1. Anthony Cioppa. Real-time semantics in video sequences. PhD thesis, University of Liège, Belgium, December 2020. Keyword(s): Sport, Soccer, Football, Machine learning, Deep learning, Semantics, Video understanding, Real-time, Semantic segmentation, Action spotting, Dataset, Background subtraction, Online distillation, SoccerNet, DeepSport. [bibtex-entry]



2. Quentin Massoz. Non-invasive, automatic, and real-time characterization of drowsiness based on eye closure dynamics. PhD thesis, University of Liège, Belgium, April 2019. Keyword(s): Drowsiness, Driver monitoring, Face, Eye closure, Pyschomotor vigilance test, Reaction time, CNN, Deep learning. [bibtex-entry]

1. Carles Cantero, Olivier Absil, Carl-Henrik Dahlqvist, and Marc Van Droogenbroeck. NA-SODINN: A deep learning algorithm for exoplanet image detection based on residual noise regimes. Astronomy & Astrophysics, 680:1-24, December 2023. Keyword(s): Exoplanet, Detection, High-contrast imaging, Noise, Noise regime, Gaussian, Laplacian, NA-SODINN. [bibtex-entry]



2. Anthony Cioppa, Adrien Deliège, Silvio Giancola, Bernard Ghanem, and Marc Van Droogenbroeck. Scaling up SoccerNet with multi-view spatial localization and re-identification. Scientific Data, 9(1), June 2022. Keyword(s): SoccerNet-v3, Human Tracking, Player Tracking, Soccer, Football, Deep learning, Machine learning, Artificial intelligence, ARIAC. [bibtex-entry]



3. Michaël Fonder, Damien Ernst, and Marc Van Droogenbroeck. Parallax Inference for Robust Temporal Monocular Depth Estimation in Unstructured Environments. Sensors, 22(23):1-22, December 2022. Keyword(s): Depth, Depth estimation, Deep learning, Drone, UAV, Parallax. [bibtex-entry]



4. Renaud Vandeghen, Gilles Louppe, and Marc Van Droogenbroeck. Adaptive Self-Training for Object Detection. arXiv, abs/2212.05911, December 2022. Keyword(s): Semi-supervised, Self training, Object detection, Artificial intelligence, Machine learning, Deep learning. [bibtex-entry]



5. Michaël Fonder and Marc Ernst, DamienVan Droogenbroeck. M4Depth: Monocular depth estimation for autonomous vehicles in unseen environments. ArXiv, abs/2105.09847, May 2021. Keyword(s): Depth estimation, Drone, UAV, Artificial Intelligence, Deep learning. [bibtex-entry]



6. Adrien Deliège, Anthony Cioppa, and Marc Van Droogenbroeck. Ghost Loss to Question the Reliability of Training Data. IEEE Access, 8:44774-44782, March 2020. Keyword(s): Deep learning, Machine learning, Ghost, Artificial Intelligence, Training data, DeepSport. [bibtex-entry]



7. Adrien Deliège, Anthony Cioppa, and Marc Van Droogenbroeck. HitNet: a neural network with capsules embedded in a Hit-or-Miss layer, extended with hybrid data augmentation and ghost capsules. ArXiv, abs/1806.06519, June 2018. Keyword(s): Neural network, Deep learning, Machine learning, Artificial intelligence, Hit-or-Miss layer, Capsule, Ghost capsule, NMISTi, DeepSport. [bibtex-entry]



8. Carlos Gomez Gonzalez, Olivier Absil, and Marc Van Droogenbroeck. Supervised detection of exoplanets in high-contrast imaging sequences. Astronomy & Astrophysics, 613:1-13, May 2018. Keyword(s): Deep learning, SODINN, VORTEX project, High angular resolution, Image processing, Detection of planets, Sparse decomposition, Detection, Planets and satellites. [bibtex-entry]



9. Quentin Massoz, Jacques Verly, and Marc Van Droogenbroeck. Multi-timescale drowsiness characterization based on a video of a driver's face. Sensors, 18(9):1-17, August 2018. Keyword(s): Drowsiness, Driver monitoring, Face, Eye closure, Pyschomotor vigilance test, Reaction time, CNN, Deep learning. [bibtex-entry]

1. Anthony Cioppa, Silvio Giancola, Adrien Deliège, Vladimir Somers, Floriane Magera, Hassan Mkhallati, Le Kang, Xin Zhou, Zhiyu Cheng, Bernard Ghanem, and Marc Van Droogenbroeck. SoccerNet Exploring the Game with Computer Vision. In Rising Stars in AI Symposium, Thuwal, Saudi Arabia, February 2023. Note: Invited talk. Keyword(s): SoccerNet, Soccer, Football, Deep learning, Machine learning, Artificial intelligence. [bibtex-entry]



2. Michaël Fonder and Marc Van Droogenbroeck. A technique to jointly estimate depth and depth uncertainty for unmanned aerial vehicles. In IEEE International Conference on Systems, Signals and Image Processing (IWSSIP), Ohrid, North Macedonia, pages 1-5, June 2023. Keyword(s): Depth, Depth estimation, Depth uncertainty, Deep learning, Drone, UAV, Parallax. [bibtex-entry]



3. Renaud Vandeghen, Gilles Louppe, and Marc Van Droogenbroeck. Adaptive Self-Training for Object Detection. In IEEE/CVF International Conference on Computer Vision Workshops (ICCV Workshops), Paris, France, pages 914-923, October 2023. Keyword(s): Deep learning, Machine learning, Self-training, Object detection, Semi-supervision, Supervision, Refinement, ASTOD, COCO dataset, DIOR dataset. [bibtex-entry]



4. Anthony Cioppa, Silvio Giancola, Adrien Deliège, Le Kang, Xin Zhou, Zhiyu Cheng, Bernard Ghanem, and Marc Van Droogenbroeck. SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos. In IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), CVsports, New Orleans, Louisiana, USA, pages 3490-3501, June 2022. IEEE. Keyword(s): SoccerNet-v3, Human Tracking, Player Tracking, Soccer, Football, Deep learning, Machine learning, Artificial intelligence, ARIAC. [bibtex-entry]



5. Silvio Giancola, Anthony Cioppa, Adrien Deliège, Floriane Magera, Vladimir Somers, Le Kang, Xin Zhou, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, and et al.. SoccerNet 2022 Challenges Results. In International ACM Workshop on Multimedia Content Analysis in Sports (MMSports), Lisboa, Portugal, pages 75-86, October 2022. ACM. Keyword(s): Challenge, SoccerNet, Human Tracking, Player Tracking, Soccer, Football, Deep learning, Machine learning, Artificial intelligence, ARIAC. [bibtex-entry]



6. Renaud Vandeghen, Anthony Cioppa, and Marc Van Droogenbroeck. Semi-Supervised Training to Improve Detection for Satellite Images. In AI4Copernicus: Earth Observation and Artificial Intelligence for a Safer World, Brussels, Belgium, May 2022. Keyword(s): Semi-supervised, Self training, Satellite, Semantic segmentation, Artificial intelligence, Machine learning, Deep learning. [bibtex-entry]



7. Renaud Vandeghen, Anthony Cioppa, and Marc Van Droogenbroeck. Semi-Supervised Training to Improve Player and Ball Detection in Soccer. In IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), CVsports, New Orleans, Louisiana, USA, pages 3480-3489, June 2022. IEEE. Keyword(s): Semi-supervised, Self training, Soccer, Semantic segmentation, Artificial intelligence, Machine learning, Deep learning, TRAIL. [bibtex-entry]



8. Anthony Cioppa, Adrien Deliège, Floriane Magera, Silvio Giancola, Olivier Barnich, Bernard Ghanem, and Marc Van Droogenbroeck. Camera Calibration and Player Localization in SoccerNet-v2 and Investigation of their Representations for Action Spotting. In IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), CVsports, Nashville, Tennessee, USA, pages 4537-4546, June 2021. Keyword(s): Calibration, SoccerNet, Dataset, Training data, Soccer, Football, Classification, Annotation, Neural network, Deep learning, Machine learning, Artificial intelligence, DeepSport. [bibtex-entry]



9. Adrien Deliège, Anthony Cioppa, Silvio Giancola, Meisam J. Seikavandi, Jacob V. Dueholm, Kamal Nasrollahi, Bernard Ghanem, Thomas B. Moeslund, and Marc Van Droogenbroeck. SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos. In IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), CVsports, Nashville, Tennessee, USA, pages 4508-4519, June 2021. Note: Best CVsports paper award. Keyword(s): Calibration, SoccerNet, Dataset, Training data, Soccer, Football, Classification, Annotation, Neural network, Deep learning, Machine learning, Artificial intelligence, DeepSport, Best paper award. [bibtex-entry]



10. Anthony Cioppa, Adrien Deliège, Silvio Giancola, Bernard Ghanem, Marc Van Droogenbroeck, Rikke Gade, and Thomas B. Moeslund. A Context-Aware Loss Function for Action Spotting in Soccer Videos. In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, Washington, USA, pages 13123-13133, June 2020. Keyword(s): Action spotting, Artificial Intelligence, Soccer, Deep learning, Loss, DeepSport. [bibtex-entry]



11. Anthony Cioppa, Adrien Deliège, Noor Ul Huda, Rikke Gade, Marc Van Droogenbroeck, and Thomas B. Moeslund. Multimodal and multiview distillation for real-time player detection on a football field. In IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), CVsports, Seattle, Washington, USA, pages 3846-3855, June 2020. Note: Best CVsports paper award. Keyword(s): Soccer, Football, Artificial intelligence, Deep learning, Machine learning, Multiview distillation, Multimodal distillation, Knowledge distillation, Player detection, Thermal camera, Fisheye camera, Real-time, DeepSport, Distillation, ViBe, Best paper award. [bibtex-entry]



12. Anthony Cioppa, Adrien Deliège, Maxime Istasse, Christophe De Vleeschouwer, and Marc Van Droogenbroeck. ARTHuS: Adaptive Real-Time Human Segmentation in Sports through Online Distillation. In IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), CVsports, Long Beach, California, USA, pages 2505-2514, June 2019. Note: Best CVsports paper award. Keyword(s): Soccer, Semantic segmentation, Artificial intelligence, Machine learning, Deep learning, CNN, DeepSport, Best paper award. [bibtex-entry]



13. Adrien Deliège, Anthony Cioppa, and Marc Van Droogenbroeck. An Effective Hit-or-Miss Layer Favoring Feature Interpretation as Learned Prototypes Deformations. In AAAI Conference on Artificial Intelligence, Workshop on Network Interpretability for Deep Learning, Honolulu, Hawaii, USA, pages 1-8, January 2019. Keyword(s): Deep learning, Machine learning, Artificial intelligence, Neural network, Classification, Capsule, HitNet, Hit-or-miss layer, Feature interpretation, Centripetal loss, Prototype, DeepSport. [bibtex-entry]



14. Adrien Deliège, A. Kumar, Maxime Istasse, Christophe De Vlesschouwer, and Marc Van Droogenbroeck. Ordinal Pooling. In British Machine Vision Conference (BMVC), Cardiff, Wales, pages 1-12, September 2019. Keyword(s): Deep learning, Machine learning, Pooling, Artificial intelligence, Neural network, Convolutional layer, CNN, DeepSport. [bibtex-entry]



15. Michaël Fonder and Marc Van Droogenbroeck. Mid-Air: A multi-modal dataset for extremely low altitude drone flights. In IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), UAVision, Long Beach, California, USA, pages 553-562, June 2019. Keyword(s): UAV, Dataset, Mid-Air, Positioning, Benchmark, Drone, Artificial Intelligence, Deep learning. [bibtex-entry]



16. Anthony Cioppa, Adrien Deliège, and Marc Van Droogenbroeck. A bottom-up approach based on semantics for the interpretation of the main camera stream in soccer games. In IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), CVsports, Salt Lake City, Utah, USA, pages 1846-1855, June 2018. Note: Best CVsports paper award. Keyword(s): Soccer, Semantic segmentation, Artificial intelligence, Deep learning, Machine learning, CNN, DeepSport, Best paper award. [bibtex-entry]



17. Marc Braham, Sébastien Piérard, and Marc Van Droogenbroeck. Semantic Background Subtraction. In IEEE International Conference on Image Processing, Beijing, China, pages 4552-4556, September 2017. Keyword(s): Background subtraction, Change detection, Semantic segmentation, Scene labeling, Scene parsing, Classification, Machine learning, Deep learning, CDNet 2014. [bibtex-entry]



18. Marc Braham and Marc Van Droogenbroeck. Deep Background Subtraction with Scene-Specific Convolutional Neural Networks. In International Conference on Systems, Signals and Image Processing (IWSSIP), Bratislava, Slovakia, pages 1-4, May 2016. Keyword(s): Background subtraction, Deep learning, Machine learning, CDNet, Change detection, CDNet 2014. [bibtex-entry]

1. Anthony Cioppa, Silvio Giancola, Adrien Deliège, Bernard Ghanem, and Marc Van Droogenbroeck. Goal! A practical guide to soccer video understanding. Norwegian Artificial Intelligence Society Symposium, Tutorial, May 2022. Keyword(s): SoccerNet, Dataset, Challennge, Soccer, Football, Classification, Annotation, Deep learning, Machine learning, Artificial intelligence. [bibtex-entry]



2. Marc Van Droogenbroeck, Marc Braham, and Sébastien Piérard. Foreground and background detection method. Chinese Patent Office, CN 109389618 B2, 18 pages, March 2022. Keyword(s): Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence. [bibtex-entry]



3. Anthony Cioppa, Adrien Deliège, Silvio Giancola, Meisam Seikavandi, Jacob Dueholm, Kamal Nasrollahi, Bernard Ghanem, Thomas Moeslund, and Marc Van Droogenbroeck. SoccerNet challenge: Task presentation and winner announcement. Oral communication, June 2021. Keyword(s): SoccerNet, Dataset, Challennge, Soccer, Football, Classification, Annotation, Deep learning, Machine learning, Artificial intelligence, DeepSport. [bibtex-entry]



4. Renaud Vandeghen. Semi-supervised learning for object detection in satellite images. Master's thesis, University of Liège, Belgium, June 2020. Keyword(s): Satellite imaging, Semi-supervised, Self training, Detection, Artificial intelligence, Machine learning, Deep learning. [bibtex-entry]



5. Marc Van Droogenbroeck, Marc Braham, and Anthony Cioppa. Foreground and background detection method. United States Patent and Trademark Office, US 10,706,558 B2, 26 pages, July 2020. Keyword(s): Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence, DeepSport. [bibtex-entry]



6. Marc Van Droogenbroeck, Marc Braham, and Sébastien Piérard. Foreground and background detection method. United States Patent and Trademark Office, US 10614736 B2, 16 pages, April 2020. Keyword(s): Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence. [bibtex-entry]



7. Marc Van Droogenbroeck, Marc Braham, and Sébastien Piérard. Foreground and background detection method. European Patent Office, EP 3438929 B2, July 2020. Keyword(s): Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence. [bibtex-entry]



8. Marc Van Droogenbroeck, Marc Braham, and Sébastien Piérard. Foreground and background detection method. Chinese Patent Office, CN109389618A, February 2019. Keyword(s): Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence. [bibtex-entry]



9. Marc Van Droogenbroeck, Adrien Deliège, and Anthony Cioppa. Image classification using neural networks. World Intellectual Property Organization, WO 2019/238976, 55 pages, December 2019. Keyword(s): Patent, Machine learning, Deep learning, Artificial intelligence, HitNet, Capsule, Data augmentation, DeepSport. [bibtex-entry]



10. Marc Van Droogenbroeck, Adrien Deliège, and Anthony Cioppa. Image classification using neural networks. European Patent Office, EP 3 582 142 A1, 32 pages, June 2018. Keyword(s): Patent, Machine learning, Deep learning, Artificial intelligence, HitNet, Capsule, Data augmentation, DeepSport. [bibtex-entry]

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