ExS-GAN: Synthesizing Anti-Forensics Images via Extra Supervised GAN

Adapt by adopting cleaner vehicles? — Evidence from a low-emission zone policy in Nanchang, China

“…We employed SGD optimizer [26] with a learning rate of β = 5 × 10 −4 . In training stage 1, we set ρ 1 = 1.0 and ρ 2 = 0.3 in Equation (8). For training stage 2, we set ρ 3 = 0.1 and ρ 4 = 1.0 in Equation ( 13), a = 3.0 in Equation ( 14), and ρ 5 = 0.05 and ρ 6 = 0.3 in Equation ( 16).…”

“…These sophisticated algorithms can produce synthetic facial images and videos with remarkable realism, making it increasingly difficult to distinguish between genuine and fake media. Albeit the development of various deepfake detection methods [4,5,14,17,23,24,25,36], their performance often suffers when applied to real-world scenarios due to a lack of robustness [8] and generalizability [22].…”