ETH Zurich

∙ Zürich , Switzerland ∙ 0 followers

ETH Zurich is a science, technology, engineering and mathematics university in the city of Zürich, Switzerland.

Featured Researchers

Yang Liu
344 publications
Luc Van Gool
253 publications
Jun Wang
221 publications
Yu Wang
136 publications
Yan Zhang
127 publications
Onur Mutlu
123 publications
Roland Siegwart
119 publications
Andreas Krause
119 publications
Yue Zhang
119 publications
Radu Timofte
118 publications
Luca Benini
108 publications

Rendering Natural Camera Bokeh Effect with Deep Learning

Bokeh is an important artistic effect used to highlight the main object ...
06/10/2020 ∙ by Andrey Ignatov, et al. ∙ 51 ∙ share

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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 ...
06/30/2020 ∙ by Andrei Ivanov, et al. ∙ 44 ∙ share

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Unsupervised Lesion Detection via Image Restoration with a Normative Prior

Unsupervised lesion detection is a challenging problem that requires acc...
04/30/2020 ∙ by Xiaoran Chen, et al. ∙ 41 ∙ share

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Deep Learning for Post-Processing Ensemble Weather Forecasts

Quantifying uncertainty in weather forecasts typically employs ensemble ...
05/18/2020 ∙ by Peter Grönquist, et al. ∙ 41 ∙ share

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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...
11/15/2019 ∙ by Thomas Mesnard, et al. ∙ 37 ∙ share

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Fine-grained Recognition: Accounting for Subtle Differences between Similar Classes

The main requisite for fine-grained recognition task is to focus on subt...
12/14/2019 ∙ by Guolei Sun, et al. ∙ 37 ∙ share

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Learning Dynamical Systems using Local Stability Priors

A coupled computational approach to simultaneously learn a vector field ...
08/23/2020 ∙ by Arash Mehrjou, et al. ∙ 36 ∙ share

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Few-Shot Classification By Few-Iteration Meta-Learning

Learning in a low-data regime from only a few labeled examples is an imp...
10/01/2020 ∙ by Ardhendu Shekhar Tripathi, et al. ∙ 35 ∙ share

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Real-Time Video Super-Resolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Report

Video super-resolution has recently become one of the most important mob...
05/17/2021 ∙ by Andrey Ignatov, et al. ∙ 35 ∙ share

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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...
07/09/2020 ∙ by Anna Volokitin, et al. ∙ 34 ∙ share

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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...
06/14/2019 ∙ by Maxim Borisyak, et al. ∙ 33 ∙ share

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No-Regret Learning in Unknown Games with Correlated Payoffs

We consider the problem of learning to play a repeated multi-agent game ...
09/18/2019 ∙ by Pier Giuseppe Sessa, et al. ∙ 33 ∙ share

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Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search

In this paper, we introduce a new reinforcement learning (RL) based neur...
07/17/2020 ∙ by Yuan Tian, et al. ∙ 29 ∙ share

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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...
01/06/2019 ∙ by Despoina Paschalidou, et al. ∙ 28 ∙ share

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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...
10/10/2019 ∙ by Nezihe Merve Gürel, et al. ∙ 28 ∙ share

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DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-Resolution

Super-resolution (SR) is by definition ill-posed. There are infinitely m...
04/09/2020 ∙ by Marcel Christoph Bühler, et al. ∙ 27 ∙ share

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No-regret Bayesian Optimization with Unknown Hyperparameters

Bayesian optimization (BO) based on Gaussian process models is a powerfu...
01/10/2019 ∙ by Felix Berkenkamp, et al. ∙ 26 ∙ share

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Active Learning for Segmentation Based on Bayesian Sample Queries

Segmentation of anatomical structures is a fundamental image analysis ta...
12/22/2019 ∙ by Firat Ozdemir, et al. ∙ 26 ∙ share

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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...
05/08/2020 ∙ by Abdelrahman Abdelhamed, et al. ∙ 25 ∙ share

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Improving Gradient Estimation in Evolutionary Strategies With Past Descent Directions

Evolutionary Strategies (ES) are known to be an effective black-box opti...
10/11/2019 ∙ by Florian Meier, et al. ∙ 24 ∙ share

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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...
03/04/2020 ∙ by Ren Yang, et al. ∙ 23 ∙ share

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EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras

We present the first event-based learning approach for motion segmentati...
03/18/2019 ∙ by Anton Mitrokhin, et al. ∙ 22 ∙ share

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AirSim Drone Racing Lab

Autonomous drone racing is a challenging research problem at the interse...
03/12/2020 ∙ by Ratnesh Madaan, et al. ∙ 22 ∙ share

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Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model

The past few years have witnessed increasing interests in applying deep ...
06/24/2020 ∙ by Ren Yang, et al. ∙ 21 ∙ share

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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...
09/02/2019 ∙ by David Haldimann, et al. ∙ 20 ∙ share

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Wavelet Domain Style Transfer for an Effective Perception-distortion Tradeoff in Single Image Super-Resolution

In single image super-resolution (SISR), given a low-resolution (LR) ima...
10/09/2019 ∙ by Xin Deng, et al. ∙ 20 ∙ share

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Efficient Video Semantic Segmentation with Labels Propagation and Refinement

This paper tackles the problem of real-time semantic segmentation of hig...
12/26/2019 ∙ by Matthieu Paul, et al. ∙ 20 ∙ share

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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),...
06/22/2020 ∙ by Benjamin Ehret, et al. ∙ 20 ∙ share

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COVIDHunter: An Accurate, Flexible, and Environment-Aware Open-Source COVID-19 Outbreak Simulation Model

Motivation: Early detection and isolation of COVID-19 patients are essen...
02/06/2021 ∙ by Mohammed Alser, et al. ∙ 20 ∙ share

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Variational Transformer Networks for Layout Generation

Generative models able to synthesize layouts of different kinds (e.g. do...
04/06/2021 ∙ by Diego Martin Arroyo, et al. ∙ 20 ∙ share

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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...
11/19/2019 ∙ by Suryansh Kumar, et al. ∙ 19 ∙ share

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Self-Calibration Supported Robust Projective Structure-from-Motion

Typical Structure-from-Motion (SfM) pipelines rely on finding correspond...
07/04/2020 ∙ by Rui Gong, et al. ∙ 19 ∙ share

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Information-Directed Exploration for Deep Reinforcement Learning

Efficient exploration remains a major challenge for reinforcement learni...
12/18/2018 ∙ by Nikolay Nikolov, et al. ∙ 18 ∙ share

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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...
01/06/2020 ∙ by Nadine Rueegg, et al. ∙ 18 ∙ share

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A scale-dependent notion of effective dimension

We introduce a notion of "effective dimension" of a statistical model ba...
01/29/2020 ∙ by Oksana Berezniuk, et al. ∙ 18 ∙ share

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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...
02/03/2020 ∙ by Thanuja D. Ambegoda, et al. ∙ 18 ∙ share

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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....
03/19/2020 ∙ by Yawei Li, et al. ∙ 18 ∙ share

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Scalable Graph Networks for Particle Simulations

Learning system dynamics directly from observations is a promising direc...
10/14/2020 ∙ by Karolis Martinkus, et al. ∙ 18 ∙ share

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Drug discovery with explainable artificial intelligence

Deep learning bears promise for drug discovery, including advanced image...
07/01/2020 ∙ by José Jiménez-Luna, et al. ∙ 17 ∙ share

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GLAMpoints: Greedily Learned Accurate Match points

We introduce a novel CNN-based feature point detector - GLAMpoints - lea...
08/19/2019 ∙ by Prune Truong, et al. ∙ 16 ∙ share

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Meta Answering for Machine Reading

We investigate a framework for machine reading, inspired by real world i...
11/11/2019 ∙ by Benjamin Borschinger, et al. ∙ 16 ∙ share

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Real-Time Model Calibration with Deep Reinforcement Learning

The dynamic, real-time, and accurate inference of model parameters from ...
06/07/2020 ∙ by Manuel Arias Chao, et al. ∙ 16 ∙ share

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Joint reconstruction and bias field correction for undersampled MR imaging

Undersampling the k-space in MRI allows saving precious acquisition time...
07/26/2020 ∙ by Mélanie Gaillochet, et al. ∙ 16 ∙ share

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Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases

Many applications of machine learning on discrete domains, such as learn...
10/01/2020 ∙ by Chris Wendler, et al. ∙ 16 ∙ share

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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...
02/13/2020 ∙ by Andrey Ignatov, et al. ∙ 15 ∙ share

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Probabilistic Performance-Pattern Decomposition (PPPD): analysis framework and applications to stochastic mechanical systems

Since the early 1900s, numerous research efforts have been devoted to de...
03/04/2020 ∙ by Ziqi Wang, et al. ∙ 15 ∙ share

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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...
03/20/2020 ∙ by Adrian Spurr, et al. ∙ 15 ∙ share

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A Commentary on the Unsupervised Learning of Disentangled Representations

The goal of the unsupervised learning of disentangled representations is...
07/28/2020 ∙ by Francesco Locatello, et al. ∙ 15 ∙ share

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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...
10/02/2018 ∙ by Andrey Ignatov, et al. ∙ 14 ∙ share

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Interventional Robustness of Deep Latent Variable Models

The ability to learn disentangled representations that split underlying ...
10/31/2018 ∙ by Raphael Suter, et al. ∙ 14 ∙ share

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