Janis Postels

ETH Zurich — Switzerland

Computer Science · Physical Sciences

7h-index379citations18works1.52yr avg
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Research Topics

Computer Graphics and Visualization Techniques(7), 3D Shape Modeling and Analysis(7), Anomaly Detection Techniques and Applications(6), Adversarial Robustness in Machine Learning(5), Advanced Vision and Imaging(4)

Publications18 total

Self-supervised Shape Completion via Involution and Implicit Correspondences
Lecture notes in computer science·2024· 2 cited
Self-supervised Shape Completion via Involution and Implicit Correspondences
arXiv (Cornell University)·2024· 1 citedOpen Access
3D Compression Using Neural Fields
arXiv (Cornell University)·2023Open Access
Unsupervised Template Warp Consistency for Implicit Surface Correspondences
Computer Graphics Forum·2023· 3 citedOpen Access
ManiFlow: Implicitly Representing Manifolds with Normalizing Flows
2022· 2 cited
ManiFlow: Implicitly Representing Manifolds with Normalizing Flows
arXiv (Cornell University)·2022Open Access
SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation
arXiv (Cornell University)·2022· 1 citedOpen Access
SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)·2022· 166 citedOpen Access
Implicit Neural Representations for Image Compression
Lecture notes in computer science·2022· 125 cited
Implicit Neural Representations for Image Compression
arXiv (Cornell University)·2021· 17 citedOpen Access
Go with the Flows: Mixtures of Normalizing Flows for Point Cloud Generation and Reconstruction
2021 International Conference on 3D Vision (3DV)·2021· 1 citedOpen Access
On the Practicality of Deterministic Epistemic Uncertainty
Repository for Publications and Research Data (ETH Zurich)·2021· 6 citedOpen Access
Variational Transformer Networks for Layout Generation
2021· 8 citedOpen Access
The OOD Blind Spot of Unsupervised Anomaly Detection.
Medical Imaging with Deep Learning·2021· 6 cited
Quantifying Aleatoric and Epistemic Uncertainty Using Density Estimation in Latent Space.
arXiv (Cornell University)·2020· 14 citedOpen Access
The Hidden Uncertainty in a Neural Networks Activations
arXiv (Cornell University)·2020· 12 citedOpen Access
Sampling-Free Epistemic Uncertainty Estimation Using Approximated Variance Propagation
2019· 13 citedOpen Access
Sampling-free Epistemic Uncertainty Estimation Using Approximated\n Variance Propagation
arXiv (Cornell University)·2019· 2 citedOpen Access

Frequent Co-authors

Federico Tombari(17), Luc Van Gool(14), Yannick Strümpler(4), Mattia Segù(3), Fisher Yu(3), Mengya Liu(3), Ajad Chhatkuli(3), Tao Sun(2), Bernt Schiele(2), Ren Yang(2), Hermann Blum(2), César Cadena(2), Roland Siegwart(2), Francesco Ferroni(2), Huseyin Coskun(2), Nassir Navab(2), Martin Danelljan(2), Yuxuan Wang(1), Diego Martìn Arroyo(1), Matthäus Heer(1)