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
244 publications
Wei Liu
224 publications
Pascal Fua
87 publications
Mathieu Salzmann
86 publications
Pascal Frossard
74 publications
Volkan Cevher
70 publications
Martin Jaggi
61 publications
Ali H. Sayed
56 publications
Vincent Lepetit
51 publications
Amin Karbasi
48 publications
Jonathan Scarlett
39 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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration

Image restoration encompasses fundamental image processing tasks that ha...
11/03/2020 ∙ by Majed El Helou, et al. ∙ 8 ∙ share

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
Attribute-Guided Sketch Generation

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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it