Research map / Image generation / Editing and style transfer
Spatially-Invariant Style-Codes Controlled Makeup Transfer
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use spatially invariant part-specific style-codes instead of pixel-wise correspondence | SCGAN · Makeup Transfer (MT) dataset; misaligned and rotated faces | visual quality and transfer correctness | Helped |
| Add an MLP to map initial style-code Z into W (ablation) | SCGAN · Part-specific lip makeup transfer | part-specific disentanglement | Helped |
| Use AdaIN layers in all three fusion blocks instead of only the first block (ablation) | SCGAN · Part-specific lip makeup transfer | makeup transfer strength | Helped |
| Add local perceptual loss (ablation) | SCGAN · Makeup Transfer (MT) dataset | local consistency and visual quality | Helped |
| Use SCGAN rather than BeautyGAN, LADN, or PSGAN | Makeup transfer · Aligned, misaligned, and rotated image pairs | user preference for visual quality and precise transfer | Helped |
Closest papers by meaning
- PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer (CVPR 2020 · similarity 0.90)
- Content-Style Decoupling for Unsupervised Makeup Transfer without Generating Pseudo Ground Truth (CVPR 2024 · similarity 0.85)
- Makeup Prior Models for 3D Facial Makeup Estimation and Applications (CVPR 2024 · similarity 0.85)
- CLeaR: A Unified Framework for Resolving the Leakage–Degradation Dilemma in Style Transfer (NeurIPS 2026 · similarity 0.84)
- What to Preserve and What to Transfer: Faithful, Identity-Preserving Diffusion-based Hairstyle Transfer (AAAI 2025 · similarity 0.84)
- SHMT: Self-supervised Hierarchical Makeup Transfer via Latent Diffusion Models (NeurIPS 2024 · similarity 0.84)
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