Research Article
A Generative Image Inpainting Model Based on Edge and Feature Self-Arrangement Constraints
Table 1
The network parameters of the edge generator.
| Layer | Inputs (H × W × C) | Kernel size | Stride | Padding | Dilation | Activation function | Outputs (H × W × C) |
| ReflectionPad | 256 × 256 × 3 | — | — | 3 | — | — | 262 × 262 × 3 | Conv | 262 × 262 × 3 | 7 × 7 | 1 | 0 | 1 | ReLU | 256 × 256 × 64 | Conv | 256 × 256 × 64 | 4 × 4 | 2 | 1 | 1 | ReLU | 128 × 128 × 128 | Conv | 128 × 128 × 128 | 4 × 4 | 2 | 1 | 1 | ReLU | 64 × 64 × 256 |
| Residual Blocks × 8 | | | | | | | | ReflectionPad | 64 × 64 × 256 | — | — | 2 | — | — | 68 × 68 × 256 | Res-conv | 68 × 68 × 256 | 3 × 3 | 1 | 0 | 2 | ReLU | 64 × 64 × 256 | ReflectionPad | 64 × 64 × 256 | — | — | 1 | — | — | 66 × 66 × 256 | Res-conv | 66 × 66 × 256 | 3 × 3 | 1 | 0 | 1 | — | 64 × 64 × 256 | ConvTranspose | 64 × 64 × 256 | 4 × 4 | 2 | 1 | 1 | ReLU | 128 × 128 × 128 | ConvTranspose | 128 × 128 × 128 | 4 × 4 | 2 | 1 | 1 | ReLU | 256 × 256 × 64 | ReflectionPad | 256 × 256 × 64 | — | — | 3 | — | ReLU | 262 × 262 × 64 | Conv | 262 × 262 × 64 | 7 × 7 | 1 | 0 | 1 | — | 256 × 256 × 1 |
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