Event
Ph.D. Dissertation Defense: Peng Zhou
Friday, November 6, 2020
8:45 a.m.-10:45 a.m.
Zoom link: https://us04web.zoom.us/j/7512278074?pwd=NDdnbzZXTmxXM3lIWjA2K1doci9mUT09
Maria Hoo
301 405 3681
mch@umd.edu
Committee:
Title: Deep Learning for Forensics
Time/Date: Friday, November 6. 2020 at 8:45-10:45 am
The advent of media sharing platforms and the easy availability of advanced photo or video editing software have resulted in a large quantity of manipulated images and videos being shared on the internet. While the intent behind such manipulations varies widely, concerns on the spread of fake news and misinformation is growing. Therefore, detecting manipulation has become an emerging necessity. Different from traditional classification, semantic object detection or segmentation, manipulation detection/classification pays more attention to low-level tampering artifacts than to semantic content. The main challenges in this problem include (a) investigating features to reveal tampering artifacts, (b) developing generic models which are robust to a large scale of post-processing methods, (c) applying algorithms to higher resolution in real scenarios and (d) handling the new emerging manipulation techniques. In this dissertation, we propose approaches to tackling these challenges.