Search Results for author: Marc Van Droogenbroeck

Found 14 papers, 8 papers with code

Semi-Supervised Training to Improve Player and Ball Detection in Soccer

1 code implementation14 Apr 2022 Renaud Vandeghen, Anthony Cioppa, Marc Van Droogenbroeck

More precisely, we design a teacher-student approach in which the teacher produces surrogate annotations on the unlabeled data to be used later for training a student which has the same architecture as the teacher.

SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos

no code implementations14 Apr 2022 Anthony Cioppa, Silvio Giancola, Adrien Deliege, Le Kang, Xin Zhou, Zhiyu Cheng, Bernard Ghanem, Marc Van Droogenbroeck

Tracking objects in soccer videos is extremely important to gather both player and team statistics, whether it is to estimate the total distance run, the ball possession or the team formation.

Benchmark Multiple Object Tracking

Survey and synthesis of state of the art in driver monitoring

no code implementations1 Oct 2021 Anaïs Halin, Jacques G. Verly, Marc Van Droogenbroeck

Road-vehicle accidents are mostly due to human errors, and many such accidents could be avoided by continuously monitoring the driver.

Ghost Loss to Question the Reliability of Training Data

no code implementations3 Sep 2021 Adrien Deliège, Anthony Cioppa, Marc Van Droogenbroeck

For that purpose, we introduce the notion of ghost loss, which can be seen as a regular loss that is zeroed out for some predicted values in a deterministic way and that allows the network to choose an alternative to the given label without being penalized.

Image Classification

Ordinal Pooling

1 code implementation3 Sep 2021 Adrien Deliège, Maxime Istasse, Ashwani Kumar, Christophe De Vleeschouwer, Marc Van Droogenbroeck

More importantly, they also demonstrate that ordinal pooling leads to consistent improvements in the accuracy over average- or max-pooling operations while speeding up the training and alleviating the issue of the choice of the pooling operations and activation functions to be used in the networks.

M4Depth: Monocular depth estimation for autonomous vehicles in unseen environments

1 code implementation20 May 2021 Michaël Fonder, Damien Ernst, Marc Van Droogenbroeck

We use these cost volumes to leverage the visual spatio-temporal constraints imposed by motion and to make the network robust for varied scenes.

Autonomous Vehicles Monocular Depth Estimation

Camera Calibration and Player Localization in SoccerNet-v2 and Investigation of their Representations for Action Spotting

no code implementations19 Apr 2021 Anthony Cioppa, Adrien Deliège, Floriane Magera, Silvio Giancola, Olivier Barnich, Bernard Ghanem, Marc Van Droogenbroeck

Specifically, we distill a powerful commercial calibration tool in a recent neural network architecture on the large-scale SoccerNet dataset, composed of untrimmed broadcast videos of 500 soccer games.

Action Spotting Camera Calibration +2

SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos

2 code implementations26 Nov 2020 Adrien Deliège, Anthony Cioppa, Silvio Giancola, Meisam J. Seikavandi, Jacob V. Dueholm, Kamal Nasrollahi, Bernard Ghanem, Thomas B. Moeslund, Marc Van Droogenbroeck

In this work, we propose SoccerNet-v2, a novel large-scale corpus of manual annotations for the SoccerNet video dataset, along with open challenges to encourage more research in soccer understanding and broadcast production.

Action Spotting Boundary Detection +5

Multimodal and multiview distillation for real-time player detection on a football field

1 code implementation16 Apr 2020 Anthony Cioppa, Adrien Deliège, Noor Ul Huda, Rikke Gade, Marc Van Droogenbroeck, Thomas B. Moeslund

As an alternative, we developed a system that detects players from a unique cheap and wide-angle fisheye camera assisted by a single narrow-angle thermal camera.

Data Augmentation Knowledge Distillation +1

Summarizing the performances of a background subtraction algorithm measured on several videos

no code implementations13 Feb 2020 Sébastien Piérard, Marc Van Droogenbroeck

In this paper, we present a theoretical approach to summarize the performances for multiple videos that preserves the relationships between performance indicators.

Real-Time Semantic Background Subtraction

1 code implementation12 Feb 2020 Anthony Cioppa, Marc Van Droogenbroeck, Marc Braham

Semantic background subtraction SBS has been shown to improve the performance of most background subtraction algorithms by combining them with semantic information, derived from a semantic segmentation network.

Semantic Segmentation

HitNet: a neural network with capsules embedded in a Hit-or-Miss layer, extended with hybrid data augmentation and ghost capsules

1 code implementation18 Jun 2018 Adrien Deliège, Anthony Cioppa, Marc Van Droogenbroeck

In this paper, we show how to redesign a simple network to reach excellent performances, which are better than the results reproduced with CapsNet on several datasets, by replacing a layer with a Hit-or-Miss layer.

Data Augmentation

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