Multimodal Deepfakes Detection

[CFAR Distinguished Professor Lecture Series]
Multimodal Deepfakes Detection by Professor Abhinav Dhall 

Deepfakes are audio or visual samples manipulated and/or generated using deep learning-based techniques. In spite of a large number of useful applications of synthetic data, misinformation can be easily spread with deepfakes. 

In this talk, Prof Abhinav Dhall from Monash University will discuss the issues which may arise due to the nefarious use of deepfakes and provide a brief overview on methods to identify deepfakes. He will be sharing his recent work in deepfakes detection inspired by human implicit and explicit signals. Moving forward with classifying deepfakes, Prof Dhall will also discuss the problem of localisation in temporal dimension.

Prof Abhinav Dhall is leading the Centre for Data Science at Indian Institute of Technology (IIT) Ropar and an adjunct senior lecturer at Monash University. He received his PhD in Computer Science from the Australian National University and held postdoctoral positions at the University of Canberra and the University of Waterloo. His research interests are in affective computing, computer vision and multimodal systems. He is also the Associate Editor of the IEEE Transactions on Affective Computing.