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2D/3D Pose Estimation and Action Recognition using Multitask Deep Learning
[article]
2018
arXiv
pre-print
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In this work, we propose a multitask framework for jointly 2D and 3D pose estimation from still images and human action recognition from video sequences. ...
Action recognition and human pose estimation are closely related but both problems are generally handled as distinct tasks in the literature. ...
Figure 1 . 1 The proposed multitask approach for pose estimation and action recognition. Our method provides 2D/3D pose estimation from single images or frame sequences. ...
arXiv:1802.09232v2
fatcat:qwactqazanccrb6toshqo7mvxq
2D/3D Pose Estimation and Action Recognition Using Multitask Deep Learning
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
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In this work, we propose a multitask framework for jointly 2D and 3D pose estimation from still images and human action recognition from video sequences. ...
Action recognition and human pose estimation are closely related but both problems are generally handled as distinct tasks in the literature. ...
The proposed multitask approach for pose estimation and action recognition. Our method provides 2D/3D pose estimation from single images or frame sequences. ...
doi:10.1109/cvpr.2018.00539
dblp:conf/cvpr/LuvizonPT18
fatcat:cnjhs4rie5ea3fm3vr27ltk4aa
A Unified Deep Framework for Joint 3D Pose Estimation and Action Recognition from a Single RGB Camera
2020
Sensors
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We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from RGB sensors using simple cameras. The approach proceeds along two stages. ...
In particular, the experimental results show that by using a monocular RGB sensor, we can develop a 3D pose estimation and human action recognition approach that reaches the performance of RGB-depth sensors ...
There are four hypotheses that motivate us to build a deep learning framework for human action recognition from 3D poses. ...
doi:10.3390/s20071825
pmid:32218350
pmcid:PMC7180926
fatcat:ilbvk55rcvhx7k2wkvgdgu4fjm
Multi-task Deep Learning for Real-Time 3D Human Pose Estimation and Action Recognition
2020
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Human pose estimation and action recognition are related tasks since both problems are strongly dependent on the human body representation and analysis. ...
In this work, we propose a multi-task framework for jointly estimating 2D or 3D human poses from monocular color images and classifying human actions from video sequences. ...
ACKNOWLEDGMENTS This work was partially supported by the Brazilian National Council for Scientific and Technological Development (CNPq) -Grant 233342/2014-1. ...
doi:10.1109/tpami.2020.2976014
pmid:32091993
fatcat:47mkuvrc3nauxbmfqzksxsl2xa
Multi-task Deep Learning for Real-Time 3D Human Pose Estimation and Action Recognition
[article]
2019
arXiv
pre-print
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Human pose estimation and action recognition are related tasks since both problems are strongly dependent on the human body representation and analysis. ...
In this work, we propose a multi-task framework for jointly estimating 2D or 3D human poses from monocular color images and classifying human actions from video sequences. ...
Acknowledgment This work was partially supported by the Brazilian National Council for Scientific and Technological Development (CNPq) -Grant 233342/2014-1. ...
arXiv:1912.08077v1
fatcat:2kth5hzd55hvvipst44kc4442u
Recent Advances in Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective
[article]
2021
arXiv
pre-print
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Recently, benefited from the deep learning technologies, a significant amount of research efforts have greatly advanced the monocular human pose estimation both in 2D and 3D areas. ...
We believe this survey will provide the readers with a deep and insightful understanding of monocular human pose estimation. ...
[24] propose a multi-task framework for jointly 2D/3D pose estimation and human action recognition from video sequences. ...
arXiv:2104.11536v1
fatcat:tdag2jq2vjdrjekwukm5nu7l6a
Recent Advances of Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective
2022
ACM Computing Surveys
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Recently, benefiting from the deep learning technologies, a significant amount of research efforts have advanced the monocular human pose estimation both in 2D and 3D areas. ...
We believe this survey will provide the readers (researchers, engineers, developers, etc.) with a deep and insightful understanding of monocular human pose estimation. ...
[123] propose a multi-task framework for jointly 2D/3D pose estimation and human action recognition from video sequences. ...
doi:10.1145/3524497
fatcat:4pbvntngrnfp7lqhcpjmy7p2fq
Temporal Hockey Action Recognition via Pose and Optical Flows
[article]
2018
arXiv
pre-print
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A novel publicly available dataset named HARPET (Hockey Action Recognition Pose Estimation, Temporal) was created, composed of sequences of annotated actions and pose of hockey players including their ...
Third, pose and optical flow streams are fused and passed to fully-connected layers to estimate the hockey player's action. ...
[14] also use action recognition for 3D pose estimation. Luvizon et al. [31] use a multitask framework for joint action recognition and 2D/3D pose estimation. Wang et al. ...
arXiv:1812.09533v1
fatcat:yc3vxgo2wvbljfa7wf46i7sd4a
Temporal Hockey Action Recognition via Pose and Optical Flows
2019
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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(3) For pose estimation, a bigger and more general dataset, MSCOCO, is successfully used for transfer learning to a smaller and more specific dataset, HARPET, achieving a PCKh of 87%. ...
A novel publicly available dataset named HARPET (Hockey Action Recognition Pose Estimation, Temporal) was created, composed of sequences of annotated actions and pose of hockey players including their ...
[14] also use action recognition for 3D pose estimation. Luvizon et al. [32] use a multitask framework for joint action recognition and 2D/3D pose estimation. Wang et al. ...
doi:10.1109/cvprw.2019.00310
dblp:conf/cvpr/CaiNVCZ19
fatcat:oyjmp3fnq5asviu3p4yslxt4wy
Action Machine: Rethinking Action Recognition in Trimmed Videos
[article]
2018
arXiv
pre-print
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Action Machine can benefit from the multi-task training of action recognition and pose estimation, the fusion of predictions from RGB images and poses. ...
It extends the Inflated 3D ConvNet (I3D) by adding a branch for human pose estimation and a 2D CNN for pose-based action recognition, being fast to train and test. ...
Thus, action recognition in videos can be naturally formulated as a multi-task learning problem including RGB-based action recognition, pose estimation and pose-based action recognition. ...
arXiv:1812.05770v2
fatcat:r3d32bxhwrgprbuuvm6cntowmq
Mimetics: Towards Understanding Human Actions Out of Context
[article]
2021
arXiv
pre-print
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to 3D action recognition methods. ...
In this paper, we propose to benchmark action recognition methods in such absence of context and introduce a novel dataset, Mimetics, consisting of mimed actions for a subset of 50 classes from the Kinetics ...
In other words, we transfer the features learned for 2D-3D pose estimation to action recognition: they typically contain information about the human poses without explicitly representing them as body keypoint ...
arXiv:1912.07249v3
fatcat:wio3wwk7indztg737ls5hysfmi
Deep Facial Expression Recognition: A Survey
[article]
2018
arXiv
pre-print
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With the transition of facial expression recognition (FER) from laboratory-controlled to challenging in-the-wild conditions and the recent success of deep learning techniques in various fields, deep neural ...
Recent deep FER systems generally focus on two important issues: overfitting caused by a lack of sufficient training data and expression-unrelated variations, such as illumination, head pose and identity ...
[224] proposed a deep fusion CNN (DF-CNN) to explore multi-modal 2D+3D FER. ...
arXiv:1804.08348v2
fatcat:katpvrizybha5bgy6bepfi3xpe
Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation
[article]
2021
arXiv
pre-print
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Various deep learning techniques have been proposed to solve the single-view 2D-to-3D pose estimation problem. ...
We further apply the proposed technique on the skeleton-based action recognition task and also achieve state-of-the-art performance. ...
using
multitask deep learning. ...
arXiv:2108.07181v2
fatcat:4agxj3njkngqzfny4oqagbhhkq
SportsCap: Monocular 3D Human Motion Capture and Fine-grained Understanding in Challenging Sports Videos
[article]
2021
arXiv
pre-print
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In this paper, we propose SportsCap -- the first approach for simultaneously capturing 3D human motions and understanding fine-grained actions from monocular challenging sports video input. ...
mapping block to assemble various correlated action attributes into a high-level action label for the overall detailed understanding of the whole sequence, so as to enable various applications like action ...
Acknowledgements This work was supported by NSFC programs (61 976138, 61977047), the National Key Research and Development Program (2018YFB2100500), STCSM (2015F0203-000-06) and SHMEC (2019-01-07-00-01 ...
arXiv:2104.11452v4
fatcat:kq3q5vs2ajdnjf2y43apoi75hm
Video Violence Recognition and Localization Using a Semi-Supervised Hard Attention Model
[article]
2022
arXiv
pre-print
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A model's accuracy is improved by removing redundant data and focusing on useful visual information in a higher resolution. ...
Using hard attention, the essential regions of videos are identified and separated from the non-informative parts of the data. ...
., & Tabia, H. (2018). 2d/3d pose estimation and action recognition using multitask deep learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 5137-5146). ...
arXiv:2202.02212v4
fatcat:roum46ecdbhnti4ui5zs5y53j4
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