activity
20172021
most citedCo-Planar Parametrization for Stereo-SLAM and Visual-Inertial Odometry

32 citations · 123 across the 21 of their papers we have counts for

collaborators

55 papers

cs.CV2021

SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimation

Yan Di, Fabian Manhardt, Gu Wang +3

Directly regressing all 6 degrees-of-freedom (6DoF) for the object pose (e.g. the 3D rotation and translation) in a cluttered environment from a single RGB image is a challenging p…

cs.CV20211 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.CV20212 cited

SRH-Net: Stacked Recurrent Hourglass Network for Stereo Matching

Hongzhi Du, Yanyan Li, Yanbiao Sun +2

The cost aggregation strategy shows a crucial role in learning-based stereo matching tasks, where 3D convolutional filters obtain state of the art but require intensive computation…

cs.CV2021

TSDF++: A Multi-Object Formulation for Dynamic Object Tracking and Reconstruction

Margarita Grinvald, Federico Tombari, Roland Siegwart +1

The ability to simultaneously track and reconstruct multiple objects moving in the scene is of the utmost importance for robotic tasks such as autonomous navigation and interaction…

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.CV20218 cited

SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences

Shun-Cheng Wu, Johanna Wald, Keisuke Tateno +2

Scene graphs are a compact and explicit representation successfully used in a variety of 2D scene understanding tasks. This work proposes a method to incrementally build up semanti…