{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/mtn-forensic-analysis-of-mp4-video-files","title":"MTN: Forensic Analysis of MP4 Video Files Using Graph Neural Networks","arxiv_id":null,"date":"2023-06-17","proceeding":"IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2023 6","authors":["Z Xiang","AKS Yadav","P Bestagini","S Tubaro","EJ Delp"],"abstract":"MP4 video files are stored using a tree data structure. These trees contain rich information that can be used for forensic analysis. In this paper, we propose MP4 Tree Network (MTN), an approach based on an end-to-end Graph Neural Networks (GNNs) that is used for forensic analysis of MP4 trees. MTN does not use any video pixel data. MTN is trained using Self-Supervised Learning (SSL), which generates semantic-preserving node embeddings for the nodes in an MP4 tree. We also propose a data augmentation technique for MP4 trees, which helps train MTN in data-scarce scenarios. MTN achieves good performance across 3 video forensics tasks on the EVA-7K dataset. We show that MTN can gain more comprehensive understanding about the MP4 trees and is more robust to potential attacks compared to existing methods.","url_abs":"https://openaccess.thecvf.com/content/CVPR2023W/WMF/html/Xiang_MTN_Forensic_Analysis_of_MP4_Video_Files_Using_Graph_Neural_CVPRW_2023_paper.html","url_pdf":"https://openaccess.thecvf.com/content/CVPR2023W/WMF/papers/Xiang_MTN_Forensic_Analysis_of_MP4_Video_Files_Using_Graph_Neural_CVPRW_2023_paper.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"mtn-forensic-analysis-of-mp4-video-files","repo_url":"https://gitlab.com/viper-purdue/mtn","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"self-supervised-learning","task_name":"Self-Supervised Learning"},{"task_slug":"video-forensics","task_name":"Video Forensics"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}