Over the last few decades, rapid progress in AI, machine learning, and deep learning has
resulted in new techniques and various tools for manipulating multimedia. Though the …

Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …

Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …

We present dynamic neural radiance fields for modeling the appearance and dynamics of a
human face. Digitally modeling and reconstructing a talking human is a key building-block …

In this paper, we analyse the generalization ability of binary classifiers for the task of
deepfake detection. We find that the stumbling block to their generalization is caused by the …

In this work we propose Identity Consistency Transformer, a novel face forgery detection
method that focuses on high-level semantics, specifically identity information, and detecting …

Existing face forgery detection models try to discriminate fake images by detecting only
spatial artifacts (eg, generative artifacts, blending) or mainly temporal artifacts (eg, flickering …

One of the most pressing challenges for the detection of face-manipulated videos is
generalising to forgery methods not seen during training while remaining effective under …

Audio-driven talking-head synthesis is a popular research topic for virtual human-related
applications. However, the inflexibility and inefficiency of existing methods, which …

The creation or manipulation of facial appearance through deep generative approaches,
known as DeepFake, have achieved significant progress and promoted a wide range of …