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
280 publications
Luc Van Gool
186 publications
Andreas Krause
94 publications
Yan Zhang
89 publications
Roland Siegwart
87 publications
Yue Zhang
82 publications
Luca Benini
80 publications
Onur Mutlu
79 publications
Radu Timofte
75 publications
Ce Zhang
58 publications
Martin Jaggi
57 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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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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(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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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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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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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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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. ∙ 18 ∙ 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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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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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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SMIT: Stochastic Multi-Label Image-to-Image Translation

Cross-domain mapping has been a very active topic in recent years. Given...
12/10/2018 ∙ by Andrés Romero, et al. ∙ 14 ∙ share

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An Empirical and Comparative Analysis of Data Valuation with Scalable Algorithms

This paper focuses on valuating training data for supervised learning ta...
11/17/2019 ∙ by Ruoxi Jia, et al. ∙ 14 ∙ share

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Self-supervised Object Motion and Depth Estimation from Video

We present a self-supervised learning framework to estimate the individu...
12/09/2019 ∙ by Qi Dai, et al. ∙ 14 ∙ share

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Knowledge-Induced Learning with Adaptive Sampling Variational Autoencoders for Open Set Fault Diagnostics

The recent increase in the availability of system condition monitoring d...
12/28/2019 ∙ by Manuel Arias Chao, et al. ∙ 14 ∙ share

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Depth Based Semantic Scene Completion with Position Importance Aware Loss

Semantic Scene Completion (SSC) refers to the task of inferring the 3D s...
01/29/2020 ∙ by Yu Liu, et al. ∙ 14 ∙ share

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Attention, please: A Spatio-temporal Transformer for 3D Human Motion Prediction

In this paper, we propose a novel architecture for the task of 3D human ...
04/18/2020 ∙ by Emre Aksan, et al. ∙ 14 ∙ share

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Extremely Weak Supervised Image-to-Image Translation for Semantic Segmentation

Recent advances in generative models and adversarial training have led t...
09/18/2019 ∙ by Samarth Shukla, et al. ∙ 13 ∙ share

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DLOW: Domain Flow for Adaptation and Generalization

In this work, we propose a domain flow generation(DLOW) approach to mode...
12/13/2018 ∙ by Rui Gong, et al. ∙ 12 ∙ share

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AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs

Stochastic differential equations are an important modeling class in man...
02/22/2019 ∙ by Gabriele Abbati, et al. ∙ 12 ∙ share

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Adversarial Training Generalizes Data-dependent Spectral Norm Regularization

We establish a theoretical link between adversarial training and operato...
06/04/2019 ∙ by Kevin Roth, et al. ∙ 12 ∙ share

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Learning Filter Basis for Convolutional Neural Network Compression

Convolutional neural networks (CNNs) based solutions have achieved state...
08/23/2019 ∙ by Yawei Li, et al. ∙ 12 ∙ share

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AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results

This paper reviews the AIM 2019 challenge on real world super-resolution...
11/18/2019 ∙ by Andreas Lugmayr, et al. ∙ 12 ∙ share

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Quantifying Data Augmentation for LiDAR based 3D Object Detection

In this work, we shed light on different data augmentation techniques co...
04/03/2020 ∙ by Martin Hahner, et al. ∙ 12 ∙ share

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EBPC: Extended Bit-Plane Compression for Deep Neural Network Inference and Training Accelerators

In the wake of the success of convolutional neural networks in image cla...
08/30/2019 ∙ by Lukas Cavigelli, et al. ∙ 11 ∙ share

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