pipeline-notes.md

CSA pipeline illustration

This is an editable vector schematic of the modern two-stage implementation. It was drawn directly as SVG, using Figure 2 of the ICCV 2019 paper as the visual reference. The drawing uses thin feature-map plates, dashed U-Net skip connections, a gray rough network, red/blue refinement layers, and a yellow CSA layer. It has no generated artwork, gradients, shadows, or decorative cards.

Source and export

• pipeline.svg is the editable source (1840 × 650 viewBox).
• pipeline.png is its 2× raster export (3680 × 1300), used where SVG rendering is unavailable.
• The SVG embeds the existing examples/masked.png, examples/mask.png, and examples/expected.png without changing their pixels. The right image is the released model's actual output, not a ground-truth target or a generated illustration.

Implementation mapping

The graph was checked against Stage2InpaintingModel.forward and RefinementNetwork.forward:

1. The rough network receives the masked RGB input.
2. A coarse composite combines rough predictions inside the hole with the known input pixels.
3. Refinement receives the coarse composite concatenated with the masked input.
4. CSA operates at the 32 × 32 encoder level for 256 × 256 inputs; it is not the 1 × 1 bottleneck.
5. Final compositing retains known input pixels and uses refinement predictions inside the hole.

Feature-map plates denote layer groups; they are not a complete operator-by-operator specification. The bottom notes describe the modern sequential training recipe: rough is trained first, then frozen during refinement training. LPIPS is a modern addition. The original paper already includes reconstruction, consistency, and relativistic average least-squares GAN supervision.

The schematic follows the paper's visual conventions; it is not a reproduction of its original figure or a claim that this release exactly reproduces the paper's training protocol.