EPFL

∙ Lausanne , Switzerland ∙ 0 followers

The École polytechnique fédérale de Lausanne is a research institute and university in Lausanne, Switzerland, that specializes in natural sciences and engineering.

Featured Researchers

Wei Wang
207 publications
Wei Liu
202 publications
Pascal Fua
77 publications
Mathieu Salzmann
75 publications
Volkan Cevher
68 publications
Pascal Frossard
66 publications
Martin Jaggi
57 publications
Ali H. Sayed
51 publications
Vincent Lepetit
49 publications
Amin Karbasi
46 publications
Jonathan Scarlett
38 publications

Using Image Priors to Improve Scene Understanding

Semantic segmentation algorithms that can robustly segment objects acros...
10/02/2019 ∙ by Brigit Schroeder, et al. ∙ 46 ∙ share

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Inverse Graph Learning over Optimization Networks

Many inferential and learning tasks can be accomplished efficiently by m...
12/18/2019 ∙ by Vincenzo Matta, et al. ∙ 40 ∙ share

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Estimating People Flows to Better Count them in Crowded Scenes

State-of-the-art methods for counting people in crowded scenes rely on d...
11/25/2019 ∙ by Weizhe Liu, et al. ∙ 36 ∙ share

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giotto-tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration

We introduce giotto-tda, a Python library that integrates high-performan...
04/06/2020 ∙ by Guillaume Tauzin, et al. ∙ 32 ∙ share

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Image Restoration using Plug-and-Play CNN MAP Denoisers

Plug-and-play denoisers can be used to perform generic image restoration...
12/18/2019 ∙ by Siavash Bigdeli, et al. ∙ 27 ∙ share

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Learn to synthesize and synthesize to learn

Attribute guided face image synthesis aims to manipulate attributes on a...
05/01/2019 ∙ by Behzad Bozorgtabar, et al. ∙ 26 ∙ share

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Shape Reconstruction by Learning Differentiable Surface Representations

Generative models that produce point clouds have emerged as a powerful t...
11/25/2019 ∙ by Jan Bednařík, et al. ∙ 24 ∙ share

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Self-Supervised Prototypical Transfer Learning for Few-Shot Classification

Most approaches in few-shot learning rely on costly annotated data relat...
06/19/2020 ∙ by Carlos Medina, et al. ∙ 21 ∙ share

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Putting Ridesharing to the Test: Efficient and Scalable Solutions and the Power of Dynamic Vehicle Relocation

Ridesharing is a coordination problem in its core. Traditionally it has ...
12/17/2019 ∙ by Panayiotis Danassis, et al. ∙ 20 ∙ share

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Self-Supervised Deep Active Accelerated MRI

We propose to simultaneously learn to sample and reconstruct magnetic re...
01/14/2019 ∙ by Kyong Hwan Jin, et al. ∙ 14 ∙ share

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Data Parallelism in Training Sparse Neural Networks

Network pruning is an effective methodology to compress large neural net...
03/25/2020 ∙ by Namhoon Lee, et al. ∙ 13 ∙ share

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Isometric Transformation Invariant Graph-based Deep Neural Network

Learning transformation invariant representations of visual data is an i...
08/21/2018 ∙ by Renata Khasanova, et al. ∙ 12 ∙ share

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Segmentation-driven 6D Object Pose Estimation

The most recent trend in estimating the 6D pose of rigid objects has bee...
12/06/2018 ∙ by Yinlin Hu, et al. ∙ 12 ∙ share

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PifPaf: Composite Fields for Human Pose Estimation

We propose a new bottom-up method for multi-person 2D human pose estimat...
03/15/2019 ∙ by Sven Kreiss, et al. ∙ 12 ∙ share

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Exploring Factors for Improving Low Resolution Face Recognition

State-of-the-art deep face recognition approaches report near perfect pe...
07/23/2019 ∙ by Omid Abdollahi Aghdam, et al. ∙ 12 ∙ share

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Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching

End-to-end deep-learning networks recently demonstrated extremely good p...
06/05/2018 ∙ by Stepan Tulyakov, et al. ∙ 10 ∙ share

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Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks

We introduce a new scene graph generation method called image-level atte...
11/09/2018 ∙ by Guillaume Jaume, et al. ∙ 10 ∙ share

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Neural Scene Decomposition for Multi-Person Motion Capture

Learning general image representations has proven key to the success of ...
03/13/2019 ∙ by Helge Rhodin, et al. ∙ 10 ∙ share

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Using Depth for Pixel-Wise Detection of Adversarial Attacks in Crowd Counting

State-of-the-art methods for counting people in crowded scenes rely on d...
11/26/2019 ∙ by Weizhe Liu, et al. ∙ 10 ∙ share

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Joint Learning of Semantic Alignment and Object Landmark Detection

Convolutional neural networks (CNNs) based approaches for semantic align...
10/02/2019 ∙ by Sangryul Jeon, et al. ∙ 9 ∙ share

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On the Performance of Exact Diffusion over Adaptive Networks

Various bias-correction methods such as EXTRA, DIGing, and exact diffusi...
03/26/2019 ∙ by Kun Yuan, et al. ∙ 8 ∙ share

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Learning Vision-based Flight in Drone Swarms by Imitation

Decentralized drone swarms deployed today either rely on sharing of posi...
08/08/2019 ∙ by Fabian Schilling, et al. ∙ 8 ∙ share

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Structure-Property Maps with Kernel Principal Covariates Regression

Data analysis based on linear methods, which look for correlations betwe...
02/12/2020 ∙ by Benjamin A. Helfrecht, et al. ∙ 8 ∙ share

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Cascade Attention Guided Residue Learning GAN for Cross-Modal Translation

Since we were babies, we intuitively develop the ability to correlate th...
07/03/2019 ∙ by Bin Duan, et al. ∙ 7 ∙ share

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MeshSDF: Differentiable Iso-Surface Extraction

Geometric Deep Learning has recently made striking progress with the adv...
06/06/2020 ∙ by Edoardo Remelli, et al. ∙ 7 ∙ share

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An Approximate Bayesian Approach to Surprise-Based Learning

Surprise-based learning allows agents to adapt quickly in non-stationary...
07/05/2019 ∙ by Vasiliki Liakoni, et al. ∙ 6 ∙ share

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Self-supervised Training of Proposal-based Segmentation via Background Prediction

While supervised object detection methods achieve impressive accuracy, t...
07/18/2019 ∙ by Isinsu Katircioglu, et al. ∙ 6 ∙ share

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Cycle In Cycle Generative Adversarial Networks for Keypoint-Guided Image Generation

In this work, we propose a novel Cycle In Cycle Generative Adversarial N...
08/02/2019 ∙ by Hao Tang, et al. ∙ 6 ∙ share

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Conditional LSTM-GAN for Melody Generation from Lyrics

Melody generation from lyrics has been a challenging research issue in t...
08/15/2019 ∙ by Yi Yu, et al. ∙ 6 ∙ share

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Is Local SGD Better than Minibatch SGD?

We study local SGD (also known as parallel SGD and federated averaging),...
02/18/2020 ∙ by Blake Woodworth, et al. ∙ 5 ∙ share

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Empirical Bayes Transductive Meta-Learning with Synthetic Gradients

We propose a meta-learning approach that learns from multiple tasks in a...
04/27/2020 ∙ by Shell Xu Hu, et al. ∙ 5 ∙ share

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VIENA2: A Driving Anticipation Dataset

Action anticipation is critical in scenarios where one needs to react be...
10/22/2018 ∙ by Mohammad Sadegh Aliakbarian, et al. ∙ 4 ∙ share

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Attribute-Guided Sketch Generation

Facial attributes are important since they provide a detailed descriptio...
01/28/2019 ∙ by Hao Tang, et al. ∙ 4 ∙ share

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Revisiting hard thresholding for DNN pruning

The most common method for DNN pruning is hard thresholding of network w...
05/21/2019 ∙ by Konstantinos Pitas, et al. ∙ 4 ∙ share

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iPool -- Information-based Pooling in Hierarchical Graph Neural Networks

With the advent of data science, the analysis of network or graph data h...
07/01/2019 ∙ by Xing Gao, et al. ∙ 4 ∙ share

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SROBB: Targeted Perceptual Loss for Single Image Super-Resolution

By benefiting from perceptual losses, recent studies have improved signi...
08/20/2019 ∙ by Mohammad Saeed Rad, et al. ∙ 4 ∙ share

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A Spatiotemporal Epidemic Model to Quantify the Effects of Contact Tracing, Testing, and Containment

We introduce a novel modeling framework for studying epidemics that is s...
04/15/2020 ∙ by Lars Lorch, et al. ∙ 4 ∙ share

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Rethinking Person Re-Identification with Confidence

A common challenge in person re-identification systems is to differentia...
06/11/2019 ∙ by George Adaimi, et al. ∙ 3 ∙ share

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MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation

We tackle the fundamentally ill-posed problem of 3D human localization f...
06/14/2019 ∙ by Lorenzo Bertoni, et al. ∙ 3 ∙ share

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Blind Universal Bayesian Image Denoising with Gaussian Noise Level Learning

Blind and universal image denoising consists of a unique model that deno...
07/05/2019 ∙ by Majed El Helou, et al. ∙ 3 ∙ share

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Benefiting from Multitask Learning to Improve Single Image Super-Resolution

Despite significant progress toward super resolving more realistic image...
07/29/2019 ∙ by Mohammad Saeed Rad, et al. ∙ 3 ∙ share

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Geometry-aware Deep Network for Single-Image Novel View Synthesis

This paper tackles the problem of novel view synthesis from a single ima...
04/17/2018 ∙ by Miaomiao Liu, et al. ∙ 2 ∙ share

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ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

Machine learning (ML) has become a core component of many real-world app...
06/04/2018 ∙ by Ahmed Salem, et al. ∙ 2 ∙ share

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Efficient Differentiable Programming in a Functional Array-Processing Language

We present a system for the automatic differentiation of a higher-order ...
06/06/2018 ∙ by Amir Shaikhha, et al. ∙ 2 ∙ share

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Fast Rotational Sparse Coding

We propose an algorithm for rotational sparse coding along with an effic...
06/12/2018 ∙ by Michael T. McCann, et al. ∙ 2 ∙ share

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MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval

This paper addresses the general problem of blind echo retrieval, i.e., ...
10/31/2018 ∙ by Helena Peic Tukuljac, et al. ∙ 2 ∙ share

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A `Little Bit' Too Much? High Speed Imaging from Sparse Photon Counts

Recent advances in photographic sensing technologies have made it possib...
11/06/2018 ∙ by Paramanand Chandramouli, et al. ∙ 2 ∙ share

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Embedded polarizing filters to separate diffuse and specular reflection

Polarizing filters provide a powerful way to separate diffuse and specul...
11/06/2018 ∙ by Laurent Valentin Jospin, et al. ∙ 2 ∙ share

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Context-Aware Crowd Counting

State-of-the-art methods for counting people in crowded scenes rely on d...
11/26/2018 ∙ by Weizhe Liu, et al. ∙ 2 ∙ share

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Privacy-Preserving Classification with Secret Vector Machines

Today, large amounts of valuable data are distributed among millions of ...
07/08/2019 ∙ by Valentin Hartmann, et al. ∙ 2 ∙ share

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