Edith Tretschk

Orcid: 0000-0002-3223-1909

Affiliations:
  • Meta, San Francisco, CA, USA
  • Max Planck Institute for Informatics, Saarbrücken, Germany (PhD)


According to our database1, Edith Tretschk authored at least 19 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
State of the Art in Dense Monocular Non-Rigid 3D Reconstruction.
Comput. Graph. Forum, May, 2023

3D-QAE: Fully Quantum Auto-Encoding of 3D Point Clouds.
CoRR, 2023

SceNeRFlow: Time-Consistent Reconstruction of General Dynamic Scenes.
CoRR, 2023

QuAnt: Quantum Annealing with Learnt Couplings.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Fully Quantum Auto-Encoding of 3D Shapes.
Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022
φ-SfT: Shape-from-Template with a Physics-Based Deformation Model.
CoRR, 2022

Advances in Neural Rendering.
Comput. Graph. Forum, 2022

Generation of Truly Random Numbers on a Quantum Annealer.
IEEE Access, 2022

$\phi$-SfT: Shape-from-Template with a Physics-Based Deformation Model.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Virtual Elastic Objects.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Video.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Deforming Scene from Monocular Video.
CoRR, 2020

DEMEA: Deep Mesh Autoencoders for Non-rigidly Deforming Objects.
Proceedings of the Computer Vision - ECCV 2020, 2020

PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations.
Proceedings of the Computer Vision - ECCV 2020, 2020

Neural Dense Non-Rigid Structure from Motion with Latent Space Constraints.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
DispVoxNets: Non-Rigid Point Set Alignment with Supervised Learning Proxies.
Proceedings of the 2019 International Conference on 3D Vision, 2019

2018
Sequential Attacks on Agents for Long-Term Adversarial Goals.
CoRR, 2018


  Loading...