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VITAL: VIsual Tracking via Adversarial Learning

Yibing Song, Chao Ma, Xiaohe Wu, Lijun Gong, Linchao Bao, Wangmeng Zuo, Chunhua Shen, Rynson W.H. Lau, Ming-Hsuan Yang
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition  
This paper presents the VITAL algorithm to address these two problems via adversarial learning.  ...  With the use of adversarial learning, our network identifies the mask that maintains the most robust features of the target objects over a long temporal span.  ...  Our VITAL tracker learns to diversify positive samples via adversarial learning and to balance training samples via cost sensitive loss.  ... 
doi:10.1109/cvpr.2018.00937 dblp:conf/cvpr/Song0WGBZSL018 fatcat:3pamz4hlfbbfnkfmlr2nnap7ri

VITAL: VIsual Tracking via Adversarial Learning [article]

Yibing Song, Chao Ma, Xiaohe Wu, Lijun Gong, Linchao Bao, Wangmeng Zuo, Chunhua Shen, Rynson Lau, Ming-Hsuan Yang
2018 arXiv   pre-print
This paper presents the VITAL algorithm to address these two problems via adversarial learning.  ...  With the use of adversarial learning, our network identifies the mask that maintains the most robust features of the target objects over a long temporal span.  ...  Our VITAL tracker learns to diversify positive samples via adversarial learning and to balance training samples via cost sensitive loss.  ... 
arXiv:1804.04273v1 fatcat:fqib3dztfvdxng57lbfgrdcpiq

Camera Measurement of Physiological Vital Signs [article]

Daniel McDuff
2021 arXiv   pre-print
Building on advances in optics, machine learning, computer vision and medicine these techniques have progressed significantly since the invention of digital cameras.  ...  This paper presents a comprehensive survey of camera measurement of physiological vital signs, describing they vital signs that can be measured and the computational techniques for doing so.  ...  Unsupervised Learning Generative Adversarial Networks. Other methods have used generative adversarial networks to train models to generate realistic PPG waveforms.  ... 
arXiv:2111.11547v1 fatcat:47l2buzxg5ht5lhrqsuszjha6a

Deep Learning Technology: A Vital Tool for National Development

Agbaraji E. C., Federal Polytechnic Nekede, Owerri
2019 International Journal of Engineering Research and  
This paper focuses on the study of deep learning technology as a vital tool for national development. There are many problems hindering the growth of most developing nations.  ...  From the review, it was concluded that deep learning can solve most of the challenges facing the developing nations.  ...  The layers are interconnected via nodes, or neurons, with each hidden layer using the output of the previous layer as its input [9] . IV.  ... 
doi:10.17577/ijertv8is070161 fatcat:dqeuc4hkofdcdgcmocya4v44te

Vocations, visions and vitalities of data analysis. An introduction

Mareile Kaufmann
2020 Information, Communication & Society  
It visualizes how authorities see migrants through thermal cameras.  ...  Via play and re-appropriation, then, users inject a liveliness into tools.  ... 
doi:10.1080/1369118x.2020.1777320 fatcat:ss7344h3cjfqxacv7bvk3wuxde

AI-enabled remote monitoring of vital signs for COVID-19: methods, prospects and challenges

Honnesh Rohmetra, Navaneeth Raghunath, Pratik Narang, Vinay Chamola, Mohsen Guizani, Naga Rajiv Lakkaniga
2021 Computing  
Recent advances in Machine Learning (ML) and Deep Learning (DL) have strengthened the power of imaging techniques and can be used to remotely perform several tasks that previously required the physical  ...  We demonstrate the potential of ML-enabled workflows for several vital signs such as heart and respiratory rates, cough, blood pressure, and oxygen saturation.  ...  [5] assess several machine learning based algorithms for clustering and prediction of vital signs.  ... 
doi:10.1007/s00607-021-00937-7 fatcat:jf5gu4ocj5cs3eerzlya625duq

Adversarial Feature Sampling Learning for Efficient Visual Tracking [article]

Yingjie Yin, Lei Zhang, De Xu, Xingang Wang
2018 arXiv   pre-print
In this paper, we propose a new visual tracking method using sampling deep convolutional features to address this problem.  ...  In addition, a generative adversarial network is integrated into our network framework to augment positive samples and improve the tracking performance.  ...  [7] proposed visual tracking via adversarial learning (VITAL) to narrow the gap between GANs and the tracking-by-detection framework.  ... 
arXiv:1809.04741v2 fatcat:gmboqsu7ojhnnc2ggtsoumr2hi

The vitality of allegory: figural narrative in modern and contemporary fiction

2012 ChoiceReviews  
A rhetorical approach to narrative-and by extension to allegory-seeks to allow for the intersection of the compositional and hermeneutic tracks via the concepts of purpose (which I discussed above in relation  ...  We can see, then, that allegory develops along two different tracks, a compositional track and a hermeneutic one.  ... 
doi:10.5860/choice.50-0122 fatcat:rogqjgrbkffz7lqjnfzqswlcwy

Robust Visual Tracking Based on Hybrid Network and Similarity Grouping

Yu Liu, Xiaoqiang Li, Chen Huang, Dian-hua Zhang, Ming-ke Gao
2019 Australian Journal of Intelligent Information Processing Systems  
The proposed HNM adopts recurrent neural networks (RNNs) to model the self-structure of object, and utilizes adversarial learning to enhance the representation ability of the most robust features in temporal  ...  offline training as a binary classifier for online tracking.  ...  RNN on Visual tracking. In field of visual tracking, the RNNs model has successfully simulated long-term contextual dependencies among frames. Ning et al.  ... 
dblp:journals/ajiips/LiuLHZG19 fatcat:ivqf7unkefeuzj5xy3fduglexe

Adversarial Semi-Supervised Multi-Domain Tracking [article]

Kourosh Meshgi, Maryam Sadat Mirzaei
2020 arXiv   pre-print
In visual tracking, the emerging features in shared layers of a multi-domain tracker, trained on various sequences, are crucial for tracking in unseen videos.  ...  We propose a semi-supervised learning scheme to separate domain-invariant and domain-specific features using adversarial learning, to encourage mutual exclusion between them, and to leverage self-supervised  ...  Related Works Deep Visual Tracking.  ... 
arXiv:2009.14635v1 fatcat:mgcali7nz5eh3ip5psdyau6rb4

Learning Target-aware Attention for Robust Tracking with Conditional Adversarial Network

Xiao Wang, Rui Yang, Tao Sun, Bin Luo
2019 British Machine Vision Conference  
Through conditional generative adversarial network (CGAN), attention maps are produced to generate the proposals with high-quality locations and scales, and perform object tracking via multi-domain CNN  ...  Many of current visual trackers are based on tracking-by-detection framework which attempts to search target object within a local search window for each frame.  ...  This fully demonstrate the importance of accurate attention region mining via joint MSE and adversarial training.  ... 
dblp:conf/bmvc/WangYSL19 fatcat:s6y6g64tyvgrzck3cxq4xzmf3y

VideoMoCo: Contrastive Video Representation Learning with Temporally Adversarial Examples [article]

Tian Pan, Yibing Song, Tianyu Yang, Wenhao Jiang, Wei Liu
2021 arXiv   pre-print
By adaptively dropping out different frames during training iterations of adversarial learning, we augment this input sample to train a temporally robust encoder.  ...  This degradation is reflected via temporal decay to attend the input sample to recent keys in the queue.  ...  Vital: Visual tracking via adversarial [50] Dejing Xu, Jun Xiao, Zhou Zhao, Jian Shao, Di Xie, and learning. In IEEE/CVF Conference on Computer Vision and Yueting Zhuang.  ... 
arXiv:2103.05905v2 fatcat:sf5xbs6n7zgubgdku2yi3j7oae

Learning attention for object tracking with adversarial learning network

Xu Cheng, Chen Song, Yongxiang Gu, Beijing Chen
2020 EURASIP Journal on Image and Video Processing  
To solve above two issues, in this paper, an effective object tracking method with learning attention is proposed to achieve the object localization and reduce the training time in adversarial learning  ...  Second, the prediction network is integrated into the generative adversarial network framework, which randomly generates masks to capture object appearance variations via adaptively dropout input features  ...  The adaptive dropout is achieved via adversarial learning to find discriminative features according to different inputs.  ... 
doi:10.1186/s13640-020-00535-1 fatcat:l3l3w6jv7rbl5em6sgxj5dxvme

FoleyGAN: Visually Guided Generative Adversarial Network-Based Synchronous Sound Generation in Silent Videos [article]

Sanchita Ghose, John J. Prevost
2021 arXiv   pre-print
Our proposed FoleyGAN model is capable of conditioning action sequences of visual events leading towards generating visually aligned realistic sound tracks.  ...  Deep learning based visual to sound generation systems essentially need to be developed particularly considering the synchronicity aspects of visual and audio features with time.  ...  Finally, the generated spectrogram is inverted via ISTFT to obtain the visually synced sound track for the respected video clip.  ... 
arXiv:2107.09262v1 fatcat:lqyve5czjzdf3ihtcr7vohffyi

Deep Learning for Visual Tracking: A Comprehensive Survey [article]

Seyed Mojtaba Marvasti-Zadeh, Li Cheng, Hossein Ghanei-Yakhdan, and Shohreh Kasaei
2019 arXiv   pre-print
It also extensively evaluates and analyzes the leading visual tracking methods.  ...  Visual target tracking is one of the most sought-after yet challenging research topics in computer vision.  ...  Kamal Nasrollahi (Visual Analysis of People Lab (VAP), Aalborg University) for his beneficial comments.  ... 
arXiv:1912.00535v1 fatcat:v5ikqi2cpbblhgtkiu6z6l5anq
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