Results 21 to 30 of about 6,005,844 (276)
Dual-Hand Motion Capture by Using Biological Inspiration for Bionic Bimanual Robot Teleoperation
Cyborg and Bionic Systems, 2023 Bionic bimanual robot teleoperation can transfer the grasping and manipulation skills of human dual hands to the bionic bimanual robots to realize natural and flexible manipulation.
Qing Gao +3 more
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3D Hand Shape and Pose Estimation [PDF]
, 2022 We study the problem of 3D hand shape and pose estimation from monocular RGB images. Recent studies have shown that single-view 3D hand pose estimation is challenging due to depth ambiguity, environmental conditions, object-occlusion, and self-occlusion.
Kaviani, Samira
core +1 more source
Semi-Supervised 3D Hand-Object Pose Estimation Via Pose Dictionary Learning [PDF]
2021 IEEE International Conference on Image Processing (ICIP), 2021 3D hand-object pose estimation is an important issue to understand the interaction between human and environment. Current hand-object pose estimation methods require detailed 3D labels, which are expensive and labor-intensive. To tackle the problem of data collection, we propose a semi-supervised 3D hand-object pose estimation method with two key ...
Zida Cheng, Siheng Chen, Ya Zhang 0002
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Coarse-to-Fine Hand–Object Pose Estimation with Interaction-Aware Graph Convolutional Network
Sensors, 2021 The analysis of hand–object poses from RGB images is important for understanding and imitating human behavior and acts as a key factor in various applications.
Maomao Zhang +3 more
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Dynamic Iterative Refinement for Efficient 3D Hand Pose Estimation [PDF]
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2022 While hand pose estimation is a critical component of most interactive extended reality and gesture recognition systems, contemporary approaches are not optimized for computational and memory efficiency. In this paper, we propose a tiny deep neural network of which partial layers are recursively exploited for refining its previous estimations.
John Yang 0001 +4 more
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Semi-Supervised Joint Learning for Hand Gesture Recognition from a Single Color Image
Sensors, 2021 Hand gesture recognition and hand pose estimation are two closely correlated tasks. In this paper, we propose a deep-learning based approach which jointly learns an intermediate level shared feature for these two tasks, so that the hand gesture ...
Chi Xu, Yunkai Jiang, Jun Zhou, Yi Liu
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3D hand pose and shape estimation from monocular RGB via efficient 2D cues
Computational Visual Media, 2023 Estimating 3D hand shape from a single-view RGB image is important for many applications. However, the diversity of hand shapes and postures, depth ambiguity, and occlusion may result in pose errors and noisy hand meshes.
Fenghao Zhang +5 more
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Residual Attention Regression for 3D Hand Pose Estimation [PDF]
, 2019 3D hand pose estimation is an important and challenging task for virtual reality and human-computer interaction. In this paper, we propose a simple and effective residual attention regression model for accurate 3D hand pose estimation from a depth image. The model is trained in an end-to-end fashion.
Jing Li 0027, Long Zhang, Zhaojie Ju
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Aligning Latent Spaces for 3D Hand Pose Estimation [PDF]
2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019 Hand pose estimation from monocular RGB inputs is a highly challenging task. Many previous works for monocular settings only used RGB information for training despite the availability of corresponding data in other modalities such as depth maps. In this work, we propose to learn a joint latent representation that leverages other modalities as weak ...
Yang, Linlin +3 more
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Dense 3D Regression for Hand Pose Estimation
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 We present a simple and effective method for 3D hand pose estimation from a single depth frame. As opposed to previous state-of-the-art methods based on holistic 3D regression, our method works on dense pixel-wise estimation. This is achieved by careful design choices in pose parameterization, which leverages both 2D and 3D properties of depth map ...
Chengde Wan +3 more
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