资源分类
》 资源 》论文》High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

2019-10-16 | |  55 |   43 |   0
Abstract We present a new method for synthesizing highresolution photo-realistic images from semantic label maps using conditional generative adversarial networks (conditional GANs). Conditional GANs have enabled a variety of applications, but the results are often limited to lowresolution and still far from realistic. In this work, we generate 2048 × 1024 visually appealing results with a novel adversarial loss, as well as new multi-scale generator and discriminator architectures. Furthermore, we extend our

上一篇：Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning

下一篇：Im2Flow: Motion Hallucination from Static Images for Action Recognition

用户评价
全部评价

热门资源

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Rating-Boosted La...

    The performance of a recommendation system reli...