Results 11 to 20 of about 371,934 (280)
IEEE Access, 2020 Human pose estimation localizes body keypoints to accurately recognizing the postures of individuals given an image. This step is a crucial prerequisite to multiple tasks of computer vision which include human action recognition, human tracking, human ...
Tewodros Legesse Munea +5 more
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Heuristic weakly supervised 3D human pose estimation
Computational Visual MediaMonocular 3D human pose estimation from RGB images has attracted significant attention in recent years. However, recent models depend on supervised training with 3D pose ground truth data or known pose priors for their target domains. 3D pose data is typically collected with motion capture devices, severely limiting their applicability.
Shuangjun Liu +2 more
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PosturePose: Optimized Posture Analysis for Semi-Supervised Monocular 3D Human Pose Estimation
Sensors, 2023 One motivation for studying semi-supervised techniques for human pose estimation is to compensate for the lack of variety in curated 3D human pose datasets by combining labeled 3D pose data with readily available unlabeled video data—effectively ...
Lawrence Amadi, Gady Agam
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Location-Free Human Pose Estimation
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 Human pose estimation (HPE) usually requires large-scale training data to reach high performance. However, it is rather time-consuming to collect high-quality and fine-grained annotations for human body. To alleviate this issue, we revisit HPE and propose a location-free framework without supervision of keypoint locations. We reformulate the regression-
Xu, Xixia +4 more
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Adapted human pose: monocular 3D human pose estimation with zero real 3D pose data [PDF]
Applied Intelligence, 2022 The ultimate goal for an inference model is to be robust and functional in real life applications. However, training vs. test data domain gaps often negatively affect model performance. This issue is especially critical for the monocular 3D human pose estimation problem, in which 3D human data is often collected in a controlled lab setting.
Shuangjun Liu +2 more
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Research Progress of Two-Dimensional Human Pose Estimation Based on Deep Learning [PDF]
Jisuanji gongcheng, 2021 The two-dimensional Human Pose Estimation(HPE) methods based on deep learning have attracted much attention for their application potential.The methods work by constructing a specific neural network architecture,and processing the extracted feature ...
LIU Yong, LI Jie, ZHANG Jianlin, XU Zhiyong, WEI Yuxing
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Recurrent Human Pose Estimation [PDF]
2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017), 2017 We propose a novel ConvNet model for predicting 2D human body poses in an image. The model regresses a heatmap representation for each body keypoint, and is able to learn and represent both the part appearances and the context of the part configuration.
Belagiannis, V, Zisserman, A
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Orientation Keypoints for 6D Human Pose Estimation [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 Most realtime human pose estimation approaches are based on detecting joint positions. Using the detected joint positions, the yaw and pitch of the limbs can be computed. However, the roll along the limb, which is critical for application such as sports analysis and computer animation, cannot be computed as this axis of rotation remains unobserved.
Martin Fisch, Ronald Clark
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Personalizing Human Video Pose Estimation [PDF]
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 We propose a personalized ConvNet pose estimator that automatically adapts itself to the uniqueness of a person's appearance to improve pose estimation in long videos. We make the following contributions: (i) we show that given a few high-precision pose annotations, e.g.
Charles, J +4 more
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THANet: Transferring Human Pose Estimation to Animal Pose Estimation
Electronics, 2023 Animal pose estimation (APE) boosts the understanding of animal behaviors. Recent vision-based APE has attracted extensive attention due to the advantages of contactless and sensorless applications. One of the main challenges in APE is the lack of high-quality keypoint annotations for different animal species since manually annotating the animal ...
Jincheng Liao +3 more
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