20 citations · 45 across the 7 of their papers we have counts for
7 papers
AIM 2020: Scene Relighting and Illumination Estimation Challenge
Majed El Helou, Ruofan Zhou, Sabine Süsstrunk +34
We review the AIM 2020 challenge on virtual image relighting and illumination estimation. This paper presents the novel VIDIT dataset used in the challenge and the different propos…
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…
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…
Image Super-Resolution via Attention based Back Projection Networks
Zhi-Song Liu, Li-Wen Wang, Chu-Tak Li +2
Deep learning based image Super-Resolution (SR) has shown rapid development due to its ability of big data digestion. Generally, deeper and wider networks can extract richer featur…
Hierarchical Back Projection Network for Image Super-Resolution
Zhi-Song Liu, Li-Wen Wang, Chu-Tak Li +1
Deep learning based single image super-resolution methods use a large number of training datasets and have recently achieved great quality progress both quantitatively and qualitat…