Search Results for author: Eddy Ilg

Found 17 papers, 10 papers with code

ERF: Explicit Radiance Field Reconstruction From Scratch

no code implementations28 Feb 2022 Samir Aroudj, Steven Lovegrove, Eddy Ilg, Tanner Schmidt, Michael Goesele, Richard Newcombe

Robustly reconstructing such a volumetric scene model with millions of unknown variables from registered scene images only is a highly non-convex and complex optimization problem.

3D Reconstruction

NinjaDesc: Content-Concealing Visual Descriptors via Adversarial Learning

no code implementations23 Dec 2021 Tony Ng, Hyo Jin Kim, Vincent Lee, Daniel DeTone, Tsun-Yi Yang, Tianwei Shen, Eddy Ilg, Vassileios Balntas, Krystian Mikolajczyk, Chris Sweeney

We let a feature encoding network and image reconstruction network compete with each other, such that the feature encoder tries to impede the image reconstruction with its generated descriptors, while the reconstructor tries to recover the input image from the descriptors.

Camera Localization Image Reconstruction

Domain Adaptation of Learned Features for Visual Localization

no code implementations21 Aug 2020 Sungyong Baik, Hyo Jin Kim, Tianwei Shen, Eddy Ilg, Kyoung Mu Lee, Chris Sweeney

We tackle the problem of visual localization under changing conditions, such as time of day, weather, and seasons.

Domain Adaptation Visual Localization

TLIO: Tight Learned Inertial Odometry

no code implementations6 Jul 2020 Wenxin Liu, David Caruso, Eddy Ilg, Jing Dong, Anastasios I. Mourikis, Kostas Daniilidis, Vijay Kumar, Jakob Engel

We show that our network, trained with pedestrian data from a headset, can produce statistically consistent measurement and uncertainty to be used as the update step in the filter, and the tightly-coupled system outperforms velocity integration approaches in position estimates, and AHRS attitude filter in orientation estimates.

FusionNet and AugmentedFlowNet: Selective Proxy Ground Truth for Training on Unlabeled Images

no code implementations20 Aug 2018 Osama Makansi, Eddy Ilg, Thomas Brox

The latter can be used as proxy-ground-truth to train a network on real-world data and to adapt it to specific domains of interest.

Optical Flow Estimation

Uncertainty Estimates and Multi-Hypotheses Networks for Optical Flow

1 code implementation ECCV 2018 Eddy Ilg, Özgün Çiçek, Silvio Galesso, Aaron Klein, Osama Makansi, Frank Hutter, Thomas Brox

Optical flow estimation can be formulated as an end-to-end supervised learning problem, which yields estimates with a superior accuracy-runtime tradeoff compared to alternative methodology.

Frame Optical Flow Estimation

What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation?

1 code implementation19 Jan 2018 Nikolaus Mayer, Eddy Ilg, Philipp Fischer, Caner Hazirbas, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox

The finding that very large networks can be trained efficiently and reliably has led to a paradigm shift in computer vision from engineered solutions to learning formulations.

Optical Flow Estimation

End-to-End Learning of Video Super-Resolution with Motion Compensation

no code implementations3 Jul 2017 Osama Makansi, Eddy Ilg, Thomas Brox

We analyze the usage of optical flow for video super-resolution and find that common off-the-shelf image warping does not allow video super-resolution to benefit much from optical flow.

Motion Compensation Optical Flow Estimation +1

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