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  • Toward video tampering exposure: inferring compression parameters from pixels. 

    Johnston, Pamela; Elyan, Eyad; Jayne, Chrisina (Springer https://doi.org/10.1007/978-3-319-98204-5_4, 2018-07-27)
    JOHNSTON, P., ELYAN, E. and JAYNE, C. 2018. Toward video tampering exposure: inferring compression parameters from pixels. In Pimenidis, E. and Jayne, C. (eds.) Communications in computers and information science, 893: engineering applications of neural networks; proceedings of the 19th international engineering applications of neural networks conference (EANN 2018), 3-5 September 2018, Bristol, UK. Cham: Springer [online], pages 44-57. Available from: https://doi.org/10.1007/978-3-319-98204-5_4
    Video tampering detection remains an open problem in the field of digital media forensics. Some existing methods focus on recompression detection because any changes made to the pixels of a video will require recompression ...
  • Video tampering localisation using features learned from authentic content. 

    Johnston, Pamela; Elyan, Eyad; Jayne, Chrisina
    JOHNSTON, P., ELYAN, E. and JAYNE, C. [2019]. Video tampering localisation using features learned from authentic content. Neural computing and applications [online], (accepted).
    Video tampering detection remains an open problem in the field of digital media forensics. As video manipulation techniques advance, it becomes easier for tamperers to create convincing forgeries that can fool human eyes. ...