Can We Leave Deepfake Data Behind in Training Deepfake Detector? Jikang Cheng
–Neural Information Processing Systems
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 manually-blended data, which we termed "blendfake", encouraging models to
Neural Information Processing Systems
Oct-9-2025, 21:23:00 GMT
- Country:
- Asia > China
- Guangdong Province > Shenzhen (0.04)
- Hong Kong (0.04)
- Hubei Province > Wuhan (0.04)
- Asia > China
- Genre:
- Research Report > New Finding (0.46)
- Industry:
- Information Technology > Security & Privacy (1.00)
- Technology: