Fake Video

Fake videos, or deepfakes, are increasingly sophisticated synthetic media posing significant threats to security and trust. Current research focuses on developing robust detection methods, employing various architectures like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and vision transformers, often incorporating multimodal analysis (audio-visual) and temporal information to identify inconsistencies between genuine and manipulated videos. These efforts are driven by the need to mitigate the spread of misinformation and enhance the authenticity verification of digital media, with a growing emphasis on generalizability across different deepfake generation techniques and robustness to various forms of video manipulation. The development of large-scale datasets and standardized evaluation metrics is also a key area of focus to facilitate progress in this rapidly evolving field.