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MT3: Meta Test-Time Training for Self-Supervised Test-Time Adaption
An unresolved problem in Deep Learning is the ability of neural networks...
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Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting – Full version
We consider a setting where multiple entities inter-act with each other ...
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Uncertainty-Based Biological Age Estimation of Brain MRI Scans
Age is an essential factor in modern diagnostic procedures. However, ass...
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Anomaly Detection Based on Selection and Weighting in Latent Space
With the high requirements of automation in the era of Industry 4.0, ano...
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Condensed Composite Memory Continual Learning
Deep Neural Networks (DNNs) suffer from a rapid decrease in performance ...
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SLPC: a VRNN-based approach for stochastic lidar prediction and completion in autonomous driving
Predicting future 3D LiDAR pointclouds is a challenging task that is use...
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End-to-end Interpretable Neural Motion Planner
In this paper, we propose a neural motion planner (NMP) for learning to ...
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PLUME: Efficient 3D Object Detection from Stereo Images
3D object detection plays a significant role in various robotic applicat...
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Auto4D: Learning to Label 4D Objects from Sequential Point Clouds
In the past few years we have seen great advances in 3D object detection...
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Diverse Complexity Measures for Dataset Curation in Self-driving
Modern self-driving autonomy systems heavily rely on deep learning. As a...
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Learning Joint 2D-3D Representations for Depth Completion
In this paper, we tackle the problem of depth completion from RGBD data....
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Multi-Task Multi-Sensor Fusion for 3D Object Detection
In this paper we propose to exploit multiple related tasks for accurate ...
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Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net
In this paper we propose a novel deep neural network that is able to joi...
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HDNET: Exploiting HD Maps for 3D Object Detection
In this paper we show that High-Definition (HD) maps provide strong prio...
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Deep Continuous Fusion for Multi-Sensor 3D Object Detection
In this paper, we propose a novel 3D object detector that can exploit bo...
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Recovering and Simulating Pedestrians in the Wild
Sensor simulation is a key component for testing the performance of self...
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Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving
In this paper, we propose an end-to-end self-driving network featuring a...
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Feature Selection Using Batch-Wise Attenuation and Feature Mask Normalization
Feature selection is generally used as one of the most important pre-pro...
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Investigating Cross-Domain Losses for Speech Enhancement
Recent years have seen a surge in the number of available frameworks for...
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Age-Net: An MRI-Based Iterative Framework for Biological Age Estimation
The concept of biological age (BA) - although important in clinical prac...
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V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction
In this paper, we explore the use of vehicle-to-vehicle (V2V) communicat...
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DSDNet: Deep Structured self-Driving Network
In this paper, we propose the Deep Structured self-Driving Network (DSDN...
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Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction
We present a novel method for testing the safety of self-driving vehicle...
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End-to-end Contextual Perception and Prediction with Interaction Transformer
In this paper, we tackle the problem of detecting objects in 3D and fore...
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Fully Automated and Standardized Segmentation of Adipose Tissue Compartments by Deep Learning in Three-dimensional Whole-body MRI of Epidemiological Cohort Studies
Purpose: To enable fast and reliable assessment of subcutaneous and visc...
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Force myography benchmark data for hand gesture recognition and transfer learning
Force myography has recently gained increasing attention for hand gestur...
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RadarNet: Exploiting Radar for Robust Perception of Dynamic Objects
We tackle the problem of exploiting Radar for perception in the context ...
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Learning Lane Graph Representations for Motion Forecasting
We propose a motion forecasting model that exploits a novel structured m...
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Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning
Post-hoc calibration is a common approach for providing high-quality con...
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LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World
We tackle the problem of producing realistic simulations of LiDAR point ...
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PnPNet: End-to-End Perception and Prediction with Tracking in the Loop
We tackle the problem of joint perception and motion forecasting in the ...
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Physically Realizable Adversarial Examples for LiDAR Object Detection
Modern autonomous driving systems rely heavily on deep learning models t...
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SELD-TCN: Sound Event Localization Detection via Temporal Convolutional Networks
The understanding of the surrounding environment plays a critical role i...
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Infinitely Wide Graph Convolutional Networks: Semi-supervised Learning via Gaussian Processes
Graph convolutional neural networks (GCNs) have recently demonstrated pr...
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On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration
Uncertainty estimates help to identify ambiguous, novel, or anomalous in...
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Perceptual Speech Enhancement via Generative Adversarial Networks
Automatic speech recognition (ASR) systems are of vital importance nowad...
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ipA-MedGAN: Inpainting of Arbitrarily Regions in Medical Modalities
Local deformations in medical modalities are common phenomena due to a m...
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Organ-based Age Estimation based on 3D MRI Scans
Individuals age differently depending on a multitude of different factor...
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Unsupervised Adversarial Correction of Rigid MR Motion Artifacts
Motion is one of the main sources for artifacts in magnetic resonance (M...
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Enhancing Flood Impact Analysis using Interactive Retrieval of Social Media Images
The analysis of natural disasters such as floods in a timely manner ofte...
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PathRank: A Multi-Task Learning Framework to Rank Paths in Spatial Networks
Modern navigation services often provide multiple paths connecting the s...
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Eigenfunction Behavior and Adaptive Finite Element Approximations of Nonlinear Eigenvalue Problems in Quantum Physics
In this paper, we investigate a class of nonlinear eigenvalue problems r...
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Localizing Catastrophic Forgetting in Neural Networks
Artificial neural networks (ANNs) suffer from catastrophic forgetting wh...
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2-bit Model Compression of Deep Convolutional Neural Network on ASIC Engine for Image Retrieval
Image retrieval utilizes image descriptors to retrieve the most similar ...
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Open-Set Recognition Using Intra-Class Splitting
This paper proposes a method to use deep neural networks as end-to-end o...
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Unsupervised Medical Image Translation Using Cycle-MedGAN
Image-to-image translation is a new field in computer vision with multip...
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An Adversarial Super-Resolution Remedy for Radar Design Trade-offs
Radar is of vital importance in many fields, such as autonomous driving,...
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PIXOR: Real-time 3D Object Detection from Point Clouds
We address the problem of real-time 3D object detection from point cloud...
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Deep One-Class Classification Using Data Splitting
This paper introduces a generic method which enables to use conventional...
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Active Learning for One-Class Classification Using Two One-Class Classifiers
This paper introduces a novel, generic active learning method for one-cl...
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