Weather Attribute-Aware Multi-Scale Image Generation with Residual Learning

Wei Ta Chu, Li Wei Huang

研究成果: Conference contribution

摘要

We present image generation networks to generate images conforming to specified weather attributes. Taking weather attributes as the conditions, the proposed networks generate scene images with the help of a guided reference image. To generate higher-resolution images, we construct a multi-scale generation framework consisting of a global generator and a local enhancer. Furthermore, we integrate the idea of residual learning into the proposed framework, and aim at generating fine-grained texture. The evaluation shows performance comparison both from quantitative and qualitative perspectives. A comprehensive study including the impact of different attributes and extension of the proposed models is also provided. This work is kind of hybrid approach among various image generation studies.

原文English
主出版物標題Indo - Taiwan 2nd International Conference on Computing, Analytics and Networks, Indo-Taiwan ICAN 2020 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面238-243
頁數6
ISBN(電子)9781728149998
DOIs
出版狀態Published - 2020 二月
事件Indo - Taiwan 2nd International Conference on Computing, Analytics and Networks, Indo-Taiwan ICAN 2020 - Rajpura, Punjab, India
持續時間: 2020 二月 72020 二月 15

出版系列

名字Indo - Taiwan 2nd International Conference on Computing, Analytics and Networks, Indo-Taiwan ICAN 2020 - Proceedings

Conference

ConferenceIndo - Taiwan 2nd International Conference on Computing, Analytics and Networks, Indo-Taiwan ICAN 2020
國家India
城市Rajpura, Punjab
期間20-02-0720-02-15

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management

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