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03/14/2021
BreakingBED – Breaking Binary and Efficient Deep Neural Networks by Adversarial Attacks
Deploying convolutional neural networks (CNNs) for embedded applications...
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01/07/2021
L2PF – Learning to Prune Faster
Various applications in the field of autonomous driving are based on con...
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11/03/2020
A Deep Temporal Fusion Framework for Scene Flow Using a Learnable Motion Model and Occlusions
Motion estimation is one of the core challenges in computer vision. With...
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10/21/2020
MonoComb: A Sparse-to-Dense Combination Approach for Monocular Scene Flow
Contrary to the ongoing trend in automotive applications towards usage o...
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08/21/2020
SSGP: Sparse Spatial Guided Propagation for Robust and Generic Interpolation
Interpolation of sparse pixel information towards a dense target resolut...
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07/27/2020
ALF: Autoencoder-based Low-rank Filter-sharing for Efficient Convolutional Neural Networks
Closing the gap between the hardware requirements of state-of-the-art co...
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06/15/2020
Binary DAD-Net: Binarized Driveable Area Detection Network for Autonomous Driving
Driveable area detection is a key component for various applications in ...
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04/12/2019
An Empirical Evaluation Study on the Training of SDC Features for Dense Pixel Matching
Training a deep neural network is a non-trivial task. Not only the tunin...
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04/05/2019
SDC - Stacked Dilated Convolution: A Unified Descriptor Network for Dense Matching Tasks
Dense pixel matching is important for many computer vision tasks such as...
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02/26/2019
