Search Results for author:
Found 10 papers, 0 papers with code
BreakingBED -- Breaking Binary and Efficient Deep Neural Networks by Adversarial Attacks
The distilled models exhibit their strength against all white box attacks with an exception of C&W.
L2PF -- Learning to Prune Faster
In this context, we present Learning to Prune Faster which details a multi-task, try-and-learn method, discretely learning redundant filters of the CNN and a continuous action of how long the layers have to be fine-tuned.
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.
MonoComb: A Sparse-to-Dense Combination Approach for Monocular Scene Flow
Contrary to the ongoing trend in automotive applications towards usage of more diverse and more sensors, this work tries to solve the complex scene flow problem under a monocular camera setup, i. e. using a single sensor.
SSGP: Sparse Spatial Guided Propagation for Robust and Generic Interpolation
Interpolation of sparse pixel information towards a dense target resolution finds its application across multiple disciplines in computer vision.
ALF: Autoencoder-based Low-rank Filter-sharing for Efficient Convolutional Neural Networks
Model compression techniques, such as pruning, are emphasized among other optimization methods for solving this problem.
Binary DAD-Net: Binarized Driveable Area Detection Network for Autonomous Driving
The driveable area detection, posed as a two class segmentation task, can be efficiently modeled with slim binary networks.
An Empirical Evaluation Study on the Training of SDC Features for Dense Pixel Matching
Not only the tuning of hyperparameters, but also the gathering and selection of training data, the design of the loss function, and the construction of training schedules is important to get the most out of a model.
SDC - Stacked Dilated Convolution: A Unified Descriptor Network for Dense Matching Tasks
Our network has a very large receptive field and avoids striding layers to maintain spatial resolution.
SceneFlowFields++: Multi-frame Matching, Visibility Prediction, and Robust Interpolation for Scene Flow Estimation
State-of-the-art scene flow algorithms pursue the conflicting targets of accuracy, run time, and robustness.
