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ICPR222 - Workshop on AI for Multimedia Forensics & Disinformation Detection

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AI4MFDD

2022 ICPRLink opens in a new window Workshop on Artificial Intelligence for Multimedia Forensics and Disinformation Detection


The AI4MFDD workshop is intended to disseminate recent development in AI-enabled multimedia forensics and disinformation detection. Multimedia carries not only the value of its content but also its value in digital forensics for combating crimes and fraudulent activities. With its apparent commercial value, multimedia piracy continues to be an acute issue, especially in the entertainment industry, despite the earnest search for solutions in the past two decades. Deliberate manipulations of multimedia content for malicious purposes have also been a prevailing problem in many walks of life. With the phenomenal leap of artificial intelligence and machine learning (deep learning in particular) in recent years, realistically forged multimedia is appearing as disinformation and fake news that are impacting social justice at the personal level and major political campaigns and national security at the national level, as well as affecting the stability of international relationships at the global level. In light of the aforementioned issues, this proposed workshop is of great interest to the community and beyond.

 Topics of interest include, but are not limited to:

  • Deepfake detection
  • Multimedia (including social media) provenance attribution and identification
  • Multimedia forgery detection
  • Deepfake dataset creation
  • Multimedia content integrity verification through intrinsic and extrinsic data
  • Multimedia copyright protection through intrinsic and extrinsic data
  • Anti-forensics and counter anti-forensics measures
  • Disinformation detection
  • Sybil nodes and sybil network detection
  • Analysis of disinformation creation and distribution through social networks
  • Disinformation dataset creation
  • Analysis and detection of propaganda and hoaxes detection

The CFP can be downloaded hereLink opens in a new window