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Walking and talking: A bilinear approach to multi-label action recognition

Sameh Khamis, Larry S. Davis
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ilwxppn4d5hizekyd3ndvy2mii" style="color: black;">2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</a> </i> &nbsp;
In contrast, we formulate multi-label training and label correlation estimation as a joint max-margin bilinear classification problem.  ...  In this work we pose the action recognition as a multi-label problem, i.e., an actor can be performing any plausible subset of actions.  ...  A visualization of the final label correlation matrix P. Intuitively, walking and talking are positively correlated, while walking and waiting were unlikely to co-occur in the dataset.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvprw.2015.7301277">doi:10.1109/cvprw.2015.7301277</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cvpr/KhamisD15.html">dblp:conf/cvpr/KhamisD15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ueal4yqlerhrrn3mknqp45iwhy">fatcat:ueal4yqlerhrrn3mknqp45iwhy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809070914/http://www.cv-foundation.org/openaccess/content_cvpr_workshops_2015/W04/papers/Khamis_Walking_and_Talking_2015_CVPR_paper.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2a/9a/2a9a1da7b652ab2dafa627d507ec9a6452f6b17e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvprw.2015.7301277"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Efficient and precise interactive hand tracking through joint, continuous optimization of pose and correspondences

Jonathan Taylor, Benjamin Luff, Arran Topalian, Erroll Wood, Sameh Khamis, Pushmeet Kohli, Shahram Izadi, Richard Banks, Andrew Fitzgibbon, Jamie Shotton, Lucas Bordeaux, Thomas Cashman (+6 others)
<span title="2016-07-11">2016</span> <i title="Association for Computing Machinery (ACM)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cqrugwalkvcezgalqorn4fwnuu" style="color: black;">ACM Transactions on Graphics</a> </i> &nbsp;
Walking and Talking: A Bilinear Approach to Multi-Label Action Recognition. In CVPR Workshop on Group And Crowd Behavior Analysis And Understanding, Boston, Massachusetts, 2015.  ...  Last Updated: March 9, 2017 Research Assistant, University of Maryland (College Park, MD) Jan '11 -May '15 • Multi-Label Action Recognition: Recast action recognition as a multi-label problem, where  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2897824.2925965">doi:10.1145/2897824.2925965</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bpvwloljcjetnezxj6u63hu6de">fatcat:bpvwloljcjetnezxj6u63hu6de</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170706090623/http://www.samehkhamis.com/samehkhamis.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/5d/48/5d48e415d8549bd2d6cf665966411bce3083c999.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2897824.2925965"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Human Action Recognition Algorithm Based on Multi-feature Map Fusion

Haofei Wang, Junfeng Li
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
To solve this problem, on the basis of resnext human action recognition method, we propose an improved resnext human action recognition method based on multi-feature map fusion.  ...  The emergence of the convolutional neural network greatly improves the accuracy of human action recognition.  ...  HUMAN ACTION RECOGNITION ALGORITHM BASED ON MULTI-FEATURE MAP FUSION A.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.3017076">doi:10.1109/access.2020.3017076</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/r7y5sye4uzdwhmrktq3attbndu">fatcat:r7y5sye4uzdwhmrktq3attbndu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200820131038/https://ieeexplore.ieee.org/ielx7/6287639/6514899/09169613.pdf?tp=&amp;arnumber=9169613&amp;isnumber=6514899&amp;ref=" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/0b/0a/0b0a6686cf834d084d38633ca03576deb5bef48e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.3017076"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

A Message Passing Algorithm for MRF Inference with Unknown Graphs and Its Applications [chapter]

Zhenhua Wang, Zhiyi Zhang, Nan Geng
<span title="">2015</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
The scalability is a bottleneck that prevents applying such technique to larger problems such as image segmentation and object detection.  ...  Here we present a fast message passing algorithm based on the mixed-integer bilinear programming formulation of the original problem.  ...  Inferring graphs and labels directly and simultaneously from data has shown to be favourable comparing with using fixed hand-engineered graphs in human action recognition [4, 5] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-16817-3_19">doi:10.1007/978-3-319-16817-3_19</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/z7ov4m7twbe57dqcrah7hlfuke">fatcat:z7ov4m7twbe57dqcrah7hlfuke</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170829164432/http://vigir.missouri.edu/~gdesouza/Research/Conference_CDs/ACCV_2014/pages/PDF/103.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/72/b2/72b28064533eefd532dcdd5358e900a5d70e9b43.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-16817-3_19"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Recurrent Tubelet Proposal and Recognition Networks for Action Detection [chapter]

Dong Li, Zhaofan Qiu, Qi Dai, Ting Yao, Tao Mei
<span title="">2018</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
The RTR capitalizes on a multi-channel architecture, where in each channel, a tubelet proposal is fed into a CNN plus LSTM to recurrently recognize action in the tubelet.  ...  Specifically, we present a novel deep architecture called Recurrent Tubelet Proposal and Recognition (RTPR) networks to incorporate temporal context for action detection.  ...  ., varying scales (third row) and multi-person plus multi-label (last row), our approach can still work very well.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-030-01231-1_19">doi:10.1007/978-3-030-01231-1_19</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fllf4ihw6vawvpfns3cffulgle">fatcat:fllf4ihw6vawvpfns3cffulgle</a> </span>
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A Comprehensive Study of Deep Video Action Recognition [article]

Yi Zhu, Xinyu Li, Chunhui Liu, Mohammadreza Zolfaghari, Yuanjun Xiong, Chongruo Wu, Zhi Zhang, Joseph Tighe, R. Manmatha, Mu Li
<span title="2020-12-11">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In the end, we discuss open problems and shed light on opportunities for video action recognition to facilitate new research ideas.  ...  In this paper, we provide a comprehensive survey of over 200 existing papers on deep learning for video action recognition.  ...  Acknowledgement We would like to thank Peter Gehler, Linchao Zhu and Thomas Brady for constructive feedback and fruitful discussions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2012.06567v1">arXiv:2012.06567v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/plqytbfck5bcndiceshix5unpa">fatcat:plqytbfck5bcndiceshix5unpa</a> </span>
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Spatio-Temporal Dynamic Inference Network for Group Activity Recognition [article]

Hangjie Yuan, Dong Ni, Mang Wang
<span title="2021-08-26">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Within each interaction field, we apply DR to predict the relation matrix and DW to predict the dynamic walk offsets in a joint-processing manner, thus forming a person-specific interaction graph.  ...  Group activity recognition aims to understand the activity performed by a group of people. In order to solve it, modeling complex spatio-temporal interactions is the key.  ...  Acknowledgement: We would like to thank Jiayang Ren, Rong Jin and anonymous reviewers for their valuable feedback. This work was supported by the National Science Foundation China grant No. U1609213.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2108.11743v1">arXiv:2108.11743v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xt43rxhtmfetjioo5bifdigvdy">fatcat:xt43rxhtmfetjioo5bifdigvdy</a> </span>
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Attend and Guide (AG-Net): A Keypoints-driven Attention-based Deep Network for Image Recognition

Asish Bera, Zachary Wharton, Yonghuai Liu, Nik Bessis, Ardhendu Behera
<span title="2021-03-11">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dhlhr4jqkbcmdbua2ca45o7kru" style="color: black;">IEEE Transactions on Image Processing</a> </i> &nbsp;
The model outperforms the state-of-the-art approaches by a considerable margin using Distracted Driver V1 (Acc: 3.39%), Distracted Driver V2 (Acc: 6.58%), Stanford-40 Actions (mAP: 2.15%), People Playing  ...  This framework applies to traditional and fine-grained image recognition tasks and does not require manually annotated regions (e.g. bounding-box of body parts, objects, etc.) for learning and prediction  ...  We thank the Associate Editor and three anonymous reviewers for their constructive comments that have improved the quality of the paper.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2021.3064256">doi:10.1109/tip.2021.3064256</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33705316">pmid:33705316</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ii6iozzjw5aptoeofoyq3yqeci">fatcat:ii6iozzjw5aptoeofoyq3yqeci</a> </span>
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3D Convolutional Networks for Action Recognition: Application to Sport Gesture Recognition [article]

Pierre-Etienne Martin, J Benois-Pineau, R Péteri, A Zemmari, J Morlier
<span title="2022-04-13">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
3D convolutional networks is a good means to perform tasks such as video segmentation into coherent spatio-temporal chunks and classification of them with regard to a target taxonomy.  ...  Filmed in a free marker less ecological environment, these videos represent a challenge from both segmentation and classification point of view.  ...  Their objectives is to evaluate classical action recognition approaches with regard to player action recognition in tennis games. The data are collected from tennis TV broadcasts.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2204.08460v1">arXiv:2204.08460v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7ks2orf4m5ge5ggmafbeghbrsu">fatcat:7ks2orf4m5ge5ggmafbeghbrsu</a> </span>
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New Convex Relaxations for MRF Inference With Unknown Graphs

Zhenhua Wang, Tong Liu, Qinfeng Shi, M. Pawan Kumar, Jianhua Zhang
<span title="">2019</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/753trptklbb4nj6jquqadzwwdu" style="color: black;">2019 IEEE/CVF International Conference on Computer Vision (ICCV)</a> </i> &nbsp;
Treating graph structures of Markov random fields as unknown and estimating them jointly with labels have been shown to be useful for modeling human activity recognition and other related tasks.  ...  We demonstrate the efficacy of our new relaxations for both synthetic data and human activity recognition.  ...  This work is partially supported by National Natural Science Foundation of China (61802348, 61876167 and U1509207), National Key R&D Program of China (2018YFB1305200), and ARC discovery grant (DP160100703  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccv.2019.01003">doi:10.1109/iccv.2019.01003</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/iccv/WangLSKZ19.html">dblp:conf/iccv/WangLSKZ19</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xzbv3lad7behnj3w6tqazbcl5m">fatcat:xzbv3lad7behnj3w6tqazbcl5m</a> </span>
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Learning Neural Textual Representations for Citation Recommendation

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
<span title="2021-01-10">2021</span> <i title="IEEE"> 2020 25th International Conference on Pattern Recognition (ICPR) </i> &nbsp;
CH3.2 A Hierarchical Multi-Task Approach to Gastrointestinal Image Analysis DAY 2 -Jan 13, 2021 Live Zhipeng Luo et al.  ...  2021 Tsai, Wen-Jiin; Jhuang, You-Ying, You-Ying 1973 DeepPear: Deep Pose Estimation and Action Recognition DAY 4 -Jan 15, 2021 Zheng, XiaoQiang; Yu, ZhenXia; chen, lin; Zhu, Fan; Wang, Shilong 2027 Multi-Label  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icpr48806.2021.9412725">doi:10.1109/icpr48806.2021.9412725</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3vge2tpd2zf7jcv5btcixnaikm">fatcat:3vge2tpd2zf7jcv5btcixnaikm</a> </span>
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A Comparative Review of Recent Kinect-based Action Recognition Algorithms

Lei Wang, Du Q. Huynh, Piotr Koniusz
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dhlhr4jqkbcmdbua2ca45o7kru" style="color: black;">IEEE Transactions on Image Processing</a> </i> &nbsp;
In this paper, we analyze and compare ten recent Kinect-based algorithms for both cross-subject action recognition and cross-view action recognition using six benchmark datasets.  ...  Since the release of the Kinect camera, a large number of Kinect-based human action recognition techniques have been proposed in the literature.  ...  ACKNOWLEDGMENTS We would like to thank the authors of HON4D [11] , HOPC [13] , LARP-SO [19] , HPM+TM [14] , IndRNN [27] and ST-GCN [26] for making their codes publicly available.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2019.2925285">doi:10.1109/tip.2019.2925285</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cluwehzl7jh4zmthater6naxrq">fatcat:cluwehzl7jh4zmthater6naxrq</a> </span>
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Static and dynamic 3D facial expression recognition: A comprehensive survey

Georgia Sandbach, Stefanos Zafeiriou, Maja Pantic, Lijun Yin
<span title="">2012</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/z7tk7kanxjcz7hgk77ae6t3ofy" style="color: black;">Image and Vision Computing</a> </i> &nbsp;
Finally, challenges that have to be addressed if 3D facial expression recognition systems are to become a part of future applications are extensively discussed.  ...  Automatic facial expression recognition constitutes an active research field due to the latest advances in computing technology that make the user's experience a clear priority.  ...  Facial surface features on the mapped mesh were then labelled according to twelve primitives to form a facial expression label map (FELM).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.imavis.2012.06.005">doi:10.1016/j.imavis.2012.06.005</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oqijx33myrbmzcbbywrysbezie">fatcat:oqijx33myrbmzcbbywrysbezie</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160909221824/http://www.ibug.doc.ic.ac.uk:80/media/uploads/documents/sandbach2012survey.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/31/bb/31bb49ba7df94b88add9e3c2db72a4a98927bb05.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.imavis.2012.06.005"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Ego4D: Around the World in 3,000 Hours of Egocentric Video [article]

Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, Miguel Martin, Tushar Nagarajan (+73 others)
<span title="2022-03-11">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The approach to collection is designed to uphold rigorous privacy and ethics standards with consenting participants and robust de-identification procedures where relevant.  ...  We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite.  ...  Chu, Samuel Clapp, Irene D'Ambra, Peter Dodds, Jacob Donley, Ruohan Gao, Tal Hassner, Ethan Acknowledgements The social benchmark team would like to acknowledge the following additional contributions  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2110.07058v3">arXiv:2110.07058v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lgh27km63nhcdcpkvbr2qarsru">fatcat:lgh27km63nhcdcpkvbr2qarsru</a> </span>
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Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures [article]

Raffaella Bernardi, Ruket Cakici, Desmond Elliott, Aykut Erdem, Erkut Erdem, Nazli Ikizler-Cinbis, Frank Keller, Adrian Muscat, Barbara Plank
<span title="2017-04-24">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this survey, we classify the existing approaches based on how they conceptualize this problem, viz., models that cast description as either generation problem or as a retrieval problem over a visual  ...  Moreover, we give an overview of the benchmark image datasets and the evaluation measures that have been developed to assess the quality of machine-generated image descriptions.  ...  4. a woman and a child are walking over the square (c) Flickr8K 9 (d) IAPR-TC12 10 1.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1601.03896v2">arXiv:1601.03896v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lbifbktev5dtbhx4obldg4t5x4">fatcat:lbifbktev5dtbhx4obldg4t5x4</a> </span>
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