Table 2.
Summary of the reviewed architectures for recaptured image forensics (RF), CG image detection (CGI), GAN-generated images detection (GAN), and Source social networks identification (SSN). Lap denotes Laplacian filter, GR denotes the Guassian residuals. Col + Tex is the combination of Cb,Cr and the texture filtering responses by Schmidt filter bank. Filters denotes a combination of three kinds of high-pass filters used for steganalysis and DCT-His denotes the histogram of DCT coefficents.
| Architecture | Input size | Preprocessing | Convolutional part | Fully connected part | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| N Layers | Activation | Pooling | BN | GAP / Stats | N Layers | Activation | Dropout | ||||
| RF | B1 [50] | N × N × 3 | Lap | 5 | ReLU | Avg | ✓ | GAP | - | - | - |
| B2 [53] | 64 × 64 × 1 | GR | 6 | L-ReLU | - | ✓ | - | 1 | L-ReLU | - | |
| B3 [52] | 32 × 32 × 3 | Conv | 2 | ReLU | Avg | ✓ | - | 1 | ? | - | |
| B4 [51] | 64 × 64 × 3 | - | 6 | ReLU | Max | - | - | 2 | ReLU | ✓ | |
| CGI | C1 [54] | 32 × 32 × 3 | - | 6 | ReLU | - | - | - | 2 | ReLU + BN | - |
| C2 [55] | 96 × 96 | Col + Tex | 4 | ReLU | Avg | ✓ | - | 1 | ? | ✓ | |
| C3 [56] | 650 × 650 | Filters | 5 | ReLU | Avg | ✓ | GAP | - | - | - | |
| C4 [57] | NxN | Conv | 3 | ReLU | Max | ✓ | - | 1 | ReLU | ✓ | |
| C5 [58] | 100 × 100 × 1 | - | 2 | - | - | - | Stats | 1 | ReLU | ✓ | |
| GAN | D1 [59] | N × N × 3 | Lap | 3 | L-ReLU | Max | - | - | 2 | L-ReLU | - |
| SSN | E1 [60] | 64 × 64 | DCT-His | 2 | ReLU | Max | - | - | 1 | ReLU | ✓ |
| E2 [61] | 64 × 64 | PRNU | 4 | ReLU | Max | - | - | 1 | ReLU | ✓ | |