no code implementations • 21 Dec 2021 • Hao Zhao, Rene Ranftl, Yurong Chen, Hongbin Zha
Here we propose an end-to-end method that directly predicts parametric layouts from an input panorama image.
no code implementations • NeurIPS 2021 • Feihu Zhang, Philip Torr, Rene Ranftl, Stephan Richter
We present an approach to contrastive representation learning for semantic segmentation.
no code implementations • 29 Sep 2021 • Nina Wiedemann, Antonio Loquercio, Matthias Müller, Rene Ranftl, Davide Scaramuzza
We evaluate our approach on several complex systems and tasks, and experimentally analyze the advantages over model-free and model-based methods in terms of performance and sample efficiency.
1 code implementation • CVPR 2021 • Kaicheng Yu, Rene Ranftl, Mathieu Salzmann
Weight sharing has become a de facto standard in neural architecture search because it enables the search to be done on commodity hardware.
3 code implementations • CVPR 2020 • Christopher Choy, Junha Lee, Rene Ranftl, Jaesik Park, Vladlen Koltun
Many problems in science and engineering can be formulated in terms of geometric patterns in high-dimensional spaces.
no code implementations • 9 Mar 2020 • Kaicheng Yu, Rene Ranftl, Mathieu Salzmann
Weight sharing promises to make neural architecture search (NAS) tractable even on commodity hardware.
no code implementations • ICLR 2019 • Adel Bibi, Bernard Ghanem, Vladlen Koltun, Rene Ranftl
In particular, we show that a forward pass through a standard dropout layer followed by a linear layer and a non-linear activation is equivalent to optimizing a convex optimization objective with a single iteration of a $\tau$-nice Proximal Stochastic Gradient method.
no code implementations • ECCV 2018 • Rene Ranftl, Vladlen Koltun
We present an approach to robust estimation of fundamental matrices from noisy data contaminated by outliers.
no code implementations • CVPR 2016 • Rene Ranftl, Vibhav Vineet, Qifeng Chen, Vladlen Koltun
We present an approach to dense depth estimation from a single monocular camera that is moving through a dynamic scene.