2019
DOI: 10.5815/ijigsp.2019.12.01
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Three-dimensional Region Forgery Detection and Localization in Videos

Abstract: Nowadays, with the extensive use of cameras in many areas of life, every day millions of videos are uploaded on the internet. In addition, with rapidly developing video editing software applications, it has become easier to forge any video. These software applications have made it challenging to detect forged videos, especially with forged videos have duplication of three-dimensional (3-D) regions. Recently, there has been increased interest in detecting forged videos, but there are very limited studies to det… Show more

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Cited by 3 publications
(2 citation statements)
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“…Hau Nguyen et al [41] are retraining the existing CNN models that were trained on the ImageNet dataset in order to identify video interframe forgeries. Te suggested techniques are based on retrained CNN models that take use of spatial-temporal correlations in a video to efectively identify interframe forgeries.…”
Section: Discussion Of Cnn Based Approaches Ganguly Et Almentioning
confidence: 99%
“…Hau Nguyen et al [41] are retraining the existing CNN models that were trained on the ImageNet dataset in order to identify video interframe forgeries. Te suggested techniques are based on retrained CNN models that take use of spatial-temporal correlations in a video to efectively identify interframe forgeries.…”
Section: Discussion Of Cnn Based Approaches Ganguly Et Almentioning
confidence: 99%
“…Because of the huge amount of video data and the close correlation between adjoining frames, digital videos are usually stored and transmitted in compressed form [5,6]. Video coding techniques have evolved over the previous decade to facilitate improved data compression while ensuring high visual quality [7,8]. Fig.…”
Section: Introductionmentioning
confidence: 99%