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A Coarse-to-fine Deep Convolutional Neural Network Framework for Frame Duplication Detection and Localization in Forged Videos [article]

Chengjiang Long, Arslan Basharat, Anthony Hoogs
2019 arXiv   pre-print
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

Maryam Munawar, Iram Noreen
2021 Intelligent Automation and Soft Computing  
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

Kalyani Dhananjay Kadam, Swati Ahirrao, Ketan Kotecha, Suneet Kumar Gupta
2022 Computational Intelligence and Neuroscience  
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

Yasmin M. Alsakar, Nagham E. Mekky, Noha A. Hikal
2021 Journal of Imaging  
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  
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]

Luisa Verdoliva
2020 arXiv   pre-print
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

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
; 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]

Di Tang, Zhe Zhou, Yinqian Zhang, Kehuan Zhang
2018 arXiv   pre-print
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

Daniel Mas Montserrat
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]

Abhishek Gupta
2020 arXiv   pre-print
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]

Sanita Reinsone, Anda Baklāne, Jānis Daugavietis
2020 Zenodo  
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]

V. Abrol, O. Absil, P.-A. Absil, S. Anthoine, P. Antoine, T. Arildsen, N. Bertin, F. Bleichrodt, J. Bobin, A. Bol, A. Bonnefoy, F. Caltagirone, V. Cambareri (+47 others)
2016 arXiv   pre-print
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

Zhengqi Li
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

Abhijit Das, University, My, Michael Blumenstein
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

Roman Vinzenz Feldbauer
2020 unpublished
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