Eddy Ilg

According to our database¹, Eddy Ilg authored at least 30 papers between 2014 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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In proceedings

Article

PhD thesis

Dataset

Other

Links

On csauthors.net:

Bibliography

2024

latentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstruction.

[BibT_eX]

[DOI]

CoRR, 2024

Recent Trends in 3D Reconstruction of General Non-Rigid Scenes.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Quantum-Hybrid Stereo Matching With Nonlinear Regularization and Spatial Pyramids.

[BibT_eX]

[DOI]

Cameron Braunstein

Eddy Ilg

Vladislav Golyanik

CoRR, 2023

Neural Point Cloud Diffusion for Disentangled 3D Shape and Appearance Generation.

[BibT_eX]

[DOI]

CoRR, 2023

Neural Parametric Gaussians for Monocular Non-Rigid Object Reconstruction.

[BibT_eX]

[DOI]

CoRR, 2023

SimNP: Learning Self-Similarity Priors Between Neural Points.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

ERF: Explicit Radiance Field Reconstruction From Scratch.

[BibT_eX]

[DOI]

CoRR, 2022

Recurrent Video Restoration Transformer with Guided Deformable Attention.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

NinjaDesc: Content-Concealing Visual Descriptors via Adversarial Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Analysis and Mitigations of Reverse Engineering Attacks on Local Feature Descriptors.

[BibT_eX]

[DOI]

CoRR, 2021

Mitigating Reverse Engineering Attacks on Local Feature Descriptors.

[BibT_eX]

[DOI]

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

TLIO: Tight Learned Inertial Odometry.

[BibT_eX]

[DOI]

Anastasios I. Mourikis

Kostas Daniilidis

Vijay Kumar

Jakob Engel

IEEE Robotics Autom. Lett., 2020

Domain Adaptation of Learned Features for Visual Localization.

[BibT_eX]

[DOI]

CoRR, 2020

Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstruction.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Domain Adaptation of Learned Featuresfor Visual Localization.

[BibT_eX]

[DOI]

Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019

Estimating optical flow with convolutional neural networks.

[BibT_eX]

[DOI]

Eddy Ilg

PhD thesis, 2019

Lucid Data Dreaming for Video Object Segmentation.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2019

Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

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

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2018

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

[BibT_eX]

[DOI]

Osama Makansi

Eddy Ilg

Thomas Brox

CoRR, 2018

Uncertainty Estimates for Optical Flow with Multi-Hypotheses Networks.

[BibT_eX]

[DOI]

CoRR, 2018

Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow Estimation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

Uncertainty Estimates and Multi-hypotheses Networks for Optical Flow.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

2017

Lucid Data Dreaming for Object Tracking.

[BibT_eX]

[DOI]

CoRR, 2017

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

[BibT_eX]

[DOI]

Osama Makansi

Eddy Ilg

Thomas Brox

Proceedings of the Pattern Recognition - 39th German Conference, 2017

DeMoN: Depth and Motion Network for Learning Monocular Stereo.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

FlowNet: Learning Optical Flow with Convolutional Networks.

[BibT_eX]

[DOI]

Patrick van der Smagt

Daniel Cremers

Thomas Brox

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014

Reconstruction of rigid body models from motion distorted laser range data using optical flow.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Eddy Ilg

Timeline

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On csauthors.net:

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