37 citations · 90 across the 8 of their papers we have counts for
8 papers
Variational AutoEncoder for Reference based Image Super-Resolution
Zhi-Song Liu, Wan-Chi Siu, Li-Wen Wang
In this paper, we propose a novel reference based image super-resolution approach via Variational AutoEncoder (RefVAE). Existing state-of-the-art methods mainly focus on single ima…
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
Pengxu Wei, Hannan Lu, Radu Timofte +68
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020. This ch…
DeepGIN: Deep Generative Inpainting Network for Extreme Image Inpainting
Chu-Tak Li, Wan-Chi Siu, Zhi-Song Liu +2
The degree of difficulty in image inpainting depends on the types and sizes of the missing parts. Existing image inpainting approaches usually encounter difficulties in completing…
Deep Relighting Networks for Image Light Source Manipulation
Li-Wen Wang, Wan-Chi Siu, Zhi-Song Liu +2
Manipulating the light source of given images is an interesting task and useful in various applications, including photography and cinematography. Existing methods usually require…
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr, Martin Danelljan, Radu Timofte +43
This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world settin…
Unsupervised Real Image Super-Resolution via Generative Variational AutoEncoder
Zhi-Song Liu, Wan-Chi Siu, Li-Wen Wang +3
Benefited from the deep learning, image Super-Resolution has been one of the most developing research fields in computer vision. Depending upon whether using a discriminator or not…