3 papers
cs.CV2025
Investigating self-supervised representations for audio-visual deepfake detection
Dragos-Alexandru Boldisor, Stefan Smeu, Dan Oneata +1
Self-supervised representations excel at many vision and speech tasks, but their potential for audio-visual deepfake detection remains underexplored. Unlike prior work that uses th…
cs.CV2024
Circumventing shortcuts in audio-visual deepfake detection datasets with unsupervised learning
Stefan Smeu, Dragos-Alexandru Boldisor, Dan Oneata +1
Good datasets are essential for developing and benchmarking any machine learning system. Their importance is even more extreme for safety critical applications such as deepfake det…
cs.CV2024
DeCLIP: Decoding CLIP representations for deepfake localization
Stefan Smeu, Elisabeta Oneata, Dan Oneata
Generative models can create entirely new images, but they can also partially modify real images in ways that are undetectable to the human eye. In this paper, we address the chall…