58 citations · 241 across the 26 of their papers we have counts for
5 papers · 1 filter
Autolabeling 3D Objects with Differentiable Rendering of SDF Shape Priors
Sergey Zakharov, Wadim Kehl, Arjun Bhargava +1
We present an automatic annotation pipeline to recover 9D cuboids and 3D shapes from pre-trained off-the-shelf 2D detectors and sparse LIDAR data. Our autolabeling method solves an…
3D Object Instance Recognition and Pose Estimation Using Triplet Loss with Dynamic Margin
Sergey Zakharov, Wadim Kehl, Benjamin Planche +2
In this paper, we address the problem of 3D object instance recognition and pose estimation of localized objects in cluttered environments using convolutional neural networks. Insp…
HomebrewedDB: RGB-D Dataset for 6D Pose Estimation of 3D Objects
Roman Kaskman, Sergey Zakharov, Ivan Shugurov +1
Among the most important prerequisites for creating and evaluating 6D object pose detectors are datasets with labeled 6D poses. With the advent of deep learning, demand for such da…
DeceptionNet: Network-Driven Domain Randomization
Sergey Zakharov, Wadim Kehl, Slobodan Ilic
We present a novel approach to tackle domain adaptation between synthetic and real data. Instead, of employing "blind" domain randomization, i.e., augmenting synthetic renderings w…
DPOD: 6D Pose Object Detector and Refiner
Sergey Zakharov, Ivan Shugurov, Slobodan Ilic
In this paper we present a novel deep learning method for 3D object detection and 6D pose estimation from RGB images. Our method, named DPOD (Dense Pose Object Detector), estimates…