Daquan Liu — accepted AI-conference papers

2022

Deep Image-Based Illumination Harmonization

Zhongyun Bao, Chengjiang Long, Gang Fu, Daquan Liu, Yuanzhen Li, Jiaming Wu +1

CVPR 2022poster

Integrating a foreground object into a background scenewith illumination harmonization is an important but chal-lenging task in computer vision and augmented reality community. Existing methods mainly focus on foreground andbackground appearance consistency or the foreground object shadow generation…

Cited by 18 PDF ↗code ↗Scholar ↗

2020

ARShadowGAN: Shadow Generative Adversarial Network for Augmented Reality in Single Light Scenes

Daquan Liu, Chengjiang Long, Hongpan Zhang, Hanning Yu, Xinzhi Dong, Chunxia Xiao

CVPR 2020poster

Generating virtual object shadows consistent with the real-world environment shading effects is important but challenging in computer vision and augmented reality applications. To address this problem, we propose an end-to-end Generative Adversarial Network for shadow generation named ARShadowGAN fo…

Cited by 106 PDF ↗code ↗Scholar ↗