Search Results for author: Wadim Kehl

Found 14 papers, 4 papers with code

Photo-realistic Neural Domain Randomization

no code implementations23 Oct 2022 Sergey Zakharov, Rares Ambrus, Vitor Guizilini, Wadim Kehl, Adrien Gaidon

In this paper, we show that the recent progress in neural rendering enables a new unified approach we call Photo-realistic Neural Domain Randomization (PNDR).

Image Generation Monocular Depth Estimation +3

Differentiable Rendering: A Survey

no code implementations22 Jun 2020 Hiroharu Kato, Deniz Beker, Mihai Morariu, Takahiro Ando, Toru Matsuoka, Wadim Kehl, Adrien Gaidon

Deep neural networks (DNNs) have shown remarkable performance improvements on vision-related tasks such as object detection or image segmentation.

Image Segmentation object-detection +2

Autolabeling 3D Objects with Differentiable Rendering of SDF Shape Priors

1 code implementation CVPR 2020 Sergey Zakharov, Wadim Kehl, Arjun Bhargava, Adrien Gaidon

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.

3D Object Instance Recognition and Pose Estimation Using Triplet Loss with Dynamic Margin

no code implementations9 Apr 2019 Sergey Zakharov, Wadim Kehl, Benjamin Planche, Andreas Hutter, Slobodan Ilic

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.

Pose Estimation

An Octree-Based Approach towards Efficient Variational Range Data Fusion

no code implementations26 Aug 2016 Wadim Kehl, Tobias Holl, Federico Tombari, Slobodan Ilic, Nassir Navab

Volume-based reconstruction is usually expensive both in terms of memory consumption and runtime.

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