arXiv:1910.00579
Unsupervised Projection Networks for Generative Adversarial Networks
원문 초록
We propose the use of unsupervised learning to train projection networks that project onto the latent space of an already trained generator. We apply our method to a trained StyleGAN, and use our projection network to perform image super-resolution and clustering of images into semantically identifiable groups.
함께 살펴볼 논문
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IM-LUT: Interpolation Mixing Look-Up Tables for Image Super-Resolution
Structural Similarity-Inspired Unfolding for Lightweight Image Super-Resolution
DACN: Dual-Attention Convolutional Network for Hyperspectral Image Super-Resolution
A Tree-guided CNN for image super-resolution
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-Resolution
Trustworthy Image Super-Resolution via Generative Pseudoinverse
토론
이 논문과 연결된 포럼 글이 아직 없습니다.