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Gabriella: An Online System for Real-Time Activity Detection in Untrimmed Security Videos [article]

Mamshad Nayeem Rizve, Ugur Demir, Praveen Tirupattur, Aayush Jung Rana, Kevin Duarte, Ishan Dave, Yogesh Singh Rawat, Mubarak Shah
<span title="2020-05-19">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this work we propose Gabriella, a real-time online system to perform activity detection on untrimmed security videos.  ...  The requirement of processing the security videos in real-time makes this even more challenging.  ...  Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2004.11475v2">arXiv:2004.11475v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ziz7mlp56jbhdjgyoxiojry3ki">fatcat:ziz7mlp56jbhdjgyoxiojry3ki</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200528023201/https://arxiv.org/pdf/2004.11475v2.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] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2004.11475v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

DAM: Dissimilarity Attention Module for Weakly-supervised Video Anomaly Detection

Snehashis Majhi, Srijan Das, Francois Bremond
<span title="2021-11-16">2021</span> <i title="IEEE"> 2021 17th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) </i> &nbsp;
This allows the framework to detect anomalies in real-time (i.e. online) scenarios without the need of extra window buffer time.  ...  Video anomaly detection under weak supervision is complicated due to the difficulties in identifying the anomaly and normal instances during training, hence, resulting in non-optimal margin of separation  ...  The authors are also grateful to the OPAL infrastructure from Université Côte d'Azur for providing resources and support.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/avss52988.2021.9663810">doi:10.1109/avss52988.2021.9663810</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4gtgkduwrzailk7gtq5rvchfgu">fatcat:4gtgkduwrzailk7gtq5rvchfgu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220309024950/https://hal.archives-ouvertes.fr/hal-03523616/file/AVSS_2021_Dissimilarity_Attention(1).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/f6/38/f63855c59afb8caf9627283e3f4c5e18f9f2375e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/avss52988.2021.9663810"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Online temporal detection of daily-living human activities in long untrimmed video streams

Abhishek Goel, Abdelrahman Abubakr, Michal Koperski, Francois Bremond, Gianpiero Francesca
<span title="">2018</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/v6z45mu6d5dtvejhm5rc2ekkxi" style="color: black;">2018 IEEE International Conference on Image Processing, Applications and Systems (IPAS)</a> </i> &nbsp;
In this work we focus on solving the problem of detection of daily-living activities in untrimmed video streams.  ...  However, it is not practical to have clipped videos in real life, where cameras provide continuous video streams in applications such as robotics, video surveillance, and smart-homes.  ...  In addition, for systems that require online detection, it is not practical to wait for long time until reading all frames of long activities to recognize its label.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ipas.2018.8708880">doi:10.1109/ipas.2018.8708880</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/ipas2/GoelAKBF18.html">dblp:conf/ipas2/GoelAKBF18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7lhaqyno5nbvjbrkmcb5apacjq">fatcat:7lhaqyno5nbvjbrkmcb5apacjq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200505114352/https://hal.inria.fr/hal-01948387/file/IPAS_2018.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/ca/f8/caf862d8e33c46de523cf7ccffe2124c1c6e2441.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ipas.2018.8708880"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Argus++: Robust Real-time Activity Detection for Unconstrained Video Streams with Overlapping Cube Proposals [article]

Lijun Yu, Yijun Qian, Wenhe Liu, Alexander G. Hauptmann
<span title="2022-01-14">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
To overcome these issues, we propose Argus++, a robust real-time activity detection system for analyzing unconstrained video streams.  ...  The overall system is optimized for real-time processing on standalone consumer-level hardware.  ...  Gabriella: An Online System for [10] Will Kay, Joao Carreira, Karen Simonyan, Brian Zhang, Real-Time Activity Detection in Untrimmed Security Videos.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2201.05290v1">arXiv:2201.05290v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n6xmnelt7nbs5cnefcgjrik4cm">fatcat:n6xmnelt7nbs5cnefcgjrik4cm</a> </span>
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ActivityNet: A large-scale video benchmark for human activity understanding

Fabian Caba Heilbron, Victor Escorcia, Bernard Ghanem, Juan Carlos Niebles
<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 (CVPR)</a> </i> &nbsp;
In its current version, ActivityNet provides samples from 203 activity classes with an average of 137 untrimmed videos per class and 1.41 activity instances per video, for a total of 849 video hours.  ...  We illustrate three scenarios in which ActivityNet can be used to compare algorithms for human activity understanding: untrimmed video classification, trimmed activity classification and activity detection  ...  Acknowledgments We would like to thank the Stanford Vision Lab for their helpful comments and support.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvpr.2015.7298698">doi:10.1109/cvpr.2015.7298698</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cvpr/HeilbronEGN15.html">dblp:conf/cvpr/HeilbronEGN15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mwlxj6rbdvay7ior2fs3lb6s54">fatcat:mwlxj6rbdvay7ior2fs3lb6s54</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170921204754/http://repository.kaust.edu.sa/kaust/bitstream/10754/556141/1/ActivityNet_CVPR2015.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/d1/ff/d1ffe122f69e74c91ef05ae09dda2d94df85d851.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvpr.2015.7298698"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

WOAD: Weakly Supervised Online Action Detection in Untrimmed Videos [article]

Mingfei Gao, Yingbo Zhou, Ran Xu, Richard Socher, Caiming Xiong
<span title="2021-05-18">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Online action detection in untrimmed videos aims to identify an action as it happens, which makes it very important for real-time applications.  ...  With the supervisory signals from TPG, OAR learns to conduct action detection in an online fashion.  ...  We thank Zuxuan Wu, Zeyuan Chen and Salesforce researchers for the help of improving the writing.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2006.03732v2">arXiv:2006.03732v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ji5sryyu35bfnnk3kcjdiz3iyq">fatcat:ji5sryyu35bfnnk3kcjdiz3iyq</a> </span>
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Online Detection of Action Start in Untrimmed, Streaming Videos [article]

Zheng Shou, Junting Pan, Jonathan Chan, Kazuyuki Miyazawa, Hassan Mansour, Anthony Vetro, Xavier Giro-i-Nieto, Shih-Fu Chang
<span title="2018-07-23">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We aim to tackle a novel task in action detection - Online Detection of Action Start (ODAS) in untrimmed, streaming videos.  ...  The goal of ODAS is to detect the start of an action instance, with high categorization accuracy and low detection latency.  ...  Online detection requires continuously monitoring the live video stream in real time.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1802.06822v3">arXiv:1802.06822v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ob5gy45jjbgifgjgj35o4f5dt4">fatcat:ob5gy45jjbgifgjgj35o4f5dt4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200824150125/https://arxiv.org/pdf/1802.06822v3.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/b8/b4/b8b4a0bdfb561edaaed971f6e416c641b295376d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1802.06822v3" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

A Novel Online Action Detection Framework from Untrimmed Video Streams [article]

Da-Hye Yoon, Nam-Gyu Cho, Seong-Whan Lee
<span title="2020-03-17">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Online temporal action localization from an untrimmed video stream is a challenging problem in computer vision.  ...  It is challenging because of i) in an untrimmed video stream, more than one action instance may appear, including background scenes, and ii) in online settings, only past and current information is available  ...  In the meanwhile, there are also several limitations.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2003.07734v1">arXiv:2003.07734v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3ilcxc22ubd5hljek5hru2nn6a">fatcat:3ilcxc22ubd5hljek5hru2nn6a</a> </span>
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Online Detection of Action Start in Untrimmed, Streaming Videos [chapter]

Zheng Shou, Junting Pan, Jonathan Chan, Kazuyuki Miyazawa, Hassan Mansour, Anthony Vetro, Xavier Giro-i-Nieto, Shih-Fu Chang
<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;
We aim to tackle a novel task in action detection -Online Detection of Action Start (ODAS) in untrimmed, streaming videos.  ...  The goal of ODAS is to detect the start of an action instance, with high categorization accuracy and low detection latency.  ...  Online detection requires continuously monitoring the live video stream in real time.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-030-01219-9_33">doi:10.1007/978-3-030-01219-9_33</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/srxbb2ipvvcixoxftlpiuy4aly">fatcat:srxbb2ipvvcixoxftlpiuy4aly</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180922010429/http://openaccess.thecvf.com:80/content_ECCV_2018/papers/Zheng_Shou_Online_Detection_of_ECCV_2018_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/cc/dd/ccdd8018d4391acbc7205bbcbe71dcae687766da.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-030-01219-9_33"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

ITI-CERTH participation in ActEV and AVS Tracks of TRECVID 2021

Konstantinos Gkountakos, Damianos Galanopoulos, Despoina Touska, Konstantinos Ioannidis, Stefanos Vrochidis, Vasileios Mezaris, Ioannis Kompatsiaris
<span title="2022-03-01">2022</span> <i title="Zenodo"> Zenodo </i> &nbsp;
ITI-CERTH participated in the Ad-hoc Video Search (AVS) and Activities in Extended Video (ActEV) tasks.  ...  For the AVS task, our participation is based on an attention-based cross-modal deep network architecture.  ...  In this direction, the Activities in Extended Videos challenge (ActEV) encourage the research of real-time automatic activity detection methods in surveillance scenarios.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.5817708">doi:10.5281/zenodo.5817708</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kw4d2tg5nngydfcc37vihyp3uq">fatcat:kw4d2tg5nngydfcc37vihyp3uq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220206065828/https://zenodo.org/record/5817708/files/ITI_CERTH_TRECVID2021_zenodo.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/b9/14/b9149e91e02fea02f3232d675e838e851a64bc37.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.5817708"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> zenodo.org </button> </a>

Enhancing camera surveillance using computer vision: a research note [article]

Haroon Idrees, Mubarak Shah, Ray Surette
<span title="2018-08-12">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
surveillance camera tasks (live monitoring of multiple surveillance cameras and summarizing archived video files).  ...  Three unaddressed research questions (can specialized computer vision applications for law enforcement be developed at this time, how will computer vision be utilized within existing public safety camera  ...  , and detects sub-actions in an original untrimmed video.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1808.03998v1">arXiv:1808.03998v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/e2ysbxkjaba2rlxonmnvgcs7jq">fatcat:e2ysbxkjaba2rlxonmnvgcs7jq</a> </span>
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Anomalous Human Activity Recognition in Surveillance Videos

<span title="2019-09-05">2019</span> <i title="Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3sfifsouvjgadp4gfj54u3z2ku" style="color: black;">International journal of recent technology and engineering</a> </i> &nbsp;
Therefore, there is a need for a system which can recognize human activity effectively in real-time.  ...  the user in real-time.  ...  The smart surveillance system can detect road accidents in real-time and call for an ambulance. D.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijrte.b1064.0782s719">doi:10.35940/ijrte.b1064.0782s719</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/352q6ou655dr7oj2jtk2rl6eca">fatcat:352q6ou655dr7oj2jtk2rl6eca</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200210011053/https://www.ijrte.org/wp-content/uploads/papers/v8i2S7/B10640782S719.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/54/da/54dada208d8755054ecc542c21b6c074f5dd6de2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijrte.b1064.0782s719"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Self-Attention Temporal Convolutional Network for Long-Term Daily Living Activity Detection

Rui Dai, Luca Minciullo, Lorenzo Garattoni, Gianpiero Francesca, Francois Bremond
<span title="">2019</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s4u3jxdcmrevzj46e7ani77j4u" style="color: black;">2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)</a> </i> &nbsp;
In this paper, we address the detection of daily living activities in long-term untrimmed videos.  ...  In this paper, we propose Self-Attention -Temporal Convolutional Network (SA-TCN), which is able to capture both complex activity patterns and their dependencies within long-term untrimmed videos.  ...  Introduction Detecting activities in untrimmed videos has been a long-studied task in computer vision. Its performance impacts domains such as health-care, assistive robotics, and video surveillance.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/avss.2019.8909841">doi:10.1109/avss.2019.8909841</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/avss/DaiMGFB19.html">dblp:conf/avss/DaiMGFB19</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/77mk6k4trbh4zoac2ozs5ffsgi">fatcat:77mk6k4trbh4zoac2ozs5ffsgi</a> </span>
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Not only Look, but also Listen: Learning Multimodal Violence Detection under Weak Supervision [article]

Peng Wu, Jing Liu, Yujia Shi, Yujia Sun, Fangtao Shao, Zhaoyang Wu, Zhiwei Yang
<span title="2020-07-13">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Violence detection has been studied in computer vision for years.  ...  Besides, our method also includes an approximator to meet the needs of online detection. Our method outperforms other state-of-the-art methods on our released dataset and other existing benchmark.  ...  Online Detection As we mentioned, a violence detection system is not only applied for offline detection (Internet VCR), but also online detection (surveillance system).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2007.04687v2">arXiv:2007.04687v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7ad74cuhabhs7iggfqnucrffn4">fatcat:7ad74cuhabhs7iggfqnucrffn4</a> </span>
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<span title="">2018</span> <i title="IEEE"> 2018 IEEE International Conference on Image Processing, Applications and Systems (IPAS) </i> &nbsp;
Depth Upsampling on FPGAs . . . . . . . . . . . . . . . . . . 37 David Langerman, Sebastian Sabogal, Barath Ramesh and Alan George Online temporal detection of daily-living human activities in long untrimmed  ...  End to End Person Re-Identification for Automated Visual Surveillance . . . . . . . . . . . . . . . . . . 220 Saadia Batool, Muhammad Zeeshan Ali, Muhammad Shahzad and Muhammad Moazam Fraz An Optimization  ... 
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