501 citations · 838 across the 22 of their papers we have counts for
29 papers
Smoothness-Based Derandomization of PAC-Bayes Bounds
Alexandre Lemire Paquin, Brahim Chaib-Draa, Philippe Giguère
We study PAC-Bayes derandomization for smooth loss functions. Our goal is to obtain generalization bounds that hold with high probability for deterministic predictors by exploiting…
MaskBEV: Joint Object Detection and Footprint Completion for Bird's-eye View 3D Point Clouds
William Guimont-Martin, Jean-Michel Fortin, François Pomerleau +1
Recent works in object detection in LiDAR point clouds mostly focus on predicting bounding boxes around objects. This prediction is commonly achieved using anchor-based or anchor-f…
MixVPR: Feature Mixing for Visual Place Recognition
Amar Ali-bey, Brahim Chaib-draa, Philippe Giguère
Visual Place Recognition (VPR) is a crucial part of mobile robotics and autonomous driving as well as other computer vision tasks. It refers to the process of identifying a place d…
Global Proxy-based Hard Mining for Visual Place Recognition
Amar Ali-bey, Brahim Chaib-draa, Philippe Giguère
Learning deep representations for visual place recognition is commonly performed using pairwise or triple loss functions that highly depend on the hardness of the examples sampled…
Tree Detection and Diameter Estimation Based on Deep Learning
Vincent Grondin, Jean-Michel Fortin, François Pomerleau +1
Tree perception is an essential building block toward autonomous forestry operations. Current developments generally consider input data from lidar sensors to solve forest navigati…
GSV-Cities: Toward Appropriate Supervised Visual Place Recognition
Amar Ali-bey, Brahim Chaib-draa, Philippe Giguère
This paper aims to investigate representation learning for large scale visual place recognition, which consists of determining the location depicted in a query image by referring t…
Training Deep Learning Algorithms on Synthetic Forest Images for Tree Detection
Vincent Grondin, François Pomerleau, Philippe Giguère
Vision-based segmentation in forested environments is a key functionality for autonomous forestry operations such as tree felling and forwarding. Deep learning algorithms demonstra…
Instance Segmentation for Autonomous Log Grasping in Forestry Operations
Jean-Michel Fortin, Olivier Gamache, Vincent Grondin +2
Wood logs picking is a challenging task to automate. Indeed, logs usually come in cluttered configurations, randomly orientated and overlapping. Recent work on log picking automati…
Kilometer-scale autonomous navigation in subarctic forests: challenges and lessons learned
Dominic Baril, Simon-Pierre Deschênes, Olivier Gamache +6
Challenges inherent to autonomous wintertime navigation in forests include lack of reliable a Global Navigation Satellite System (GNSS) signal, low feature contrast, high illuminat…
SuMa++: Efficient LiDAR-based Semantic SLAM
Xieyuanli Chen, Andres Milioto, Emanuele Palazzolo +3
Reliable and accurate localization and mapping are key components of most autonomous systems. Besides geometric information about the mapped environment, the semantics plays an imp…
Lidar Scan Registration Robust to Extreme Motions
Simon-Pierre Deschênes, Dominic Baril, Vladimír Kubelka +2
Registration algorithms, such as Iterative Closest Point (ICP), have proven effective in mobile robot localization algorithms over the last decades. However, they are susceptible t…
Accurate outdoor ground truth based on total stations
Maxime Vaidis, Philippe Giguère, François Pomerleau +1
In robotics, accurate ground-truth position fostered the development of mapping and localization algorithms through the creation of cornerstone datasets. In outdoor environments an…
Evaluation of Skid-Steering Kinematic Models for Subarctic Environments
Dominic Baril, Vincent Grondin, Simon-Pierre Deschênes +6
In subarctic and arctic areas, large and heavy skid-steered robots are preferred for their robustness and ability to operate on difficult terrain. State estimation, motion control…
The Indian Chefs Process
Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier +6
This paper introduces the Indian Chefs Process (ICP), a Bayesian nonparametric prior on the joint space of infinite directed acyclic graphs (DAGs) and orders that generalizes India…
Tree bark re-identification using a deep-learning feature descriptor
Martin Robert, Patrick Dallaire, Philippe Giguère
The ability to visually re-identify objects is a fundamental capability in vision systems. Oftentimes, it relies on collections of visual signatures based on descriptors, such as S…
Deep Template-based Object Instance Detection
Jean-Philippe Mercier, Mathieu Garon, Philippe Giguère +1
Much of the focus in the object detection literature has been on the problem of identifying the bounding box of a particular class of object in an image. Yet, in contexts such as r…
Driving Datasets Literature Review
Charles-Éric Noël Laflamme, François Pomerleau, Philippe Giguère
This report is a survey of the different autonomous driving datasets which have been published up to date. The first section introduces the many sensor types used in autonomous dri…
ReFusion: 3D Reconstruction in Dynamic Environments for RGB-D Cameras Exploiting Residuals
Emanuele Palazzolo, Jens Behley, Philipp Lottes +2
Mapping and localization are essential capabilities of robotic systems. Although the majority of mapping systems focus on static environments, the deployment in real-world situatio…
Predicting GNSS satellite visibility from dense point clouds
Philippe Dandurand, Philippe Babin, Vladimır Kubelka +2
To help future mobile agents plan their movement in harsh environments,a predictive model has been designed to determine what areas would be favorable for Global Navigation Satelli…
Large-scale 3D Mapping of Subarctic Forests
Philippe Babin, Philippe Dandurand, Vladimír Kubelka +2
The ability to map challenging subarctic environments opens new horizons for robotic deployments in industries such as forestry, surveillance, and open-pit mining. In this paper, w…
Automatic 3D Mapping for Tree Diameter Measurements in Inventory Operations
Jean-François Tremblay, Martin Béland, François Pomerleau +2
Forestry is a major industry in many parts of the world. It relies on forest inventory, which consists of measuring tree attributes. We propose to use 3D mapping, based on the iter…
GQ-STN: Optimizing One-Shot Grasp Detection based on Robustness Classifier
Alexandre Gariépy, Jean-Christophe Ruel, Brahim Chaib-draa +1
Grasping is a fundamental robotic task needed for the deployment of household robots or furthering warehouse automation. However, few approaches are able to perform grasp detection…
Analysis of Robust Functions for Registration Algorithms
Philippe Babin, Philippe Giguère, François Pomerleau
Registration accuracy is influenced by the presence of outliers and numerous robust solutions have been developed over the years to mitigate their effect. However, without a large…
CELLO-3D: Estimating the Covariance of ICP in the Real World
David Landry, François Pomerleau, Philippe Giguère
The fusion of Iterative Closest Point (ICP) reg- istrations in existing state estimation frameworks relies on an accurate estimation of their uncertainty. In this paper, we study t…