
Rendering Natural Camera Bokeh Effect with Deep Learning
Bokeh is an important artistic effect used to highlight the main object ...
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Data Movement Is All You Need: A Case Study on Optimizing Transformers
Transformers have become widely used for language modeling and sequence ...
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Unsupervised Lesion Detection via Image Restoration with a Normative Prior
Unsupervised lesion detection is a challenging problem that requires acc...
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Deep Learning for PostProcessing Ensemble Weather Forecasts
Quantifying uncertainty in weather forecasts typically employs ensemble ...
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Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks
In the past few years, deep learning has transformed artificial intellig...
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Finegrained Recognition: Accounting for Subtle Differences between Similar Classes
The main requisite for finegrained recognition task is to focus on subt...
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Learning Dynamical Systems using Local Stability Priors
A coupled computational approach to simultaneously learn a vector field ...
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FewShot Classification By FewIteration MetaLearning
Learning in a lowdata regime from only a few labeled examples is an imp...
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RealTime Video SuperResolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Report
Video superresolution has recently become one of the most important mob...
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Modelling the Distribution of 3D Brain MRI using a 2D Slice VAE
Probabilistic modelling has been an essential tool in medical image anal...
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(1 + ε)class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets
Anomaly detection is not an easy problem since distribution of anomalous...
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NoRegret Learning in Unknown Games with Correlated Payoffs
We consider the problem of learning to play a repeated multiagent game ...
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OffPolicy Reinforcement Learning for Efficient and Effective GAN Architecture Search
In this paper, we introduce a new reinforcement learning (RL) based neur...
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RayNet: Learning Volumetric 3D Reconstruction with Ray Potentials
In this paper, we consider the problem of reconstructing a dense 3D mode...
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An Anatomy of Graph Neural Networks Going Deep via the Lens of Mutual Information: Exponential Decay vs. Full Preservation
Graph Convolutional Network (GCN) has attracted intensive interests rece...
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DeepSEE: Deep Disentangled Semantic Explorative Extreme SuperResolution
Superresolution (SR) is by definition illposed. There are infinitely m...
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Noregret Bayesian Optimization with Unknown Hyperparameters
Bayesian optimization (BO) based on Gaussian process models is a powerfu...
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Active Learning for Segmentation Based on Bayesian Sample Queries
Segmentation of anatomical structures is a fundamental image analysis ta...
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NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
This paper reviews the NTIRE 2020 challenge on real image denoising with...
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Improving Gradient Estimation in Evolutionary Strategies With Past Descent Directions
Evolutionary Strategies (ES) are known to be an effective blackbox opti...
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Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement
The recent years have witnessed the great potential of deep learning for...
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EVIMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras
We present the first eventbased learning approach for motion segmentati...
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AirSim Drone Racing Lab
Autonomous drone racing is a challenging research problem at the interse...
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Learning for Video Compression with Recurrent AutoEncoder and Recurrent Probability Model
The past few years have witnessed increasing interests in applying deep ...
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This is not what I imagined: Error Detection for Semantic Segmentation through Visual Dissimilarity
There has been a remarkable progress in the accuracy of semantic segment...
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Wavelet Domain Style Transfer for an Effective Perceptiondistortion Tradeoff in Single Image SuperResolution
In single image superresolution (SISR), given a lowresolution (LR) ima...
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Efficient Video Semantic Segmentation with Labels Propagation and Refinement
This paper tackles the problem of realtime semantic segmentation of hig...
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Continual Learning in Recurrent Neural Networks with Hypernetworks
The last decade has seen a surge of interest in continual learning (CL),...
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COVIDHunter: An Accurate, Flexible, and EnvironmentAware OpenSource COVID19 Outbreak Simulation Model
Motivation: Early detection and isolation of COVID19 patients are essen...
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Variational Transformer Networks for Layout Generation
Generative models able to synthesize layouts of different kinds (e.g. do...
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Superpixel Soup: Monocular Dense 3D Reconstruction of a Complex Dynamic Scene
This work addresses the task of dense 3D reconstruction of a complex dyn...
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SelfCalibration Supported Robust Projective StructurefromMotion
Typical StructurefromMotion (SfM) pipelines rely on finding correspond...
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InformationDirected Exploration for Deep Reinforcement Learning
Efficient exploration remains a major challenge for reinforcement learni...
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Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations
The goal of many computer vision systems is to transform image pixels in...
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A scaledependent notion of effective dimension
We introduce a notion of "effective dimension" of a statistical model ba...
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Efficient 2D neuron boundary segmentation with local topological constraints
We present a method for segmenting neuron membranes in 2D electron micro...
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Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression
In this paper, we analyze two popular network compression techniques, i....
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Scalable Graph Networks for Particle Simulations
Learning system dynamics directly from observations is a promising direc...
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Drug discovery with explainable artificial intelligence
Deep learning bears promise for drug discovery, including advanced image...
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GLAMpoints: Greedily Learned Accurate Match points
We introduce a novel CNNbased feature point detector  GLAMpoints  lea...
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Meta Answering for Machine Reading
We investigate a framework for machine reading, inspired by real world i...
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RealTime Model Calibration with Deep Reinforcement Learning
The dynamic, realtime, and accurate inference of model parameters from ...
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Joint reconstruction and bias field correction for undersampled MR imaging
Undersampling the kspace in MRI allows saving precious acquisition time...
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Learning Set Functions that are Sparse in NonOrthogonal Fourier Bases
Many applications of machine learning on discrete domains, such as learn...
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Replacing Mobile Camera ISP with a Single Deep Learning Model
As the popularity of mobile photography is growing constantly, lots of e...
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Probabilistic PerformancePattern Decomposition (PPPD): analysis framework and applications to stochastic mechanical systems
Since the early 1900s, numerous research efforts have been devoted to de...
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Weakly Supervised 3D Hand Pose Estimation via Biomechanical Constraints
Estimating 3D hand pose from 2D images is a difficult, inverse problem d...
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A Commentary on the Unsupervised Learning of Disentangled Representations
The goal of the unsupervised learning of disentangled representations is...
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AI Benchmark: Running Deep Neural Networks on Android Smartphones
Over the last years, the computational power of mobile devices such as s...
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Interventional Robustness of Deep Latent Variable Models
The ability to learn disentangled representations that split underlying ...
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ETH Zurich
ETH Zurich is a science, technology, engineering and mathematics university in the city of Zürich, Switzerland.