkdong4dm6hldb3qo43xm
Robotic hand/eye coordination system in an assisted technology context
2017
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This research focuses on hand/eye coordination tasks. One critical information required in the planning of a hand/eye coordination task is accurate knowledge of a target object's pose and shape. ...
Although a stereo method has been avoided as a 3D sensing method for robotic grasping, particularly in a domestic setting, due to its noisiness and relative inaccuracy, the proposed box modeling method ...
Finally, I also thank to Monash University for giving me a scholarship to fund my entire study to pursue a higher degree. ...
doi:10.4225/03/589021b9860d5
fatcat:mi3tlfikzrbt5f5elskx7pcqii