Research map / Image generation / Editing and style transfer
Invertible Conditional GAN Revisited: Photo-to-Manga Face Translation with Modern Architectures (Student Abstract)
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use IcFGAN instead of GNR | photo-to-manga face translation · Tezuka Dataset | FID: 43.04 -> 33.15 | Helped |
| Use IcFGAN instead of UI2I Style | photo-to-manga face translation · Tezuka Dataset | FID: 114.10 -> 33.15 | Helped |
| Use IcFGAN instead of UI2I Style | photo-to-manga face translation · User Study 1 | preference for target manga style: 28.12% -> 51.16% | Helped |
| Use IcFGAN instead of UI2I Style | photo-to-manga face translation · User Study 2 | identify translation from source photo: 62.22% -> 64.60% | Helped |
Closest papers by meaning
- MangaGAN: Unpaired Photo-to-Manga Translation Based on The Methodology of Manga Drawing (AAAI 2021 · similarity 0.88)
- Fine-Grained Face Swapping via Regional GAN Inversion (CVPR 2023 · similarity 0.87)
- Controllable 3D Face Generation with Conditional Style Code Diffusion (AAAI 2024 · similarity 0.86)
- In-N-Out: Faithful 3D GAN Inversion with Volumetric Decomposition for Face Editing (CVPR 2024 · similarity 0.85)
- WarpGAN: Warping-Guided 3D GAN Inversion with Style-Based Novel View Inpainting (NeurIPS 2025 · similarity 0.84)
- Diffusion-driven GAN Inversion for Multi-Modal Face Image Generation (CVPR 2024 · similarity 0.84)
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