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MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network [article]

Muhammed Kocabas, Salih Karagoz, Emre Akbas
2018 arXiv   pre-print
In this paper, we present MultiPoseNet, a novel bottom-up multi-person pose estimation architecture that combines a multi-task model with a novel assignment method.  ...  MultiPoseNet can jointly handle person detection, keypoint detection, person segmentation and pose estimation problems.  ...  Multi Person Pose Estimation Bottom-up Multi person pose estimation solutions branched out as bottomup and top-down methods.  ... 
arXiv:1807.04067v1 fatcat:kazintu5fjajtdq24eypr7m5dm

MultiPoseNet: Fast Multi-Person Pose Estimation Using Pose Residual Network [chapter]

Muhammed Kocabas, Salih Karagoz, Emre Akbas
2018 Lecture Notes in Computer Science  
In this paper, we present MultiPoseNet, a novel bottom-up multi-person pose estimation architecture that combines a multi-task model with a novel assignment method.  ...  MultiPoseNet can jointly handle person detection, person segmentation and pose estimation problems.  ...  We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Tesla K40 GPU used for this research.  ... 
doi:10.1007/978-3-030-01252-6_26 fatcat:4iunbknmarbf7imstj4yupxf7m

Multi-Person Pose Estimation Using an Orientation and Occlusion Aware Deep Learning Network

Yanlei Gu, Huiyang Zhang, Shunsuke Kamijo
2020 Sensors  
This paper proposes a novel multi-task framework for the multi-person pose estimation.  ...  In order to further improve the performance of the multi-person pose estimation, this paper proposes to organize the different information in serial multi-task models instead of the widely used parallel  ...  propose to estimate the multi-person pose using a pose residual network [28] . The proposed system is named as the MultiPoseNet and has real time performance.  ... 
doi:10.3390/s20061593 pmid:32178461 pmcid:PMC7146407 fatcat:qb6eh2xhonfi7as7egl47x7yze

SIMPLE: SIngle-network with Mimicking and Point Learning for Bottom-up Human Pose Estimation [article]

Jiabin Zhang, Zheng Zhu, Jiwen Lu, Junjie Huang, Guan Huang, Jie Zhou
2021 arXiv   pre-print
To make a better trade-off between accuracy and efficiency, we propose a novel multi-person pose estimation framework, SIngle-network with Mimicking and Point Learning for Bottom-up Human Pose Estimation  ...  The practical application requests both accuracy and efficiency on multi-person pose estimation algorithms.  ...  Conclusion In this paper, we propose SIMPLE, a novel multi-person pose estimation framework.  ... 
arXiv:2104.02486v2 fatcat:635i7w5skbb7rljmyaokvwme3u

Deep Multi-Task Networks For Occluded Pedestrian Pose Estimation [article]

Arindam Das, Sudip Das, Ganesh Sistu, Jonathan Horgan, Ujjwal Bhattacharya, Edward Jones, Martin Glavin, Ciarán Eising
2022 arXiv   pre-print
Most of the existing works on pedestrian pose estimation do not consider estimating the pose of an occluded pedestrians, as the annotations of the occluded parts are not available in relevant automotive  ...  Thereafter, an encoder learns pose specific features using an unsupervised instance-level domain adaptation method for the pedestrian instances from both distributions.  ...  ., and Akbas, E. (2018).Multiposenet: Fast multi-person pose estimation using pose residual network.In ECCV.[Lin et al., 2014] Lin, T.-Y., Maire, M., Belongie, S., Hays, J.,  ... 
arXiv:2206.07510v1 fatcat:jzsxq6nc75c5bckhzwqftvlbde

Recent Advances of Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective

Wu Liu, Tao Mei
2022 ACM Computing Surveys  
Furthermore, we analyze the solutions for challenging cases, such as the lack of data, the inherent ambiguity between 2D and 3D, and the complex multi-person scenarios.  ...  Especially, we provide insightful analyses for the intrinsic connections and methods evolution from 2D to 3D pose estimation.  ...  With the rapidly-developed application need for multiple-person pose estimation, small and fast networks attract more and more attention.  ... 
doi:10.1145/3524497 fatcat:4pbvntngrnfp7lqhcpjmy7p2fq

Recent Advances in Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective [article]

Wu Liu, Qian Bao, Yu Sun, Tao Mei
2021 arXiv   pre-print
summarizing the differences and connections between these approaches, we further analyze the solutions for challenging cases, such as the lack of data, the inherent ambiguity between 2D and 3D, and the complex multi-person  ...  We believe this survey will provide the readers with a deep and insightful understanding of monocular human pose estimation.  ...  MultiPoseNet proposes a Pose Residual Network (PRN) to assign the predicted keypoints and the detected person bounding boxes by measuring their locations' similarity.  ... 
arXiv:2104.11536v1 fatcat:tdag2jq2vjdrjekwukm5nu7l6a

Multi-Person Pose Estimation with Enhanced Feature Aggregation and Selection [article]

Xixia Xu, Qi Zou, Xue Lin
2020 arXiv   pre-print
We propose a novel Enhanced Feature Aggregation and Selection network (EFASNet) for multi-person 2D human pose estimation.  ...  More specifically, a Feature Aggregation and Selection Module (FASM), which constructs hierarchical multi-scale feature aggregation and makes the aggregated features discriminative, is proposed to get  ...  MultiPoseNet [22] jointly localizes the human detection and multi-person pose estimation, which designs a pose residual network to receive keypoints and person detections and obtain accurate estimation  ... 
arXiv:2003.10238v1 fatcat:uwdgvyg65be5lozplyu4hgzjli

Multitask Network for Joint Object Detection, Semantic Segmentation and Human Pose Estimation in Vehicle Occupancy Monitoring [article]

Nikolas Ebert, Patrick Mangat, Oliver Wasenmüller
2022 arXiv   pre-print
In the state-of-the-art, single or multiple deep neural networks are used for either object recognition, semantic segmentation, or human pose estimation.  ...  In contrast, we propose our Multitask Detection, Segmentation and Pose Estimation Network (MDSP) -- the first multitask network solving all these three tasks jointly in the area of occupancy monitoring  ...  As illustrated in Figure 1 , we perform a joint multi-class object detection and semantic segmentation extended with a 2D multi-person pose estimation. In contrast a b b c Fig. 1 .  ... 
arXiv:2205.01515v1 fatcat:pjhn5cy7izaxdhqgv44l7ubfuu

Deep Learning-Based Human Pose Estimation: A Survey [article]

Ce Zheng and Wenhan Wu and Chen Chen and Taojiannan Yang and Sijie Zhu and Ju Shen and Nasser Kehtarnavaz and Mubarak Shah
2022 arXiv   pre-print
Furthermore, 2D and 3D human pose estimation datasets and evaluation metrics are included.  ...  Human pose estimation aims to locate the human body parts and build human body representation (e.g., body skeleton) from input data such as images and videos.  ...  In the following, we review deep learning-based 2D HPE methods with respect to single-person and multi-person scenarios. 2D single-person pose estimation 2D single-person pose estimation is used to localize  ... 
arXiv:2012.13392v4 fatcat:ypnqtq3sbncr5fuujif2dhqwji

A Fall Detection Network by 2D/3D Spatio-temporal Joint Models with Tensor Compression on Edge

Shuwei Li, Changhai Man, Ao Shen, Ziyi Guan, Wei Mao, Shaobo Luo, Rumin Zhang, Hao Yu
2022 ACM Transactions on Embedded Computing Systems  
We also introduce the increasingly mature RGB-D camera and propose 3d pose estimation network to further improve the accuracy of the system.  ...  fall detection in the elderly by using Convolutional Neural Network (CNN) and 3D-CNN, respectively.  ...  The 2D pose estimation part mainly uses the Openpose network structure. In this part, pose estimation is carried out in 1+n stages, and each stage is divided into two branches.  ... 
doi:10.1145/3531004 fatcat:7lwqa7bze5b5vki24gjpza47la

GSTO: Gated Scale-Transfer Operation for Multi-Scale Feature Learning in Pixel Labeling [article]

Zhuoying Wang and Yongtao Wang and Zhi Tang and Yangyan Li and Ying Chen and Haibin Ling and Weisi Lin
2020 arXiv   pre-print
In particular, by plugging GSTO into HRNet, we get a more powerful backbone (namely GSTO-HRNet) for pixel labeling, and it achieves new state-of-the-art results on the COCO benchmark for human pose estimation  ...  Both forms of GSTO are lightweight and plug-and-play, which can be flexibly integrated into networks or modules for learning better multi-scale features.  ...  Mul- [4] Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, tiposenet: Fast multi-person pose estimation using pose Kevin Murphy, and Alan L Yuille.  ... 
arXiv:2005.13363v2 fatcat:qsvle64qojfmvjjinb4t3rkyme

Fast and Lightweight Human Pose Estimation

Haopan Ren, Wenming Wang, Kaixiang Zhang, Dejian Wei, Yanyan Gao, Yue Sun
2021 IEEE Access  
We pay attention to single-person pose estimation, which is the basis of relevant vision tasks, such as multi-person pose estimation, video-based pose estimation, and pose tracking.  ...  FAST AND LIGHTWEIGHT NETWORK The simple and widely adopted pipeline [10] , [13] to estimate human pose consists of a stem decreasing the size of input images, the main body learning the features of  ... 
doi:10.1109/access.2021.3069102 fatcat:j2suqvcmobchrft63uzd5ru77u

LandmarkNet: a 2D digital radiograph landmark estimator for registration

Zhen Wang, Cong Liu, Longhua Ma
2020 BMC Medical Informatics and Decision Making  
The method applies the idea of Feature Pyramid Network (FPN) twice to merge the cross-scale and cross-layer features for feature extraction and landmark estimation successively.  ...  The network finally produces heatmap to display the approximate location of landmarks and we obtain accurate position estimation after non-maximum suppression (NMS) processing.  ...  Pose estimation is usually also considered as a detection problem, and the output is heatmap [14] . The Stacked Hourglass Networks for pose estimation proposed by Newell et al.  ... 
doi:10.1186/s12911-020-01164-4 pmid:32693827 fatcat:vy4or32ejrgphmka7rrlxgqc3i

Towards accurate multi-person pose estimation in the wild [article]

Insafutdinov Eldar, Universität Des Saarlandes
2021
The first contribution is a multi-person pose estimation algorithm based on the bottom-up detection-by-grouping paradigm.  ...  Articulated human pose tracking requires tracking multiple persons in the video sequence while simultaneously estimating full body poses.  ...  Our new benchmark encompasses three tasks focusing on i) single-frame multi-person pose estimation, ii) multi-person pose estimation in videos, and iii) multi-person articulated tracking.  ... 
doi:10.22028/d291-33512 fatcat:ioyobbty6rh7pifk5u5muj7msm