Filters








14,973 Hits in 4.7 sec

2021 Index IEEE Transactions on Image Processing Vol. 30

2021 IEEE Transactions on Image Processing  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TIP 2021 5327-5338 Multi-Scale Spatial Attention-Guided Monocular Depth Estimation With Semantic Enhancement.  ...  ., +, TIP 2021 907-920 Robust and Efficient Graph Correspondence Transfer for Person Re-Identi-TIP 2021 2488-2500 Uncertainty Guided Multi-Scale Attention Network for Raindrop Removal From a Single Image  ... 
doi:10.1109/tip.2022.3142569 fatcat:z26yhwuecbgrnb2czhwjlf73qu

Pose-Guided Multi-Scale Structural Relationship Learning for Video-Based Pedestrian Re-Identification

Dan Wei, Xiaoqiang Hu, Ziyang Wang, Jianglin Shen, Hongjuan Ren
2021 IEEE Access  
The input of the graph convolutional network is a local region divided by a multi-scale method, and the output is a pose-guided multi-scale structural relationship feature.  ...  In this paper, a posture-guided multi-scale structural relationship learning pedestrian re-identification method is proposed.  ...  METHOD In this section, we introduce the proposed video person reidentification method for pose-guided multi-scale structural relationship learning(PMSRL).  ... 
doi:10.1109/access.2021.3062967 fatcat:rec42qjynbg7dhpbfvvwy7t3ja

Pose-Guided Multi-Granularity Attention Network for Text-Based Person Search [article]

Ya Jing, Chenyang Si, Junbo Wang, Wei Wang, Liang Wang, Tieniu Tan
2019 arXiv   pre-print
To exploit the multilevel corresponding visual contents, we propose a pose-guided multi-granularity attention network (PMA).  ...  Text-based person search aims to retrieve the corresponding person images in an image database by virtue of a describing sentence about the person, which poses great potential for various applications  ...  In this paper, we propose a pose-guided multi-granularity attention network to learn multilevel cross-modal relevances. Human Pose for Person Search.  ... 
arXiv:1809.08440v3 fatcat:rb33zfv645at3nfh7qu7vcjqvi

Pose-Guided Multi-Granularity Attention Network for Text-Based Person Search

Ya Jing, Chenyang Si, Junbo Wang, Wei Wang, Liang Wang, Tieniu Tan
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
To exploit the multilevel corresponding visual contents, we propose a pose-guided multi-granularity attention network (PMA).  ...  Text-based person search aims to retrieve the corresponding person images in an image database by virtue of a describing sentence about the person, which poses great potential for various applications  ...  In this paper, we propose a pose-guided multi-granularity attention network to learn multilevel cross-modal relevances. Human Pose for Person Search.  ... 
doi:10.1609/aaai.v34i07.6777 fatcat:e7o4adxewrb5ned33qnmjdisuq

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 6151-6163 Learning Recurrent 3D Attention for Video-Based Person Re-Identification.  ...  ., +, TIP 2020 7192-7202 One-Pass Multi-Task Networks With Cross-Task Guided Attention for Brain Tumor Segmentation.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

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
2D and 3D, and the complex multi-person scenarios.  ...  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.  ...  [151] develop a multi-stage convolution network to recurrently optimize the estimated 3D pose.  ... 
arXiv:2104.11536v1 fatcat:tdag2jq2vjdrjekwukm5nu7l6a

Pedestrian Attribute Recognition: A Survey [article]

Xiao Wang, Shaofei Zheng, Rui Yang, Bin Luo, Jin Tang
2019 arXiv   pre-print
Thirdly, we analyse the concept of multi-task learning and multi-label learning, and also explain the relations between these two learning algorithms and pedestrian attribute recognition.  ...  The goal of this paper is to review existing works using traditional methods or based on deep learning networks.  ...  , Lin et al. propose the multi-task network to estimate the person attributes and person ID simultaneously.  ... 
arXiv:1901.07474v1 fatcat:h5krexsotbecvlwi2w4uw2y3ay

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.  ...  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.  ...  [198] develop a multi-stage convolution network to recurrently optimize the estimated 3D pose.  ... 
doi:10.1145/3524497 fatcat:4pbvntngrnfp7lqhcpjmy7p2fq

Attention-Aware Compositional Network for Person Re-identification [article]

Jing Xu, Rui Zhao, Feng Zhu, Huaming Wang, Wanli Ouyang
2018 arXiv   pre-print
In this work, we introduce a novel framework called Attention-Aware Compositional Network (AACN) for person ReID.  ...  Furthermore, pose-guided visibility scores are estimated for body parts to deal with part occlusion in the proposed AFC module.  ...  Inspired by the multi-stage CNN [6] for human pose estimation, we utilize a two-stage network to learn part attentions.  ... 
arXiv:1805.03344v2 fatcat:ciqqzd4mqjcevgpjejk4ezti6y

Table of contents

2020 IEEE Transactions on Image Processing  
Urey 4505 One-Pass Multi-Task Networks With Cross-Task Guided Attention for Brain Tumor Segmentation ..................... ..............................................................................  ...  Daei 2452 Tensor Multi-Task Learning for Person Re-Identification ........... Z. Zhang, Y. Xie, W. Zhang, Y. Tang, and Q.  ... 
doi:10.1109/tip.2019.2940372 fatcat:h23ul2rqazbstcho46uv3lunku

Attention-Aware Compositional Network for Person Re-identification

Jing Xu, Rui Zhao, Feng Zhu, Huaming Wang, Wanli Ouyang
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition  
In this work, we introduce a novel framework called Attention-Aware Compositional Network (AACN) for person ReID.  ...  Furthermore, pose-guided visibility scores are estimated for body parts to deal with part occlusion in the proposed AFC module.  ...  Inspired by the multi-stage CNN [6] for human pose estimation, we utilize a two-stage network to learn part attentions.  ... 
doi:10.1109/cvpr.2018.00226 dblp:conf/cvpr/Xu00WO18 fatcat:ac2nvw2lhfazpmdit6w53ovyoq

Mutual Learning to Adapt for Joint Human Parsing and Pose Estimation [chapter]

Xuecheng Nie, Jiashi Feng, Shuicheng Yan
2018 Lecture Notes in Computer Science  
This paper presents a novel Mutual Learning to Adapt model (MuLA) for joint human parsing and pose estimation.  ...  Different from existing post-processing or multi-task learning based methods, MuLA predicts dynamic task-specific model parameters via recurrently leveraging guidance information from its parallel tasks  ...  We visualize human parsing and multi-person pose estimation results in Fig. 4 (b) .  ... 
doi:10.1007/978-3-030-01228-1_31 fatcat:lsjqh4ckong37kvnovkdt4xeae

2021 Index IEEE Transactions on Multimedia Vol. 23

2021 IEEE transactions on multimedia  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TMM 2021 4376-4387 Pose-Guided Tracking-by-Detection: Robust Multi-Person Pose Tracking.  ...  ., +, TMM 2021 1160-1172 3D Pose Estimation Based on Reinforce Learning for 2D Image-Based 3D Model Retrieval.  ... 
doi:10.1109/tmm.2022.3141947 fatcat:lil2nf3vd5ehbfgtslulu7y3lq

Look into Person: Joint Body Parsing & Pose Estimation Network and A New Benchmark [article]

Xiaodan Liang and Ke Gong and Xiaohui Shen and Liang Lin
2018 arXiv   pre-print
Furthermore, we simplify the network to solve human parsing by exploring a novel self-supervised structure-sensitive learning approach, which imposes human pose structures into the parsing results without  ...  To further explore and take advantage of the semantic correlation of these two tasks, we propose a novel joint human parsing and pose estimation network to explore efficient context modeling, which can  ...  From the comparisons, we can learn that multi-scale features greatly improve for human parsing but slightly for pose estimation.  ... 
arXiv:1804.01984v1 fatcat:rh3sppvtffatfeufksixt724qu

Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing [article]

Ke Gong, Xiaodan Liang, Dongyu Zhang, Xiaohui Shen, Liang Lin
2017 arXiv   pre-print
imposes human pose structures into parsing results without resorting to extra supervision (i.e., no need for specifically labeling human joints in model training).  ...  Our self-supervised learning framework can be injected into any advanced neural networks to help incorporate rich high-level knowledge regarding human joints from a global perspective and improve the parsing  ...  [5] proposed an attention mechanism that learns to weight the multi-scale features at each pixel location.  ... 
arXiv:1703.05446v2 fatcat:y2k2n5xm5relnehlriod7hq76e
« Previous Showing results 1 — 15 out of 14,973 results