Differences in forgery attributes of images generated in CNN-synthesized and image-editing
domains are large, and such differences make a unified image forgery detection and …

Artificial intelligence (AI) has rapidly developed through advancements in computational
power and the growth of massive datasets. However, this progress has also heightened …

The rapid development of generative AI is a double-edged sword, which not only facilitates
content creation but also makes image manipulation easier and more difficult to detect …

Explainability in artificial intelligence is crucial for restoring trust, particularly in areas like
face forgery detection, where viewers often struggle to distinguish between real and …

Large numbers of synthesized videos from diffusion models pose threats to information
security and authenticity, leading to an increasing demand for generated content detection …

The rapid advancement of deepfake technologies has sparked widespread public concern,
particularly as face forgery poses a serious threat to public information security. However …

Integrating the 3D world into large language models (3D-based LLMs) has been a
promising research direction for 3D scene understanding. However, current 3D-based LLMs …

The existing methods for Vision and Language Navigation in the Continuous Environment
(VLN-CE) commonly incorporate a waypoint predictor to discretize the environment. This …

The rapid advancement of generative models in creating highly realistic images poses
substantial risks for misinformation dissemination. For instance, a synthetic image, when …

The rapid development of photo-realistic face generation methods has raised significant
concerns in society and academia, highlighting the urgent need for robust and generalizable …