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Multimodal Unsupervised Image-To-Image Translation
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Multimodal unsupervised image-to-image translation is the task of producing multiple translations to one domain from a single image in another domain.
<span style="color:grey; opacity: 0.6">( Image credit: MUNIT: Multimodal UNsupervised Image-to-image Translation )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
A Style-aware Discriminator for Controllable Image Translation
Image-to-image Translation via Hierarchical Style Disentanglement
Lifespan Age Transformation Synthesis
High-Resolution Daytime Translation Without Domain Labels
StarGAN v2: Diverse Image Synthesis for Multiple Domains
Breaking the cycle -- Colleagues are all you need
Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection
Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis
Semi-Supervised Image-to-Image Translation
Latent Filter Scaling for Multimodal Unsupervised Image-to-Image Translation
Diverse Image-to-Image Translation via Disentangled Representations
Multimodal Unsupervised Image-to-Image Translation
Toward Multimodal Image-to-Image Translation
In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Unsupervised Image-to-Image Translation Networks
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