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ORCIDJanis Postels
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2020 – today
- 2024
[b1]Janis Postels:
Epistemic Uncertainty Quantification and 3D Point Cloud Generation Using Explicit Generative Models. ETH Zurich, Zürich, Switzerland, 2024- [i10]Mengya Liu, Ajad Chhatkuli, Janis Postels, Luc Van Gool, Federico Tombari:
Self-supervised Shape Completion via Involution and Implicit Correspondences. CoRR abs/2409.15939 (2024) - 2023
- [j1]Mengya Liu, Ajad Chhatkuli, Janis Postels, Luc Van Gool, Federico Tombari:
Unsupervised Template Warp Consistency for Implicit Surface Correspondences. Comput. Graph. Forum 42(2): 77-87 (2023) - [i9]Janis Postels, Yannick Strümpler, Klara Reichard, Luc Van Gool, Federico Tombari:
3D Compression Using Neural Fields. CoRR abs/2311.13009 (2023) - 2022
- [c8]Janis Postels, Martin Danelljan, Luc Van Gool, Federico Tombari:
ManiFlow: Implicitly Representing Manifolds with Normalizing Flows. 3DV 2022: 84-93 - [c7]Tao Sun
, Mattia Segù, Janis Postels, Yuxuan Wang, Luc Van Gool, Bernt Schiele, Federico Tombari, Fisher Yu:
SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation. CVPR 2022: 21339-21350 - [c6]Yannick Strümpler, Janis Postels, Ren Yang, Luc Van Gool, Federico Tombari:
Implicit Neural Representations for Image Compression. ECCV (26) 2022: 74-91 - [c5]Janis Postels, Mattia Segù, Tao Sun, Luca Daniel Sieber, Luc Van Gool, Fisher Yu, Federico Tombari:
On the Practicality of Deterministic Epistemic Uncertainty. ICML 2022: 17870-17909 - [i8]Tao Sun, Mattia Segù, Janis Postels, Yuxuan Wang, Luc Van Gool, Bernt Schiele, Federico Tombari, Fisher Yu:
SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation. CoRR abs/2206.08367 (2022) - [i7]Janis Postels, Martin Danelljan, Luc Van Gool, Federico Tombari:
ManiFlow: Implicitly Representing Manifolds with Normalizing Flows. CoRR abs/2208.08932 (2022) - 2021
- [c4]Janis Postels, Mengya Liu, Riccardo Spezialetti, Luc Van Gool, Federico Tombari:
Go with the Flows: Mixtures of Normalizing Flows for Point Cloud Generation and Reconstruction. 3DV 2021: 1249-1258 - [c3]Diego Martín Arroyo, Janis Postels, Federico Tombari:
Variational Transformer Networks for Layout Generation. CVPR 2021: 13642-13652 - [c2]Matthäus Heer, Janis Postels, Xiaoran Chen, Ender Konukoglu, Shadi Albarqouni:
The OOD Blind Spot of Unsupervised Anomaly Detection. MIDL 2021: 286-300 - [i6]Diego Martín Arroyo, Janis Postels, Federico Tombari:
Variational Transformer Networks for Layout Generation. CoRR abs/2104.02416 (2021) - [i5]Janis Postels, Mengya Liu, Riccardo Spezialetti, Luc Van Gool, Federico Tombari:
Go with the Flows: Mixtures of Normalizing Flows for Point Cloud Generation and Reconstruction. CoRR abs/2106.03135 (2021) - [i4]Janis Postels, Mattia Segù, Tao Sun, Luc Van Gool, Fisher Yu, Federico Tombari:
On the Practicality of Deterministic Epistemic Uncertainty. CoRR abs/2107.00649 (2021) - [i3]Yannick Strümpler, Janis Postels, Ren Yang, Luc Van Gool, Federico Tombari:
Implicit Neural Representations for Image Compression. CoRR abs/2112.04267 (2021) - 2020
- [i2]Janis Postels, Hermann Blum, Cesar Cadena, Roland Siegwart, Luc Van Gool, Federico Tombari:
Quantifying Aleatoric and Epistemic Uncertainty Using Density Estimation in Latent Space. CoRR abs/2012.03082 (2020)
2010 – 2019
- 2019
- [c1]Janis Postels, Francesco Ferroni, Huseyin Coskun, Nassir Navab, Federico Tombari:
Sampling-Free Epistemic Uncertainty Estimation Using Approximated Variance Propagation. ICCV 2019: 2931-2940 - [i1]Janis Postels, Francesco Ferroni, Huseyin Coskun, Nassir Navab, Federico Tombari:
Sampling-free Epistemic Uncertainty Estimation Using Approximated Variance Propagation. CoRR abs/1908.00598 (2019)
Coauthor Index
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