activity
20162019
most citedSemantic Instance Segmentation with a Discriminative Loss Function

444 citations · 1.2k across the 15 of their papers we have counts for

collaborators

27 papers

cs.CV2019

Learning a Curve Guardian for Motorcycles

Simon Hecker, Alexander Liniger, Henrik Maurenbrecher +2

Up to 17% of all motorcycle accidents occur when the rider is maneuvering through a curve and the main cause of curve accidents can be attributed to inappropriate speed and wrong i…

cs.CV20194 cited

3D Appearance Super-Resolution with Deep Learning

Yawei Li, Vagia Tsiminaki, Radu Timofte +2

We tackle the problem of retrieving high-resolution (HR) texture maps of objects that are captured from multiple view points. In the multi-view case, model-based super-resolution (…

cs.CV2019100 cited

The 2019 DAVIS Challenge on VOS: Unsupervised Multi-Object Segmentation

Sergi Caelles, Jordi Pont-Tuset, Federico Perazzi +3

We present the 2019 DAVIS Challenge on Video Object Segmentation, the third edition of the DAVIS Challenge series, a public competition designed for the task of Video Object Segmen…

cs.CV2019

DynamoNet: Dynamic Action and Motion Network

Ali Diba, Vivek Sharma, Luc Van Gool +1

In this paper, we are interested in self-supervised learning the motion cues in videos using dynamic motion filters for a better motion representation to finally boost human action…

cs.CV20195 cited

A Novel BiLevel Paradigm for Image-to-Image Translation

Liqian Ma, Qianru Sun, Bernt Schiele +1

Image-to-image (I2I) translation is a pixel-level mapping that requires a large number of paired training data and often suffers from the problems of high diversity and strong cate…

cs.CV20176 cited

Error Correction for Dense Semantic Image Labeling

Yu-Hui Huang, Xu Jia, Stamatios Georgoulis +2

Pixelwise semantic image labeling is an important, yet challenging, task with many applications. Typical approaches to tackle this problem involve either the training of deep netwo…