PowerPoint 演示文稿

PowerPoint 演示文稿

Background Task Fashion image inpaint ing Some conceptions Visual compatibility Diversity Framework

Two-stage model Shape generation network. Appearance generation network Base on segmentation map Shape generation network. Input An 18-channel pose heatmap A binary mask of face and hai

r An 8-channel parsing map (wi th a missing region) And A latent vector encode from V AE to encourages diversity. Shape generation network. Latent vector in shape gene

rator Train: Zs encoded from a binary ma sk of missing region by Es. Test: Ys encoded from contextual r egion during testing by Ecs. Visual compatibility relationships To learn the correlations between the shapes of synthesized garments and contextual garments.

Enables compatibility aware sampling during inference when xs is not available we can simply sample ys from Ecs(xc) Appearance generation network Input A RGB image of face and hair A RGB image (with missing regio n) An 8-channel parsing map

And A latent vector encode from VAE to encourages diversity. Loss Perception + Gram matrix for rec onstruction KL divergence term.

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