Project description: In order to recover confidence in the growing digital ecosystem, especially in this new era of fake news and DeepFake, the goal of this project is to strengthen the confidence in the integrity of a digital asset through its content (e.g., videos, photos, audio). The project will investigate the latest approaches for detecting … Continued
Project description: Given the threat of deepfakes, significant efforts have been made for proposing deepfake detection methods. Nevertheless, these methods remain not sufficiently mature for real-world deployment. as they usually specialize in detecting one type of deepfakes, which limits their generalization capability, and typically rely on very large models. Hence, UNFAKE aims to provide a more … Continued
Project description: With the fast advances in Artificial intelligence, deepfake videos are becoming more accessible and realistic-looking. Their twisted use, constitutes a threat to society Existing deepfake detection methods mostly rely on exploiting discrepancies caused by a given generation method. The goal of FakeDeTeR is to define a more generic approach that captures even deepfakes … Continued
Project description: Being constrained to keep a straight face should no longer be a condition for a well-performing face recognition system. IDform proposes to robustly identify people from their faces in full dynamic conditions. The idea is to build on the success of today’s best performing face systems that use deep learning; however, instead of … Continued