355 citations · 2.7k across the 325 of their papers we have counts for
19 papers · 1 filter
Efficient Video Semantic Segmentation with Labels Propagation and Refinement
Matthieu Paul, Christoph Mayer, Luc Van Gool +1
This paper tackles the problem of real-time semantic segmentation of high definition videos using a hybrid GPU / CPU approach. We propose an Efficient Video Segmentation(EVS) pipel…
Adversarial Feature Distribution Alignment for Semi-Supervised Learning
Christoph Mayer, Matthieu Paul, Radu Timofte
Training deep neural networks with only a few labeled samples can lead to overfitting. This is problematic in semi-supervised learning where only a few labeled samples are availabl…
GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences
Prune Truong, Martin Danelljan, Radu Timofte
Establishing dense correspondences between a pair of images is an important and general problem, covering geometric matching, optical flow and semantic correspondences. While these…
AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr, Martin Danelljan, Radu Timofte +18
This paper reviews the AIM 2019 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting,…
Frequency Separation for Real-World Super-Resolution
Manuel Fritsche, Shuhang Gu, Radu Timofte
Most of the recent literature on image super-resolution (SR) assumes the availability of training data in the form of paired low resolution (LR) and high resolution (HR) images or…
AIM 2019 Challenge on Image Demoireing: Methods and Results
Shanxin Yuan, Radu Timofte, Gregory Slabaugh +25
This paper reviews the first-ever image demoireing challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ICCV 2019. This paper desc…