Deep feature based forgery detection in video using parallel convolutional neural network: VFID-Net-Reference-Cited by-同舟云学术

Deep feature based forgery detection in video using parallel convolutional neural network: VFID-Net

Published:2022-07-14 Issue:29 Volume:81 Page:42223-42240
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Kumar Vinay^ORCID,Gaur Manish,kansal Vineet

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-021-11448-0.pdf

Reference32 articles.

1. Aghamaleki JA, Behrad A (2016) Inter-frame video forgery detection and localization using intrinsic effects of double compression on quantization errors of video coding. Signal Process Image Commun 47:289–302

2. Baghel N, Raikwar SC, Bhatnagar C (2020) Image conditioned keyframe-based video summarization using object detection. arXiv preprint. https://arxiv.org/abs/2009.05269

3. Bakas J, Naskar R (2018) A digital forensic technique for inter–frame video forgery detection based on 3D CNN. In: International conference on information systems security. Springer, Cham

4. Bakas J, Naskar R, Dixit R (2019) Detection and localization of inter-frame video forgeries based on inconsistency in correlation distribution between Haralick coded frames. Multimedia Tools Appl 78(4):4905–4935

5. Bakas J, Naskar R, Bakshi S (2021) Detection and localization of inter-frame forgeries in videos based on macroblock variation and motion vector analysis. Comput Electr Eng 89:106929

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Real‐time object‐removal tampering localization in surveillance videos by employing YOLO‐V8;Journal of Forensic Sciences;2024-04-04

2. RETRACTED: Detecting video forgery: A machine learning approach for consistency analysis of video frames;Journal of Intelligent & Fuzzy Systems;2024-03-05

3. A Light Weight Depthwise Separable Layer Optimized CNN Architecture for Object-Based Forgery Detection in Surveillance Videos;The Computer Journal;2024-02-11

4. A comprehensive analysis of digital video forensics techniques and challenges;Iran Journal of Computer Science;2023-12-11

5. Forged Video Detection Using Deep Learning: A SLR;Applied Computational Intelligence and Soft Computing;2023-10-25