Search Results for author:
Found 3 papers, 0 papers with code
Detection and Localization of Facial Expression Manipulations
Thus, it is important to develop methods that can detect manipulations in facial expressions, and localize the manipulated regions.
Facial Expression Recognition
Facial Expression Recognition (FER)
+1
Learning to identify image manipulations in scientific publications
We show that our method leads to a 90% accuracy rate of detecting duplicated images, a ~ 13% improvement in detection accuracy in comparison to other manipulation detection methods.
A Skip Connection Architecture for Localization of Image Manipulations
In order to exploit these traces in localizing the tampered regions, we propose an encoder-decoder based network where we fuse representations from early layers in the encoder (which are richer in low-level spatial cues, like edges) by skip pooling with representations of the last layer of the decoder and use for manipulation detection.
