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CVPR2020顶会

Semantic Pyramid for Image Generation

Assaf Shocher, Yossi Gandelsman, Inbar Mosseri, Michal Yarom, Michal Irani, William T. Freeman, Tali Dekel

2020年份
19顶会引用

摘要

Semantic Pyramid for Image Generation. We introduce a new image generative model that is designed and trained to leverage the hierarchical space of deep-features learned by a pre-trained classification network. Our model provides a unified versatile framework for various image generation and manipulation tasks, including: (a) generating images with a controllable extent of semantic similarity to a reference image, obtained by reconstructing images from different layers of a classification model; (b) generating realistic image samples from unnatural reference image such as line drawings; (c) semantically compositing different images, and (d) controlling the semantic content of an image by enforcing a new, modified class label.

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