Causes of artifacts
Conventional methods cause ghosting effects at the edges of the hair due to full image feature fusion, and CanonSwap uses a targeted solution.
Precision Control Program
- Adaptive Space Mask: PIM module generates pixel-level masks via UNet with 0.1px boundary control accuracy
- Background protection mechanisms: Enable VGG-19 feature matching validation for non-facial regions, and retain original pixels if differences exceed thresholds
- Edge feathering technique: Achieving a natural hairline transition with Laplacian pyramid blending
Parameter tuning recommendations
Key parameter settings: 1) Set mask_dilation to 3-5px 2) Enable background_fix=True 3) Use x4 oversampling for 4K footage. The test shows that the border artifacts of 98.7% can be reduced, and the SSIM index is improved to 0.974.
This answer comes from the articleCanonSwap: A tool for realizing high-fidelity face-swapping in videoThe
May not be reproduced without permission:AI productivity tools " How to eliminate unintended artifacts in the background area after face swap?
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