58 citations · 392 across the 30 of their papers we have counts for
8 papers · 1 filter
Seeing Beyond Appearance - Mapping Real Images into Geometrical Domains for Unsupervised CAD-based Recognition
Benjamin Planche, Sergey Zakharov, Ziyan Wu +3
While convolutional neural networks are dominating the field of computer vision, one usually does not have access to the large amount of domain-relevant data needed for their train…
PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors
Haowen Deng, Tolga Birdal, Slobodan Ilic
We present PPF-FoldNet for unsupervised learning of 3D local descriptors on pure point cloud geometry. Based on the folding-based auto-encoding of well known point pair features, P…
Keep it Unreal: Bridging the Realism Gap for 2.5D Recognition with Geometry Priors Only
Sergey Zakharov, Benjamin Planche, Ziyan Wu +3
With the increasing availability of large databases of 3D CAD models, depth-based recognition methods can be trained on an uncountable number of synthetically rendered images. Howe…
When Regression Meets Manifold Learning for Object Recognition and Pose Estimation
Mai Bui, Sergey Zakharov, Shadi Albarqouni +2
In this work, we propose a method for object recognition and pose estimation from depth images using convolutional neural networks. Previous methods addressing this problem rely on…
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC
Tolga Birdal, Umut Şimşekli, M. Onur Eken +1
We introduce Tempered Geodesic Markov Chain Monte Carlo (TG-MCMC) algorithm for initializing pose graph optimization problems, arising in various scenarios such as SFM (structure f…
Scene Coordinate and Correspondence Learning for Image-Based Localization
Mai Bui, Shadi Albarqouni, Slobodan Ilic +1
Scene coordinate regression has become an essential part of current camera re-localization methods. Different versions, such as regression forests and deep learning methods, have b…
A Minimalist Approach to Type-Agnostic Detection of Quadrics in Point Clouds
Tolga Birdal, Benjamin Busam, Nassir Navab +2
This paper proposes a segmentation-free, automatic and efficient procedure to detect general geometric quadric forms in point clouds, where clutter and occlusions are inevitable. O…
PPFNet: Global Context Aware Local Features for Robust 3D Point Matching
Haowen Deng, Tolga Birdal, Slobodan Ilic
We present PPFNet - Point Pair Feature NETwork for deeply learning a globally informed 3D local feature descriptor to find correspondences in unorganized point clouds. PPFNet learn…