DFDC

Researchers proposed lightweight Swin-Transformer-based architectures for detecting GAN-generated synthetic faces, with a hybrid EfficientNet-B0+Swin model achieving 99% accuracy and 99.44% recall on …

BitMind Forensics (BMF), trained through Bittensor SN34's open adversarial competition, achieves 0.936 AUC on Sumsub's original images and 0.872 pooled AUC over its full manipulation battery, outperfo…