2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDIMA-ELI-1.3
Paper Title A Generative Adversarial Framework for Optimizing Image Matting and Harmonization Simultaneously
Authors Xuqian Ren, Beijing Institute of Technology, China; Yifan Liu, University of Adelaide, Australia; Chunlei Song, Beijing Institute of Technology, China
SessionIMA-ELI-1: Imaging and Media Applications + Electronic Imaging
LocationArea F
Session Time:Monday, 20 September, 15:30 - 17:00
Presentation Time:Monday, 20 September, 15:30 - 17:00
Presentation Poster
Topic Imaging and Media Applications: Image and video processing over networks
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Image matting and image harmonization are two important tasks in image composition. Image matting, aiming to achieve foreground boundary details, and image harmonization, aiming to make the background compatible with the foreground, are both promising yet challenging tasks. Previous works consider optimizing these two tasks separately, which may lead to a sub-optimal solution. We propose to optimize matting and harmonization simultaneously to get better performance on both the two tasks and achieve more natural results. We propose a new Generative Adversarial (GAN) framework which optimizing the matting network and the harmonization network based on a self-attention discriminator. The discriminator is required to distinguish the natural images from different types of fake synthesis images. Extensive experiments on our constructed dataset demonstrate the effectiveness of our proposed method.