CA-IDD is the first diffusion model for face swapping that integrates multi-modal cross-attention guidance from identity embeddings, gaze, and facial parsing to achieve better identity consistency and an FID of 11.73 over GAN baselines.
High- fidelity diffusion face swapping with id-constrained facial conditioning
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CA-IDD: Cross-Attention Guided Identity-Conditional Diffusion for Identity-Consistent Face Swapping
CA-IDD is the first diffusion model for face swapping that integrates multi-modal cross-attention guidance from identity embeddings, gaze, and facial parsing to achieve better identity consistency and an FID of 11.73 over GAN baselines.