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A Coarse-to-fine Deep Convolutional Neural Network Framework for Frame Duplication Detection and Localization in Forged Videos
[article]
2019
arXiv
pre-print
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In this paper, we propose a novel coarse-to-fine framework based on deep Convolutional Neural Networks to automatically detect and localize such frame duplication. ...
Videos can be manipulated by duplicating a sequence of consecutive frames with the goal of concealing or imitating a specific content in the same video. ...
In this paper, we propose a novel coarse-to-fine deep learning framework, denoted as C2F-DCNN, for frame duplication detection and localization in forged videos. ...
arXiv:1811.10762v2
fatcat:hkbijwcgwbchnil7ws55rmxxdy
Duplicate Frame Video Forgery Detection Using Siamese-based RNN
2021
Intelligent Automation and Soft Computing
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The first step in the proposed framework is to extract the features and convert videos into frames. I3D network receives an original and a forged video to detect frame-to-frame duplication. ...
A novel deep learning framework consisting of Inflated 3D (I3D) and Siamese-based Recurrent Neural Network (RNN) is proposed to resolve the aforementioned issues. ...
The proposed framework is a deep learning approach based on Inflated 3D (I3D) network and Siamese-based Recurrent Neural Network (SRNN) for frame duplication. ...
doi:10.32604/iasc.2021.018854
fatcat:urz2ao4xfvdplh72ah5m3p5cmi
Efficient Approach towards Detection and Identification of Copy Move and Image Splicing Forgeries Using Mask R-CNN with MobileNet V1
2022
Computational Intelligence and Neuroscience
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However, the deep learning networks for handling these forgeries are expensive in terms of the high number of parameters, storage, and computational cost. ...
Therefore, there is a pressing need for effective methods for the detection and identification of forgeries. ...
. e research study in [56] uses color illumination, deep convolution neural networks, and semantic segmentation to detect and localize image splicing forgery. ...
doi:10.1155/2022/6845326
pmid:35035463
pmcid:PMC8754624
fatcat:4ff622eef5bfjac5w5i4nogjf4
Detecting and Locating Passive Video Forgery Based on Low Computational Complexity Third-Order Tensor Representation
2021
Journal of Imaging
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Experimental results and comparisons show the superiority of the proposed scheme with a precision value of up to 99% in detecting and locating both types of attacks for static as well as dynamic videos ...
Forgery affects video integrity and authenticity and has serious implications. For example, digital videos for security and surveillance purposes are used as evidence in courts. ...
Acknowledgments: The authors thank Department of Information Technology, Faculty of Computers and Information Science, Mansoura University. ...
doi:10.3390/jimaging7030047
pmid:34460703
fatcat:djbnutbzvngmpfn63roaeoj2zq
Image Tampering Detection Based on Combined Feature Extraction Methods
2020
International Journal of Advanced Trends in Computer Science and Engineering
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We propose a cross breed highlight model like convolutional neural Network System (CNN), histogram of situated slope (HOG), scale-invariant component change (sift) highlights to identify the altered areas ...
At that point the framework contains the information picture is portioned into covering squares, whereupon a HOG-CNN highlight is applied to each square. ...
IMPLEMENTATION Convolutional neural networks used for rich highlights extraction. SIFT likewise used to identify the altered picture locale. ...
doi:10.30534/ijatcse/2020/176952020
fatcat:7oqrgvewirf55dysmmiadmlfhm
Media Forensics and DeepFakes: an overview
[article]
2020
arXiv
pre-print
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This review paper aims to present an analysis of the methods for visual media integrity verification, that is, the detection of manipulated images and videos. ...
On the one hand, this opens the door to a series of exciting applications in different fields such as creative arts, advertising, film production, video games. ...
Double compression detection has been also extended to H.264 video analysis in [125] , where a two-stream neural network is proposed to analyze separately intra-coded frames and predictive frames. ...
arXiv:2001.06564v1
fatcat:b3izh3hcmrae5frbd2bv3tmlgu
Learning Neural Textual Representations for Citation Recommendation
2021
2020 25th International Conference on Pattern Recognition (ICPR)
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; Skocaj, Danijel 1532 End-To-End Training of a Two-Stage Neural Network for Defect Detection GAP: Quantifying the Generative Adversarial Set and Class Feature Applicability of Deep Neural Networks Deep ...
Feature Engineering and Stacked Echo State Networks for Musical
Onset Detection
DAY 2 -Jan 13, 2021
Hou, Zejiang; Kung, SY
2636
A Discriminant Information Approach to Deep Neural Network
Pruning ...
doi:10.1109/icpr48806.2021.9412725
fatcat:3vge2tpd2zf7jcv5btcixnaikm
Face Flashing: a Secure Liveness Detection Protocol based on Light Reflections
[article]
2018
arXiv
pre-print
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The overall accuracy of our liveness detection system is 98.8\%, and its robustness was evaluated in different scenarios. In the worst case, our system's accuracy decreased to a still-high 97.3\%. ...
To overcome these limitations, we propose a new liveness detection protocol called Face Flashing that significantly increases the bar for launching successful attacks on face authentication systems. ...
ACKNOWLEDGMENT We thank our shepherd Muhammad Naveed for his patient guidance on improving this paper, and anonymous reviewers for their insightful comments. We also want to thank Tao ...
arXiv:1801.01949v2
fatcat:vug5rlhlzbckbbdxb6lpjyz5f4
Machine Learning-Based Multimedia Analytics
2020
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Furthermore, we present multiple neural network architectures and systems for commercial logo detection, 3D pose estimation and tracking, deepfakes detection, and manipulation detection in satellite images ...
We present several image synthesis and rendering techniques to generate new images for training neural networks. ...
use a temporal-aware pipeline composed by a Convolutional Neural Network (CNN) and a Recurrent Neural Network (RNN) to detect DeepFake videos. ...
doi:10.25394/pgs.12616292.v1
fatcat:2fgi4u3oozcxblntqm32imwamu
The State of AI Ethics Report (June 2020)
[article]
2020
arXiv
pre-print
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Artificial intelligence has become the byword for technological progress and is being used in everything from helping us combat the COVID-19 pandemic to nudging our attention in different directions as ...
We cover a wide set of areas in this report spanning Agency and Responsibility, Security and Risk, Disinformation, Jobs and Labor, the Future of AI Ethics, and more. ...
Framing a machine learning approach here as an end-to-end task is problematic because it requires large amounts of labelled data and with neural network based approaches, there is little explanation offered ...
arXiv:2006.14662v1
fatcat:q76dnqzh4ja5pofurjmpmyeyey
Book of Abstracts of the Digital Humanities in the Nordic Countries 5th conference. Riga, 20–23 October 2020
[article]
2020
Zenodo
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Book of Abstracts DHN, Rīga 2020 Book of Abstracts of the Digital Humanities in the Nordic Countries 5th conference. ...
conferences/dhn2020 Editors: Sanita Reinsone, Anda Baklāne, Jānis Daugavietis Editorial assistants: Justīne Jaudzema, Ilze Ļaksa-Timinska Cover: Anete Krūmiņa Publisher: Institute of Literature, Folklore and ...
We thank the Staatsbibliothek Berlin for providing access to the Wegehaupt collection. ...
doi:10.5281/zenodo.4107117
fatcat:6ongky6p5rab7gvtawnjmp2ofm
Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16)
[article]
2016
arXiv
pre-print
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For this third edition, iTWIST'16 gathered about 50 international participants and features 8 invited talks, 12 oral presentations, and 12 posters on the following themes, all related to the theory, application ...
learning and inference; "Blind" inverse problems and dictionary learning; Optimization for sparse modelling; Information theory, geometry and randomness; Sparsity? ...
ACKNOWLEDGEMENT The authors are grateful to Dr. Bruno Cornelis for registering the data sets and for useful discussions and also to Attila Fesus, Prof. Maximiliaan Martens and Prof. ...
arXiv:1609.04167v1
fatcat:cral5owpqremninl43bksxvenu
Learning Geometry, Appearance and Motion in the Wild
2021
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In contrast, the photos we see on the Internet only constitute a single view observation for each scene; the videos often involve dynamics due to a variety of timevarying factors such as illumination changes ...
Therefore, In this thesis, I address these problems to in-the-wild scenarios by leveraging a compelling source of data: massive quantities of unlabeled photos and videos people take and upload to the Internet ...
[144, 378, 363, 9, 364, 414] also demonstrate how to automatically detect and localize arbitrary image and video forgeries in order to prevent image synthesis and editing algorithms from being mishandled ...
doi:10.7298/x53b-a512
fatcat:e5uee5uc2nbphg5bprkvkphdfa
Towards Multi-modal Sclera and Iris Biometric Recognition with Adaptive Liveness Detection
2018
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and anti-spoofing/liveness detection (which is one method to distinguish between real and fake data). ...
Regardless of the available biometrics traits, to date, no biometric system has been found to be a perfect, and which can be applied universally in a way that is robust/adaptive to change in different ...
The proposed algorithm makes a twolayered neural network Figure 5 .4. ...
doi:10.25904/1912/2705
fatcat:qb7kk42di5frjnoyfmvt3vxdsu
Hubness in the protein sequence universe
2020
unpublished
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In addition, deep networks are used to learn protein sequence vector representations, and investigated for orthologous group inference. ...
The free open source software package "scikit-hubness" for Python implements these methods to make hubness analysis and reduction available to machine learning researchers and practitioners. ...
Both of you taught me a great many things, and analyzing the intersection and union of your advice gives me yet more insight. ...
doi:10.25365/thesis.64427
fatcat:wbai3saw7nbwtjtywtr73bbky4