Research map / Image generation / Editing and style transfer
Unsupervised Image-to-Image Translation With Generative Prior
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add distilled generative prior to the content encoder (ablation) | GP-UNIT · Ablation evaluation | Content Consistency: 0.02 -> 0.83 | Helped |
| Add distilled generative prior to the content encoder (ablation) | GP-UNIT · Ablation evaluation | FID: 16.11 -> 15.29 | Helped |
| Add dynamic skip connections (ablation) | GP-UNIT · Ablation evaluation | Content Consistency: 0.15 -> 0.83 | Helped |
| Add dynamic skip connections (ablation) | GP-UNIT · Ablation evaluation | FID: 15.83 -> 15.29 | Helped |
| Add dynamic skip connections (ablation) | GP-UNIT · Ablation evaluation | Diversity: 0.52 -> 0.51 | No clear effect |
| Use the full coarse-to-fine GP-UNIT instead of StarGAN2 | image translation · Bird ↔ Car | FID: 29.28 -> 13.93 | Helped |
| Use the full coarse-to-fine GP-UNIT instead of StarGAN2 | image translation · Bird ↔ Car | Diversity (LPIPS): 0.58 -> 0.61 | Helped |
Closest papers by meaning
- Unsupervised Image-to-Image Translation Networks (NeurIPS 2017 · similarity 0.93)
- TraVeLGAN: Image-To-Image Translation by Transformation Vector Learning (CVPR 2019 · similarity 0.92)
- DA-GAN: Instance-Level Image Translation by Deep Attention Generative Adversarial Networks (CVPR 2018 · similarity 0.90)
- Rethinking the Paradigm of Content Constraints in Unpaired Image-to-Image Translation (AAAI 2024 · similarity 0.90)
- Latent Filter Scaling for Multimodal Unsupervised Image-To-Image Translation (CVPR 2019 · similarity 0.90)
- Self-Supervised Dense Consistency Regularization for Image-to-Image Translation (CVPR 2022 · similarity 0.90)
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