Person

Ruofan Zhou

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Related publications (19)

NTIRE 2021 Depth Guided Image Relighting Challenge

Sabine Süsstrunk, Majed El Helou, Ruofan Zhou, Radu Timofte

Image relighting is attracting increasing interest due to its various applications. From a research perspective, image relighting can be exploited to conduct both image normalization for domain adaptation, and also for data augmentation. It also has multip ...

2021

Adaptive extreme video completion

Sabine Süsstrunk, Radhakrishna Achanta, Majed El Helou, Ruofan Zhou

A computer-implemented video completion method is proposed for reconstructing a sparsely sampled video comprising sparsely sampled video frames comprising sparse sets of picture element intensity values. The method comprises: distributing the sparse sets o ...

2021

Towards Real-World Super-Resolution using Deep Neural Networks

Ruofan Zhou

Image super-resolution reconstructs a higher-resolution image from the observed low-resolution image. In recent years, machine learning models have been widely employed and deep learning networks have achieved state-of-the-art super-resolution performance. ...

EPFL2020

Divergence-Based Adaptive Extreme Video Completion

Sabine Süsstrunk, Fabrice Jean Guibert, Majed El Helou, Ruofan Zhou, Frank Schmutz

Extreme image or video completion, where, for instance, we only retain 1% of pixels in random locations, allows for very cheap sampling in terms of the required pre-processing. The consequence is, however, a reconstruction that is challenging for humans an ...

2020

AIM 2020: Scene Relighting and Illumination Estimation Challenge

Sabine Süsstrunk, Xin Huang, Majed El Helou, Ruofan Zhou, Matthew Brown, Radu Timofte, Tongtong Zhao, Shanshan Zhao, Yu Zhu, Yuzhong Liu

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 proposed solutions and final evaluation results over the 3 challenge tracks. The f ...

2020

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Deep image relighting is gaining more interest lately, as it allows photo enhancement through illumination-specific retouching without human effort. Aside from aesthetic enhancement and photo montage, image relighting is valuable for domain adaptation, whe ...

2020

Stochastic Frequency Masking to Improve Super-Resolution and Denoising Networks

Sabine Süsstrunk, Majed El Helou, Ruofan Zhou

Super-resolution and denoising are ill-posed yet fundamental image restoration tasks. In blind settings, the degradation kernel or the noise level are unknown. This makes restoration even more challenging, notably for learning-based methods, as they tend t ...

2020

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In fluorescence microscopy live-cell imaging, there is a critical trade-off between the signal-to-noise ratio and spatial resolution on one side, and the integrity of the biological sample on the other side. To obtain clean high-resolution (HR) images, one ...

2020

AIM 2019 Challenge on Image Extreme Super-Resolution: Methods and Results

Liying Lu, Majed El Helou, Ruofan Zhou, Xin Yang, Wei Li, Radu Timofte, Jia Yu, Muhammad Haris, Peng Yi, Jiayi Ma, Hanwen Liu

This paper reviews the AIM 2019 challenge on extreme image super-resolution, the problem of restoring of rich details in a low resolution image. Compared to previous, this challenge focuses on an extreme upscaling factor, x16, and employs the novel DIVerse ...

IEEE COMPUTER SOC2019

Multi-modal Spectral Image Super-Resolution

Sabine Süsstrunk, Ruofan Zhou, Fayez Lahoud

Recent advances have shown the great power of deep convolutional neural networks (CNN) to learn the relationship between low and high-resolution image patches. However, these methods only take a single-scale image as input and require large amount of data ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

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