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A survey on 3D hand pose estimation: Cameras, methods, and datasets
R Li, Z Liu, J Tan - Pattern Recognition, 2019 - Elsevier
Abstract 3D Hand pose estimation has received an increasing amount of attention,
especially since consumer depth cameras came onto the market in 2010. Although …
especially since consumer depth cameras came onto the market in 2010. Although …
Handvoxnet: Deep voxel-based network for 3d hand shape and pose estimation from a single depth map
Abstract 3D hand shape and pose estimation from a single depth map is a new and
challenging computer vision problem with many applications. The state-of-the-art methods …
challenging computer vision problem with many applications. The state-of-the-art methods …
Shpr-net: Deep semantic hand pose regression from point clouds
3-D hand pose estimation is an essential problem for human-computer interaction. Most of
the existing depth-based hand pose estimation methods consume 2-D depth map or 3-D …
the existing depth-based hand pose estimation methods consume 2-D depth map or 3-D …
Deephps: End-to-end estimation of 3d hand pose and shape by learning from synthetic depth
Articulated hand pose and shape estimation is an important problem for vision-based
applications such as augmented reality and animation. In contrast to the existing methods …
applications such as augmented reality and animation. In contrast to the existing methods …
[HTML][HTML] A comprehensive study on deep learning-based 3D hand pose estimation methods
The field of 3D hand pose estimation has been gaining a lot of attention recently, due to its
significance in several applications that require human-computer interaction (HCI). The …
significance in several applications that require human-computer interaction (HCI). The …
Handvoxnet++: 3d hand shape and pose estimation using voxel-based neural networks
3D hand shape and pose estimation from a single depth map is a new and challenging
computer vision problem with many applications. Existing methods addressing it directly …
computer vision problem with many applications. Existing methods addressing it directly …
DeepAirSig: End-to-end deep learning based in-air signature verification
In-air signature verification is vital for biometric user identification in contact-less mode. The
state-of-the-art methods use heuristics for signature acquisition, and provide insufficient data …
state-of-the-art methods use heuristics for signature acquisition, and provide insufficient data …
Structure-aware 3d hand pose regression from a single depth image
Hand pose tracking in 3D is an essential task for many virtual reality (VR) applications such
as games and manipulating virtual objects with bare hands. CNN-based learning methods …
as games and manipulating virtual objects with bare hands. CNN-based learning methods …
3dairsig: A framework for enabling in-air signatures using a multi-modal depth sensor
In-air signature is a new modality which is essential for user authentication and access
control in noncontact mode and has been actively studied in recent years. However, it has …
control in noncontact mode and has been actively studied in recent years. However, it has …
An end-to-end framework for unconstrained monocular 3D hand pose estimation
S Sharma, S Huang - Pattern Recognition, 2021 - Elsevier
This work addresses the challenging problem of unconstrained 3D hand pose estimation
using monocular RGB images. Most of the existing approaches assume some prior …
using monocular RGB images. Most of the existing approaches assume some prior …