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VersatileMotion: A Unified Framework for Motion Synthesis and Comprehension
Zeyu Ling, Bo Han, Shiyang Li +3
Large language models (LLMs) are, by design, inherently capable of multi-task learning: through a unified next-token prediction paradigm, they can naturally address a wide variety…
Stacking Brick by Brick: Aligned Feature Isolation for Incremental Face Forgery Detection
Jikang Cheng, Zhiyuan Yan, Ying Zhang +5
The rapid advancement of face forgery techniques has introduced a growing variety of forgeries. Incremental Face Forgery Detection (IFFD), involving gradually adding new forgery da…
Can We Leave Deepfake Data Behind in Training Deepfake Detector?
Jikang Cheng, Zhiyuan Yan, Ying Zhang +3
The generalization ability of deepfake detectors is vital for their applications in real-world scenarios. One effective solution to enhance this ability is to train the models with…
IDRetracor: Towards Visual Forensics Against Malicious Face Swapping
Jikang Cheng, Jiaxin Ai, Zhen Han +4
The face swapping technique based on deepfake methods poses significant social risks to personal identity security. While numerous deepfake detection methods have been proposed as…
DePatch: Towards Robust Adversarial Patch for Evading Person Detectors in the Real World
Jikang Cheng, Ying Zhang, Zhongyuan Wang +2
Recent years have seen an increasing interest in physical adversarial attacks, which aim to craft deployable patterns for deceiving deep neural networks, especially for person dete…
ED: Explicit Data-level Debiasing for Deepfake Detection
Jikang Cheng, Ying Zhang, Qin Zou +4
Learning intrinsic bias from limited data has been considered the main reason for the failure of deepfake detection with generalizability. Apart from the discovered content and spe…