Object-based forgery detection in surveillance video using capsule network
Author:
Funder
Nvidia Corporation
Department of Science and Technology, Government of India
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-021-03511-3.pdf
Reference41 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. Amerini I, Becarelli R, Caldelli R, Del Mastio A (2014) Splicing forgeries localization through the use of first digit features. In: IEEE international workshop on information forensics and security (WIFS), pp 143–148
3. Amerini I, Galteri L, Caldelli R, Del Bimbo A (2019) Deepfake video detection through optical flow based CNN. In: IEEE/CVF international conference on computer vision workshop (ICCVW), pp 1205–1207
4. 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, (ICISS 2018). Springer, pp 304–317
5. Bhartiya G, Jalal AS (2017) Forgery detection using feature-clustering in recompressed JPEG images. Multim Tools Appl 76(20):20799–20814
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