no code implementations • 9 Jul 2021 • Ashwin Raaghav Narayanan, Arber Zela, Tonmoy Saikia, Thomas Brox, Frank Hutter
Ensembles of CNN models trained with different seeds (also known as Deep Ensembles) are known to achieve superior performance over a single copy of the CNN.
1 code implementation • CVPR 2022 • Simon Schrodi, Tonmoy Saikia, Thomas Brox
We show how these mistakes can be rectified in order to make optical flow networks robust to physical patch-based attacks.
no code implementations • ICCV 2021 • Tonmoy Saikia, Cordelia Schmid, Thomas Brox
CNNs perform remarkably well when the training and test distributions are i. i. d, but unseen image corruptions can cause a surprisingly large drop in performance.
no code implementations • 22 Jan 2020 • Tonmoy Saikia, Thomas Brox, Cordelia Schmid
To learn models or features that generalize across tasks and domains is one of the grand goals of machine learning.
1 code implementation • ICLR 2020 • Arber Zela, Thomas Elsken, Tonmoy Saikia, Yassine Marrakchi, Thomas Brox, Frank Hutter
Differentiable Architecture Search (DARTS) has attracted a lot of attention due to its simplicity and small search costs achieved by a continuous relaxation and an approximation of the resulting bi-level optimization problem.
1 code implementation • ICCV 2019 • Tonmoy Saikia, Yassine Marrakchi, Arber Zela, Frank Hutter, Thomas Brox
In this work, we show how to use and extend existing AutoML techniques to efficiently optimize large-scale U-Net-like encoder-decoder architectures.
1 code implementation • ECCV 2018 • Eddy Ilg, Tonmoy Saikia, Margret Keuper, Thomas Brox
Making use of the estimated occlusions, we also show improved results on motion segmentation and scene flow estimation.
12 code implementations • CVPR 2017 • Eddy Ilg, Nikolaus Mayer, Tonmoy Saikia, Margret Keuper, Alexey Dosovitskiy, Thomas Brox
Particularly on small displacements and real-world data, FlowNet cannot compete with variational methods.
Dense Pixel Correspondence Estimation Optical Flow Estimation +1