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Adversarial Learning of Structure-Aware Fully Convolutional Networks for Landmark Localization [article]

Yu Chen, Chunhua Shen, Hao Chen, Xiu-Shen Wei, Lingqiao Liu, Jian Yang
2019 arXiv   pre-print
The effectiveness of the proposed network is evaluated on three pose-related tasks: 2D single human pose estimation, 2D facial landmark estimation and 3D single human pose estimation.  ...  training of the deep network.  ...  ACKNOWLEDGEMENTS This work was partially supported by the National Science Fund of China under Grant U1713208, Program for Changjiang Scholars and "111" Program AH92005.  ... 
arXiv:1711.00253v5 fatcat:3laenudkwjbqleiszofe6paxja

Adversarial Learning of Structure-Aware Fully Convolutional Networks for Landmark Localization

Yu Chen, Chunhua Shen, Hao Chen, Xiu-Shen Wei, Lingqiao Liu, Jian Yang
2019 IEEE Transactions on Pattern Analysis and Machine Intelligence  
The effectiveness of the proposed network is evaluated on three pose-related tasks: 2D human pose estimation, 2D facial landmark estimation and 3D human pose estimation.  ...  training of the deep network.  ...  ACKNOWLEDGEMENTS The authors would like to thank the editor and the anonymous reviewers for their critical and constructive comments. J.  ... 
doi:10.1109/tpami.2019.2901875 pmid:30835211 fatcat:bwcawevazfcp3dlk5qcg4j3ube

Exploring deep learning-based architecture, strategies, applications and current trends in generic object detection: A comprehensive review

Lubna Aziz, Sah bin Haji Salam, Sara Ayub
2020 IEEE Access  
Finally, we finish the survey by identifying fifteen current trends and promising direction for future research.  ...  object detection methods such as YOLO(v2 to v5), SSD, DSSD, RetinaNet, RefineDet, CornerNet, EfficientDet, M2Det 3) Some latest detectors such as, relation network for object detection, DCN v2, NAS FPN  ...  For more information, see https://creativecommons.org/licenses/by/4.0/. This article has been accepted for publication in a future issue of this journal, but has not been fully edited.  ... 
doi:10.1109/access.2020.3021508 fatcat:guri46oiejhfzeitxuuprpmjka

A Survey of Deep Learning-based Object Detection

Licheng Jiao, Fan Zhang, Fang Liu, Shuyuan Yang, Lingling Li, Zhixi Feng, Rong Qu
2019 IEEE Access  
With the rapid development of deep learning networks for detection tasks, the performance of object detectors has been greatly improved.  ...  algorithms and further research.  ...  Attention mechanism is an effective method for networks focusing on the most significant region part.  ... 
doi:10.1109/access.2019.2939201 fatcat:jesz2av2tjbkxfpaqyecptgls4

Automatic vocal tract landmark localization from midsagittal MRI data [article]

Mohammad Eslami, Christiane Neuschaefer-Rube, Antoine Serrurier
2019 arXiv   pre-print
Analyzing their variability is crucial for understanding speech production, diagnosing speech and swallowing disorders and building intuitive applications for rehabilitation.  ...  The generation of such a multi-channel image from an input MRI image is tested through two deep learning networks, one taken from the literature and one designed on purpose in this study, the flat-net.  ...  Badin for providing the data, L. Lamalle for recording them, and J.-A. Valdés Vargas and G. Ananthakrishnan for performing the majority of the initial landmark labelling.  ... 
arXiv:1907.07951v1 fatcat:dkaqnwl74rfgvio3sniuf4deci

VR content creation and exploration with deep learning: A survey

Miao Wang, Xu-Quan Lyu, Yi-Jun Li, Fang-Lue Zhang
2020 Computational Visual Media  
VR content creation and exploration relates to image and video analysis, synthesis and editing, so deep learning methods such as fully convolutional networks and general adversarial networks are widely  ...  This article surveys recent research that uses such deep learning methods for VR content creation and exploration.  ...  [124] proposed a "stacked hourglass" convolutional network architecture based on successive steps of pooling and upsampling for 2D human pose estimation.  ... 
doi:10.1007/s41095-020-0162-z fatcat:lgogzx26bvhn5f7uyefjkz7zny

Smart Fashion: A Review of AI Applications in the Fashion Apparel Industry [article]

Seyed Omid Mohammadi, Ahmad Kalhor
2021 arXiv   pre-print
Furthermore, we provide a list of 86 public fashion datasets accompanied by a list of suggested applications and additional information for each.  ...  The implementation of machine learning, computer vision, and artificial intelligence (AI) in fashion applications is opening lots of new opportunities for this industry.  ...  detection, CPM, Gaussian peak heatmap For shoe try-on task Wang [51] 2018 VGG-16, Fashion grammar, BCRNN 58.3% mDR Wild images Li [55] 2019 Two-stream multi-task network, Hourglass, 0.0467 NE For  ... 
arXiv:2111.00905v2 fatcat:6n6d62lntjfu5pxmjzgi4mpv6i

Deep Learning for Scene Classification: A Survey [article]

Delu Zeng, Minyu Liao, Mohammad Tavakolian, Yulan Guo, Bolei Zhou, Dewen Hu, Matti Pietikäinen, Li Liu
2021 arXiv   pre-print
directly from big raw data, have been bringing remarkable progress in the field of scene representation and classification.  ...  Scene classification, aiming at classifying a scene image to one of the predefined scene categories by comprehending the entire image, is a longstanding, fundamental and challenging problem in computer  ...  ACKNOWLEDGMENTS The authors would like to thank the pioneer researchers in scene classification and other related fields. This work was supported in part by grants from National Science  ... 
arXiv:2101.10531v2 fatcat:hwqw5so46ngxdlnfw7zynmpu6m

A Survey on Deep Domain Adaptation and Tiny Object Detection Challenges, Techniques and Datasets [article]

Muhammed Muzammul, Xi Li
2021 arXiv   pre-print
In the future, OD methods and models can be analyzed for real-time object detection, tracking strategies.  ...  In part 3), To obtain knowledge-able findings, we discussed different object detection methods, i.e., convolutions and convolutional neural networks (CNN), pooling operations with trending types.  ...  Hourglass network).  ... 
arXiv:2107.07927v1 fatcat:pgwxu5tnvzhj7ln3ccndmpilsi

A comprehensive survey on semantic facial attribute editing using generative adversarial networks [article]

Ahmad Nickabadi, Maryam Saeedi Fard, Nastaran Moradzadeh Farid, Najmeh Mohammadbagheri
2022 arXiv   pre-print
Among different domains, face photos have received a great deal of attention and a large number of face generation and manipulation models have been proposed.  ...  Generating random photo-realistic images has experienced tremendous growth during the past few years due to the advances of the deep convolutional neural networks and generative models.  ...  The refinement module takes modulated normalization layer, extracts salient features, and discards features not related to attribute changes.  ... 
arXiv:2205.10587v1 fatcat:thpe4crcgndifb5mhtuveww4ji

Deep Learning for Generic Object Detection: A Survey

Li Liu, Wanli Ouyang, Xiaogang Wang, Paul Fieguth, Jie Chen, Xinwang Liu, Matti Pietikäinen
2019 International Journal of Computer Vision  
Deep learning techniques have emerged as a powerful strategy for learning feature representations directly from data and have led to remarkable breakthroughs in the field of generic object detection.  ...  We finish the survey by identifying promising directions for future research.  ...  The authors would also like to express their sincere appreciation to Professor Jiří Matas, the associate editor and the anonymous reviewers for their comments and suggestions.  ... 
doi:10.1007/s11263-019-01247-4 fatcat:isdmz4febvbthgowo33c6ifhm4

A Guide to Image and Video based Small Object Detection using Deep Learning : Case Study of Maritime Surveillance [article]

Aref Miri Rekavandi, Lian Xu, Farid Boussaid, Abd-Krim Seghouane, Stephen Hoefs, Mohammed Bennamoun
2022 arXiv   pre-print
In addition, the popular datasets that have been used for SOD for generic and maritime applications are discussed, and also well-known evaluation metrics for the state-of-the-art methods on some of the  ...  Small object detection (SOD) in optical images and videos is a challenging problem that even state-of-the-art generic object detection methods fail to accurately localize and identify such objects.  ...  ACKNOWLEDGEMENT This research is supported by the Commonwealth of Australia as represented by the Defence Science and Technology Group of the Department of Defence.  ... 
arXiv:2207.12926v1 fatcat:fjcuijt2f5d63apgg67eiydofa

Continuous Human Action Recognition for Human-Machine Interaction: A Review [article]

Harshala Gammulle, David Ahmedt-Aristizabal, Simon Denman, Lachlan Tychsen-Smith, Lars Petersson, Clinton Fookes
2022 arXiv   pre-print
Recognising actions and detecting action transitions within an input video are challenging but necessary tasks for applications that require real-time human-machine interaction.  ...  With advances in data-driven machine learning research, a wide variety of prediction models have been proposed to capture spatio-temporal features for the analysis of video streams.  ...  CornerNet [99] is a one-stage approach which detects objects represented by paired heatmaps, the top-left corner and bottom-right corner, using a stacked hourglass network [174] .  ... 
arXiv:2202.13096v1 fatcat:mczyeb5vyfgxdiubjhklwjrtlm

Conference Guide [Front matter]

2020 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV)  
Another network under Stacked Hourglass architecture is constructed to detect specific keypoints of each fish.  ...  Our TA3N first integrates spatial attention to focus on salient areas which are discriminative and transferable.  ...  , and modifies the values in the communication links to interfere in the consensus process.  ... 
doi:10.1109/icarcv50220.2020.9305477 fatcat:4h7gpoj7ljgsrlkjoyw3qcfzxi

A Revisit of Shape Editing Techniques: from the Geometric to the Neural Viewpoint [article]

Yu-Jie Yuan, Yu-Kun Lai, Tong Wu, Lin Gao, Ligang Liu
2021 arXiv   pre-print
Traditionally, the deformed shape is determined by the optimal transformation and weights for an energy term.  ...  Both traditional methods and recent neural network based methods are reviewed.  ...  The input representation is processed through a stack of 3D hourglass modules.  ... 
arXiv:2103.01694v1 fatcat:lhgswnemnbhvrazl76qhz5rhmy
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