1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.CV2021★ 1 cited
KLIEP-based Density Ratio Estimation for Semantically Consistent Synthetic to Real Images Adaptation in Urban Traffic Scenes
Artem Savkin, Federico Tombari
Synthetic data has been applied in many deep learning based computer vision tasks. Limited performance of algorithms trained solely on synthetic data has been approached with domai…
cs.CV2021
Content Disentanglement for Semantically Consistent Synthetic-to-Real Domain Adaptation
Mert Keser, Artem Savkin, Federico Tombari
Synthetic data generation is an appealing approach to generate novel traffic scenarios in autonomous driving. However, deep learning perception algorithms trained solely on synthet…
cs.CV2018
Automated Scene Flow Data Generation for Training and Verification
Oliver Wasenmüller, René Schuster, Didier Stricker +6
Scene flow describes the 3D position as well as the 3D motion of each pixel in an image. Such algorithms are the basis for many state-of-the-art autonomous or automated driving fun…