Publications de Ruofan Zhou | EPFL Graph Search

A comparative study on wavelets and residuals in deep super resolution

Sabine Süsstrunk, Majed El Helou, Ruofan Zhou, Fayez Lahoud

Despite the advances in single-image super resolution using deep convolutional networks, the main problem remains unsolved: recovering fine texture details. Recent works in super resolution aim at modifying the training of neural networks to enable the rec ...

2019

PIRM2018 Challenge on Spectral Image Super-Resolution: Methods and Results

Sabine Süsstrunk, Tong Zhang, Dong Liu, Ruofan Zhou, Fayez Lahoud, Radu Timofte, Chang Chen, Soumik Sarkar

In this paper, we describe the Perceptual Image Restoration and Manipulation (PIRM) workshop challenge on spectral image super-resolution, motivate its structure and conclude on results obtained by the participants. The challenge is one of the first of its ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Kernel Modeling Super-Resolution on Real Low-Resolution Images

Sabine Süsstrunk, Ruofan Zhou

Deep convolutional neural networks (CNNs), trained on corresponding pairs of high- and low-resolution images, achieve state-of-the-art performance in single-image super- resolution and surpass previous signal-processing based approaches. However, their per ...

IEEE COMPUTER SOC2019

Drone Shadow Tracking

Sabine Süsstrunk, Majed El Helou, Ruofan Zhou

Aerial videos taken by a drone not too far above the surface may contain the drone's shadow projected on the scene. This deteriorates the aesthetic quality of videos. With the presence of other shadows, shadow removal cannot be directly applied, and the sh ...

2019

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 ...

Springer2018

PIRM2018 Challenge on Spectral Image Super-Resolution: Methods and Results

Sabine Süsstrunk, Tong Zhang, Dong Liu, Ruofan Zhou, Fayez Lahoud, Radu Timofte, Chang Chen, Soumik Sarkar

In this paper, we describe the Perceptual Image Restoration and Manipulation (PIRM) workshop challenge on spectral image super- resolution, motivate its structure and conclude on results obtained by the participants. The challenge is one of the first of it ...

2018

NTIRE 2018 Challenge on Spectral Reconstruction from RGB Images

Bing Zhang, Lei Zhang, Majed El Helou, Dong Liu, Ruofan Zhou, Fayez Lahoud, Marjan Shahpaski, Radu Timofte, Chang Chen, Soumik Sarkar, Himanshu Sharma, Yigit Baran Can

This paper reviews the first challenge on spectral image reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3channel RGB image. The challenge was divided into 2 tracks: the "Clean" track sought HS recove ...

IEEE2018

Deep Residual Network for Joint Demosaicing and Super- Resolution

Sabine Süsstrunk, Radhakrishna Achanta, Ruofan Zhou

The two classic image restoration tasks, demosaicing and super-resolution, have traditionally always been studied indepen- dently. That is sub-optimal as sequential processing, demosaic- ing and then super-resolution, may lead to amplification of ar- tifac ...

Society for Imaging Science and Technology ( IS&T )2018

NTIRE 2018 Challenge on Spectral Reconstruction from RGB Images

Bing Zhang, Lei Zhang, Majed El Helou, Dong Liu, Ruofan Zhou, Fayez Lahoud, Marjan Shahpaski, Radu Timofte, Chang Chen, Soumik Sarkar, Himanshu Sharma

This paper reviews the first challenge on spectral image reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3- channel RGB image. The challenge was divided into 2 tracks: the “Clean” track sought HS reco ...

2018

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