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Eric Marchand

24 accepted papers

2025

Toward Robust Neural Reconstruction from Sparse Point Sets

CVPR 2025poster

We consider the challenging problem of learning Signed Distance Functions (SDF) from sparse and noisy 3D point clouds. In contrast to recent methods that depend on smoothness priors, our method, rooted in a distributionally robust optimization (DRO) framework, incorporates a regularization term tha…

Cited by 1SourcePDFScholar
2023

Deep metric learning for visual servoing: when pose and image meet in latent space

ICRA 2023poster

We propose a new visual servoing method that controls a robot's motion in a latent space. We aim to extract the best properties of two previously proposed servoing methods: we seek to obtain the accuracy of photometric methods such as Direct Visual Servoing (DVS), as well as the behavior and converg…

Cited by 12SourceScholar
2023

JAWS: Just a Wild Shot for Cinematic Transfer in Neural Radiance Fields

CVPR 2023poster

This paper presents JAWS, an optimzation-driven approach that achieves the robust transfer of visual cinematic features from a reference in-the-wild video clip to a newly generated clip. To this end, we rely on an implicit-neural-representation (INR) in a way to compute a clip that shares the same c…

2022

Vision-based rotational control of an agile observation satellite

IROS 2022poster

Recent Earth observation satellites are now equipped with new instrument that allows image feedback in real-time. Problematic such as ground target tracking, moving or not, can now be addressed by precisely controlling the satellite attitude. In this paper, we propose to consider this problem using…

Cited by 4SourceScholar
2021

Tracking Pedestrian Heads in Dense Crowd

CVPR 2021poster

Tracking humans in crowded video sequences is an important constituent of visual scene understanding. Increasing crowd density challenges visibility of humans, limiting the scalability of existing pedestrian trackers to higher crowd densities. For that reason, we propose to revitalize head tracking…

Cited by 107PDFcodeScholar
2020

Relative Pose Estimation and Planar Reconstruction via Superpixel-Driven Multiple Homographies

IROS 2020poster

This paper proposes a novel method to simultaneously perform relative camera pose estimation and planar reconstruction of a scene from two RGB images. We start by extracting and matching superpixel information from both images and rely on a novel multi-model RANSAC approach to estimate multiple homo…

Cited by 8SourceScholar
2020

Simultaneous Tracking and Elasticity Parameter Estimation of Deformable Objects

ICRA 2020poster

In this paper, we propose a novel method to simultaneously track the deformation of soft objects and estimate their elasticity parameters. The tracking of the deformable object is performed by combining the visual information captured by a RGB-D sensor with interactive Finite Element Method simulati…

Cited by 21SourceScholar
2018

A modular framework for model-based visual tracking using edge, texture and depth features

IROS 2018poster

We present in this paper a modular real-time model-based visual tracker. It is able to fuse different types of measurement, that is, edge points, textured points, and depth map, provided by one or multiple vision sensors. A confidence index is also proposed for determining if the outputs of the trac…

Cited by 33SourceScholar
2018

Interval-Based Cooperative Uavs Pose Domain Characterization from Images and Ranges

IROS 2018poster

An interval-based approach to cooperative localization for a group of unmanned aerial vehicles (UAVs) is proposed. It computes a pose uncertainty domain for each robot, i.e., a set that contains the true robot pose, assuming bounded error measurements. The algorithm combines distances measurements t…

Cited by 6SourceScholar
2018

Optimized Contrast Enhancements to Improve Robustness of Visual Tracking in a SLAM Relocalisation Context

IROS 2018poster

Robustness of indirect SLAM techniques to light changing conditions remains a central issue in the robotics community. With the change in the illumination of a scene, feature points are either not extracted properly due to low contrasts, or not matched due to large differences in descriptors. In thi…

Cited by 3SourceScholar
2018

Training Deep Neural Networks for Visual Servoing

ICRA 2018poster

We present a deep neural network-based method to perform high-precision, robust and real-time 6 DOF positioning tasks by visual servoing. A convolutional neural network is fine-tuned to estimate the relative pose between the current and desired images and a pose-based visual servoing control law is…

Cited by 177SourceScholar
2017

An optical tracking system based on hybrid stereo/single-view registration and controlled cameras

IROS 2017poster

Optical tracking is widely used in robotics applications such as unmanned aerial vehicle (UAV) localization. Unfortunately, such systems require many cameras and are, consequently, expensive. In this paper, we propose an approach to considerably increase the optical tracking volume without adding ca…

Cited by 1SourceScholar
2016

Three-dimensional visual tracking and pose estimation in Scanning Electron Microscopes

IROS 2016poster

Visual tracking and estimation of the 3D posture of a micro/nano-object is a key issue in the development of automated manipulation tasks using the visual feedback. The 3D posture of the micro-object is estimated based on a template matching algorithm. Nevertheless, a key challenge for visual tracki…

Cited by 15SourceScholar
2015

3D object pose detection using foreground/background segmentation

ICRA 2015poster

This paper addresses the challenge of detecting and localizing a poorly textured known object, by initially estimating its complete 3D pose in a video sequence. Our solution relies on the 3D model of the object and synthetic views. The full pose estimation process is then based on foreground/backgro…

Cited by 15SourceScholar
2015

Hybrid automatic visual servoing scheme using defocus information for 6-DoF micropositioning

ICRA 2015poster

Direct photometric visual servoing uses only the pure image information as a visual feature, instead of using classic geometric features such as points or lines. It was demonstrated efficiently in 6 degrees of freedom (DoF) positioning. However, in micro-scale, using only image intensity as a visual…

Cited by 4SourceScholar