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09/05/2023
Employing Real Training Data for Deep Noise Suppression
Most deep noise suppression (DNS) models are trained with reference-base...
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08/25/2023
A Re-Parameterized Vision Transformer (ReVT) for Domain-Generalized Semantic Segmentation
The task of semantic segmentation requires a model to assign semantic la...
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04/24/2023
Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated Driving
Deep neural networks (DNNs) have proven their capabilities in many areas...
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04/18/2023
Coded Speech Quality Measurement by a Non-Intrusive PESQ-DNN
Wideband codecs such as AMR-WB or EVS are widely used in (mobile) speech...
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09/20/2022
Relaxed Attention for Transformer Models
The powerful modeling capabilities of all-attention-based transformer ar...
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06/01/2022
On the Choice of Data for Efficient Training and Validation of End-to-End Driving Models
The emergence of data-driven machine learning (ML) has facilitated signi...
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06/01/2022
Amodal Cityscapes: A New Dataset, its Generation, and an Amodal Semantic Segmentation Challenge Baseline
Amodal perception terms the ability of humans to imagine the entire shap...
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05/09/2022
Bandwidth-Scalable Fully Mask-Based Deep FCRN Acoustic Echo Cancellation and Postfiltering
Although today's speech communication systems support various bandwidths...
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05/04/2022
Does a PESQNet (Loss) Require a Clean Reference Input? The Original PESQ Does, But ACR Listening Tests Don't
Perceptual evaluation of speech quality (PESQ) requires a clean speech r...
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03/02/2022
Detecting Adversarial Perturbations in Multi-Task Perception
While deep neural networks (DNNs) achieve impressive performance on envi...
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03/02/2022
Continual BatchNorm Adaptation (CBNA) for Semantic Segmentation
Environment perception in autonomous driving vehicles often heavily reli...
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01/17/2022
Improving Performance of Semantic Segmentation CycleGANs by Noise Injection into the Latent Segmentation Space
In recent years, semantic segmentation has taken benefit from various wo...
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01/08/2022
Reconfigurable Intelligent Surface Enabled Spatial Multiplexing with Fully Convolutional Network
Reconfigurable intelligent surface (RIS) is an emerging technology for f...
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11/06/2021
Deep Noise Suppression Maximizing Non-Differentiable PESQ Mediated by a Non-Intrusive PESQNet
Speech enhancement employing deep neural networks (DNNs) for denoising a...
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09/20/2021
Description of Corner Cases in Automated Driving: Goals and Challenges
Scaling the distribution of automated vehicles requires handling various...
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07/02/2021
Relaxed Attention: A Simple Method to Boost Performance of End-to-End Automatic Speech Recognition
Recently, attention-based encoder-decoder (AED) models have shown high p...
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04/12/2021
Improving Online Performance Prediction for Semantic Segmentation
In this work we address the task of observing the performance of a seman...
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04/09/2021
SVDistNet: Self-Supervised Near-Field Distance Estimation on Surround View Fisheye Cameras
A 360 perception of scene geometry is essential for automated driving, n...
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03/31/2021
Multi-Encoder Learning and Stream Fusion for Transformer-Based End-to-End Automatic Speech Recognition
Stream fusion, also known as system combination, is a common technique i...
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03/31/2021
Y^2-Net FCRN for Acoustic Echo and Noise Suppression
In recent years, deep neural networks (DNNs) were studied as an alternat...
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03/05/2021
An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving
Systems and functions that rely on machine learning (ML) are the basis o...
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02/11/2021
Corner Cases for Visual Perception in Automated Driving: Some Guidance on Detection Approaches
Automated driving has become a major topic of interest not only in the a...
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01/11/2021
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing
Enabling autonomous driving (AD) can be considered one of the biggest ch...
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12/02/2020
From a Fourier-Domain Perspective on Adversarial Examples to a Wiener Filter Defense for Semantic Segmentation
Despite recent advancements, deep neural networks are not robust against...
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12/02/2020
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs
Deep neural networks are often not robust to semantically-irrelevant cha...
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11/17/2020
Unsupervised BatchNorm Adaptation (UBNA): A Domain Adaptation Method for Semantic Segmentation Without Using Source Domain Representations
In this paper we present a solution to the task of "unsupervised domain ...
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10/28/2020
Transferable Universal Adversarial Perturbations Using Generative Models
Deep neural networks tend to be vulnerable to adversarial perturbations,...
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08/10/2020
SynDistNet: Self-Supervised Monocular Fisheye Camera Distance Estimation Synergized with Semantic Segmentation for Autonomous Driving
State-of-the-art self-supervised learning approaches for monocular depth...
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07/16/2020
openDD: A Large-Scale Roundabout Drone Dataset
Analyzing and predicting the traffic scene around the ego vehicle has be...
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07/14/2020
Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance
Self-supervised monocular depth estimation presents a powerful method to...
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06/15/2020
Self-Supervised Domain Mismatch Estimation for Autonomous Perception
Autonomous driving requires self awareness of its perception functions. ...
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05/12/2020
Class-Incremental Learning for Semantic Segmentation Re-Using Neither Old Data Nor Old Labels
While neural networks trained for semantic segmentation are essential fo...
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04/23/2020
Improved Noise and Attack Robustness for Semantic Segmentation by Using Multi-Task Training with Self-Supervised Depth Estimation
While current approaches for neural network training often aim at improv...
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08/14/2019
Components Loss for Neural Networks in Mask-Based Speech Enhancement
Estimating time-frequency domain masks for single-channel speech enhance...
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05/23/2019
A Perceptual Weighting Filter Loss for DNN Training in Speech Enhancement
Single-channel speech enhancement with deep neural networks (DNNs) has s...
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02/25/2019
Towards Corner Case Detection for Autonomous Driving
The progress in autonomous driving is also due to the increased availabi...
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02/12/2019
GAN- vs. JPEG2000 Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation
The high amount of sensors required for autonomous driving poses enormou...
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06/25/2018