activity
20162022
most citedFast Scene Understanding for Autonomous Driving

49 citations · 62 across the 5 of their papers we have counts for

collaborators

19 papers

eess.IV2022

Multi-Bracket High Dynamic Range Imaging with Event Cameras

Nico Messikommer, Stamatios Georgoulis, Daniel Gehrig +5

Modern high dynamic range (HDR) imaging pipelines align and fuse multiple low dynamic range (LDR) images captured at different exposure times. While these methods work well in stat…

cs.CV20227 cited

Time Lens++: Event-based Frame Interpolation with Parametric Non-linear Flow and Multi-scale Fusion

Stepan Tulyakov, Alfredo Bochicchio, Daniel Gehrig +3

Recently, video frame interpolation using a combination of frame- and event-based cameras has surpassed traditional image-based methods both in terms of performance and memory effi…

cs.CV2022

FoV-Net: Field-of-View Extrapolation Using Self-Attention and Uncertainty

Liqian Ma, Stamatios Georgoulis, Xu Jia +1

The ability to make educated predictions about their surroundings, and associate them with certain confidence, is important for intelligent systems, like autonomous vehicles and ro…

cs.CV2021

TimeLens: Event-based Video Frame Interpolation

Stepan Tulyakov, Daniel Gehrig, Stamatios Georgoulis +4

State-of-the-art frame interpolation methods generate intermediate frames by inferring object motions in the image from consecutive key-frames. In the absence of additional informa…

cs.CV2021

Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation

Suman Saha, Anton Obukhov, Danda Pani Paudel +4

We present an approach for encoding visual task relationships to improve model performance in an Unsupervised Domain Adaptation (UDA) setting. Semantic segmentation and monocular d…

cs.CV2021

Exploring Relational Context for Multi-Task Dense Prediction

David Bruggemann, Menelaos Kanakis, Anton Obukhov +2

The timeline of computer vision research is marked with advances in learning and utilizing efficient contextual representations. Most of them, however, are targeted at improving mo…