Christian Wolf

research

∙ 02/01/2022

MoCap-less Quantitative Evaluation of Ego-Pose Estimation Without Ground Truth Measurements

The emergence of data-driven approaches for control and planning in robo...

0 Quentin Possamaï, et al. ∙

research

∙ 02/01/2022

Filtered-CoPhy: Unsupervised Learning of Counterfactual Physics in Pixel Space

Learning causal relationships in high-dimensional data (images, videos) ...

3 Steeven Janny, et al. ∙

research

∙ 12/22/2021

Graph augmented Deep Reinforcement Learning in the GameRLand3D environment

We address planning and navigation in challenging 3D video games featuri...

11 Edward Beeching, et al. ∙

research

∙ 12/07/2021

Godot Reinforcement Learning Agents

We present Godot Reinforcement Learning (RL) Agents, an open-source inte...

0 Edward Beeching, et al. ∙

research

∙ 11/29/2021

An in-depth experimental study of sensor usage and visual reasoning of robots navigating in real environments

Visual navigation by mobile robots is classically tackled through SLAM p...

0 Assem Sadek, et al. ∙

research

∙ 10/12/2021

Satellite Image Semantic Segmentation

In this paper, we propose a method for the automatic semantic segmentati...

0 Eric Guérin, et al. ∙

research

∙ 09/24/2021

SIM2REALVIZ: Visualizing the Sim2Real Gap in Robot Ego-Pose Estimation

The Robotics community has started to heavily rely on increasingly reali...

6 Theo Jaunet, et al. ∙

research

∙ 07/29/2021

Underwater Acoustic Networks for Security Risk Assessment in Public Drinking Water Reservoirs

We have built a novel system for the surveillance of drinking water rese...

14 Jörg Stork, et al. ∙

research

∙ 07/13/2021

Teaching Agents how to Map: Spatial Reasoning for Multi-Object Navigation

In the context of visual navigation, the capacity to map a novel environ...

1 Pierre Marza, et al. ∙

research

∙ 06/22/2021

Universal Domain Adaptation in Ordinal Regression

We address the problem of universal domain adaptation (UDA) in ordinal r...

0 Chidlovskii Boris, et al. ∙

research

∙ 06/10/2021

Supervising the Transfer of Reasoning Patterns in VQA

Methods for Visual Question Anwering (VQA) are notorious for leveraging ...

13 Corentin Kervadec, et al. ∙

research

∙ 04/08/2021

How Transferable are Reasoning Patterns in VQA?

Since its inception, Visual Question Answering (VQA) is notoriously know...

14 Corentin Kervadec, et al. ∙

research

∙ 04/02/2021

VisQA: X-raying Vision and Language Reasoning in Transformers

Visual Question Answering systems target answering open-ended textual qu...

29 Theo Jaunet, et al. ∙

research

∙ 03/23/2021

Deep KKL: Data-driven Output Prediction for Non-Linear Systems

We address the problem of output prediction, ie. designing a model for a...

0 Steeven Janny, et al. ∙

research

∙ 01/21/2021

SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation

In this paper we introduce a Transformer-based approach to video object ...

0 Brendan Duke, et al. ∙

research

∙ 07/10/2020

Learning to plan with uncertain topological maps

We train an agent to navigate in 3D environments using a hierarchical st...

11 Edward Beeching, et al. ∙

research

∙ 06/10/2020

Estimating semantic structure for the VQA answer space

Since its appearance, Visual Question Answering (VQA, i.e. answering a q...

0 Corentin Kervadec, et al. ∙

research

∙ 06/09/2020

Roses Are Red, Violets Are Blue... but Should Vqa Expect Them To?

To be reliable on rare events is an important requirement for systems ba...

0 Corentin Kervadec, et al. ∙

research

∙ 01/24/2020

EgoMap: Projective mapping and structured egocentric memory for Deep RL

Tasks involving localization, memorization and planning in partially obs...

0 Edward Beeching, et al. ∙

research

∙ 12/06/2019

Weak Supervision helps Emergence of Word-Object Alignment and improves Vision-Language Tasks

The large adoption of the self-attention (i.e. transformer model) and BE...

18 Corentin Kervadec, et al. ∙

research

∙ 09/26/2019

COPHY: Counterfactual Learning of Physical Dynamics

Understanding causes and effects in mechanical systems is an essential c...

8 Fabien Baradel, et al. ∙

research

∙ 09/06/2019

DRLViz: Understanding Decisions and Memory in Deep Reinforcement Learning

We present DRLViz, a visual analytics interface to interpret the interna...

23 Theo Jaunet, et al. ∙

research

∙ 04/16/2019

Learning 3D Navigation Protocols on Touch Interfaces with Cooperative Multi-Agent Reinforcement Learning

Using touch devices to navigate in virtual 3D environments such as compu...

4 Quentin Debard, et al. ∙

research

∙ 04/03/2019

Deep Reinforcement Learning on a Budget: 3D Control and Reasoning Without a Supercomputer

An important goal of research in Deep Reinforcement Learning in mobile r...

22 Edward Beeching, et al. ∙

research

∙ 06/16/2018

Object Level Visual Reasoning in Videos

Human activity recognition is typically addressed by training models to ...

0 Fabien Baradel, et al. ∙

research

∙ 02/22/2018

Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points

We propose a method for human activity recognition from RGB data which d...

0 Fabien Baradel, et al. ∙

research

∙ 02/19/2018

Learning to recognize touch gestures: recurrent vs. convolutional features and dynamic sampling

We propose a fully automatic method for learning gestures on big touch d...

0 Quentin Debard, et al. ∙

research

∙ 12/20/2017

Human Action Recognition: Pose-based Attention draws focus to Hands

We propose a new spatio-temporal attention based mechanism for human act...

0 Fabien Baradel, et al. ∙

research

∙ 09/25/2017

Multi-view pose estimation with mixtures-of-parts and adaptive viewpoint selection

We propose a new method for human pose estimation which leverages inform...

0 Emre Dogan, et al. ∙

research

∙ 07/25/2017

Residual Conv-Deconv Grid Network for Semantic Segmentation

This paper presents GridNet, a new Convolutional Neural Network (CNN) ar...

0 Damien Fourure, et al. ∙

research

∙ 03/29/2017

Pose-conditioned Spatio-Temporal Attention for Human Action Recognition

We address human action recognition from multi-modal video data involvin...

0 Fabien Baradel, et al. ∙

research

∙ 11/17/2016

Learning to detect and localize many objects from few examples

The current trend in object detection and localization is to learn predi...

0 Bastien Moysset, et al. ∙

research

∙ 11/20/2015

Hand Pose Estimation through Semi-Supervised and Weakly-Supervised Learning

We propose a method for hand pose estimation based on a deep regressor t...

0 Natalia Neverova, et al. ∙

research

∙ 11/12/2015

Learning Human Identity from Motion Patterns

We present a large-scale study exploring the capability of temporal deep...

0 Natalia Neverova, et al. ∙

research

∙ 05/04/2015

Activity recognition from videos with parallel hypergraph matching on GPUs

In this paper, we propose a method for activity recognition from videos ...

0 Eric Lombardi, et al. ∙

research

∙ 12/31/2014

ModDrop: adaptive multi-modal gesture recognition

We present a method for gesture detection and localisation based on mult...

0 Natalia Neverova, et al. ∙

Christian Wolf

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