Search Results for author: Nicolas Saunier

Found 16 papers, 8 papers with code

CenterPoly: real-time instance segmentation using bounding polygons

1 code implementation19 Aug 2021 Hughes Perreault, Guillaume-Alexandre Bilodeau, Nicolas Saunier, Maguelonne Héritier

The models were trained and evaluated on Cityscapes, KITTI and IDD and the results are reported on their public benchmark, which are state-of-the-art at real-time speeds.

Real-time Instance Segmentation Semantic Segmentation

MeNToS: Tracklets Association with a Space-Time Memory Network

no code implementations15 Jul 2021 Mehdi Miah, Guillaume-Alexandre Bilodeau, Nicolas Saunier

We propose a method for multi-object tracking and segmentation (MOTS) that does not require fine-tuning or per benchmark hyperparameter selection.

Instance Segmentation Multi-Object Tracking +5

Soft Attention: Does it Actually Help to Learn Social Interactions in Pedestrian Trajectory Prediction?

no code implementations16 Jun 2021 Laurent Boucaud, Daniel Aloise, Nicolas Saunier

In this paper, we focus on the deep-learning models with a soft-attention mechanism for social interaction modeling and study whether they use social information at prediction time.

Pedestrian Trajectory Prediction Trajectory Prediction

Low-Rank Autoregressive Tensor Completion for Spatiotemporal Traffic Data Imputation

1 code implementation30 Apr 2021 Xinyu Chen, MengYing Lei, Nicolas Saunier, Lijun Sun

In this paper, we propose a low-rank autoregressive tensor completion (LATC) framework by introducing \textit{temporal variation} as a new regularization term into the completion of a third-order (sensor $\times$ time of day $\times$ day) tensor.

Imputation Time Series +1

A Grid-based Representation for Human Action Recognition

no code implementations17 Oct 2020 Soufiane Lamghari, Guillaume-Alexandre Bilodeau, Nicolas Saunier

Human action recognition (HAR) in videos is a fundamental research topic in computer vision.

Action Recognition

An Empirical Analysis of Visual Features for Multiple Object Tracking in Urban Scenes

1 code implementation15 Oct 2020 Mehdi Miah, Justine Pepin, Nicolas Saunier, Guillaume-Alexandre Bilodeau

Commonly used features are color histograms, histograms of oriented gradients, deep features from convolutional neural networks and re-identification (ReID) features.

Multiple Object Tracking

Scalable Low-Rank Tensor Learning for Spatiotemporal Traffic Data Imputation

3 code implementations7 Aug 2020 Xinyu Chen, Yixian Chen, Nicolas Saunier, Lijun Sun

Recent studies based on tensor nuclear norm have demonstrated the superiority of tensor learning in imputation tasks by effectively characterizing the complex correlations/dependencies in spatiotemporal data.

Imputation Traffic Data Imputation

Supervised and Unsupervised Detections for Multiple Object Tracking in Traffic Scenes: A Comparative Study

no code implementations30 Mar 2020 Hui-Lee Ooi, Guillaume-Alexandre Bilodeau, Nicolas Saunier

In this paper, we propose a multiple object tracker, called MF-Tracker, that integrates multiple classical features (spatial distances and colours) and modern features (detection labels and re-identification features) in its tracking framework.

Multiple Object Tracking

SpotNet: Self-Attention Multi-Task Network for Object Detection

1 code implementation13 Feb 2020 Hughes Perreault, Guillaume-Alexandre Bilodeau, Nicolas Saunier, Maguelonne Héritier

We use those segmentation maps inside the network as a self-attention mechanism to weight the feature map used to produce the bounding boxes, decreasing the signal of non-relevant areas.

Instance Segmentation Multi-Task Learning +1

Autocamera Calibration for traffic surveillance cameras with wide angle lenses

no code implementations20 Jan 2020 Aman Gajendra Jain, Nicolas Saunier

Extrinsic calibration is accomplished by estimating the two vanishing points, on the ground plane, from the motion of vehicles at perpendicular intersections.

Tracking in Urban Traffic Scenes from Background Subtraction and Object Detection

no code implementations15 May 2019 Hui-Lee Ooi, Guillaume-Alexandre Bilodeau, Nicolas Saunier

In this paper, we propose to combine detections from background subtraction and from a multiclass object detector for multiple object tracking (MOT) in urban traffic scenes.

Multiple Object Tracking Object Detection +1

Road User Detection in Videos

1 code implementation28 Mar 2019 Hughes Perreault, Guillaume-Alexandre Bilodeau, Nicolas Saunier, Pierre Gravel

Two new models, RetinaNet-Double and RetinaNet-Flow, are proposed, based respectively on the concatenation of a target frame with a preceding frame, and the concatenation of the optical flow with the target frame.

Video Object Detection

Multiple Object Tracking in Urban Traffic Scenes with a Multiclass Object Detector

no code implementations6 Sep 2018 Hui-Lee Ooi, Guillaume-Alexandre Bilodeau, Nicolas Saunier, David-Alexandre Beaupré

Multiple object tracking (MOT) in urban traffic aims to produce the trajectories of the different road users that move across the field of view with different directions and speeds and that can have varying appearances and sizes.

General Classification Multiple Object Tracking

Improving Multiple Object Tracking with Optical Flow and Edge Preprocessing

no code implementations29 Jan 2018 David-Alexandre Beaupré, Guillaume-Alexandre Bilodeau, Nicolas Saunier

In this paper, we present a new method for detecting road users in an urban environment which leads to an improvement in multiple object tracking.

Multiple Object Tracking Object Detection +1

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