1. 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.
   

   @article{Cioppa2022Scaling,
   title = {Scaling up {SoccerNet} with multi-view spatial localization and re-identification},
   author = {Cioppa, Anthony and Deli{\`e}ge, Adrien and Giancola, Silvio and Ghanem, Bernard and Van Droogenbroeck, Marc},
   journal = {Scientific Data},
   volume = {9},
   number = {1},
   month = {June},
   year = {2022},
   keywords = {SoccerNet-v3, Human Tracking, Player Tracking, Soccer, Football, Deep learning, Machine learning, Artificial intelligence, ARIAC},
   doi = {10.1038/s41597-022-01469-1},
   url = {https://doi.org/10.1038/s41597-022-01469-1} 
   }
   




2. 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.
   

   @article{Fonder2022Parallax,
   title = {Parallax Inference for Robust Temporal Monocular Depth Estimation in Unstructured Environments},
   author = {Fonder, Micha{\"e}l and Ernst, Damien and Van Droogenbroeck, Marc},
   journal = {Sensors},
   volume = {22},
   number = {23},
   pages = {1-22},
   month = {December},
   year = {2022},
   keywords = {Depth, Depth estimation, Deep learning, Drone, UAV, Parallax},
   doi = {10.3390/s22239374},
   url = {https://doi.org/10.3390/s22239374} 
   }
   




3. Henri Mertens and Marc Van Droogenbroeck. Error-rate in Viterbi decoding of a duobinary signal in presence of noise and distortions: theory and simulation. arXiv, abs/2209.01360, 2022. Keyword(s): Viterbi, Decoder, Modulation, Noise, Distortion.
   

   @article{Mertens2022ErrorRate,
   title = {Error-rate in {V}iterbi decoding of a duobinary signal in presence of noise and distortions: theory and simulation},
   author = {Mertens, Henri and Van Droogenbroeck, Marc},
   journal = {arXiv},
   year = {2022},
   volume = {abs/2209.01360},
   eprint = {2209.01360},
   doi = {10.48550/arXiv.2209.01360},
   url = {https://doi.org/10.48550/arXiv.2209.01360},
   eprinttype = {arXiv},
   keywords = {Viterbi, Decoder, Modulation, Noise, Distortion} 
   }
   




4. Milton Giovanny Moncayo-Unda, Marc Van Droogenbroeck, Ismaïl Saadi, and Mario Cools. An anonymised longitudinal GPS location dataset to understand changes in activity-travel behaviour between pre- and post-COVID periods. Data in Brief, 45:1-15, November 2022. Note: Online first. Keyword(s): Google location history, GPS, Activity point location, Travel, Covid, Timeline tracking, Longitudinal data.
   

   @article{MoncayoUnda2022AnAnonymised,
   title = {An anonymised longitudinal {GPS} location dataset to understand changes in activity-travel behaviour between pre- and post-{COVID} periods},
   author = {Moncayo-Unda, Milton Giovanny and Van Droogenbroeck, Marc and Saadi, Isma{\"\i}l and Cools, Mario},
   journal = {Data in Brief},
   volume = {45},
   pages = {1-15},
   month = Nov,
   year = {2022},
   keywords = {Google location history, GPS, Activity point location, Travel, Covid, Timeline tracking, Longitudinal data},
   note = {Online first},
   doi = {10.1016/j.dib.2022.108776},
   url = {https://doi.org/10.1016/j.dib.2022.108776} 
   }
   




5. Sébastien Piérard, Marc Braham, and Marc Van Droogenbroeck. An exploration of the performances achievable by combining unsupervised background subtraction algorithms. ArXiv, abs/2202.12563, February 2022. Keyword(s): Background subtraction, Combination, Majority vote, BKS, Evaluation, Performance, Summarization, Change detection, Classification performance, CDNet 2014, ARIAC.
   

   @article{Pierar2022AnExploration,
   title = {An exploration of the performances achievable by combining unsupervised background subtraction algorithms},
   author = {Pi\'erard, S\'ebastien and Braham, Marc and {Van Droogenbroeck}, Marc},
   journal = {ArXiv},
   month = {February},
   year = {2022},
   volume = {abs/2202.12563},
   eprint = {2202.12563},
   doi = {10.48550/arXiv.2202.12563},
   url = {https://doi.org/10.48550/arXiv.2202.12563},
   eprinttype = {arXiv},
   keywords = {Background subtraction, Combination, Majority vote, BKS, Evaluation, Performance, Summarization, Change detection, Classification performance, CDNet 2014, ARIAC} 
   }
   




6. 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.
   

   @article{Vandeghen2002Adaptive-arxiv,
   title = {Adaptive Self-Training for Object Detection},
   author = {Vandeghen, Renaud and Louppe, Gilles and Van Droogenbroeck, Marc},
   journal = {arXiv},
   month = {December},
   year = {2022},
   volume = {abs/2212.05911},
   eprint = {2212.05911},
   doi = {10.48550/arXiv.2212.05911},
   url = {https://doi.org/10.48550/arXiv.2212.05911},
   eprinttype = {arXiv},
   keywords = {Semi-supervised, Self training, Object detection, Artificial intelligence, Machine learning, Deep learning} 
   }
   

1. Faustine Cantalloube, Valentin Christiaens, Carles Cantero, Evert Nasedkin, Anthony Cioppa, Olivier Absil, Markus J. Bonse, Philippe Delorme, Carlos A. Gomez-Gonzalez, Sandrine Juillard, Johan Mazoyer, Matthias Samland, Jean-Baptiste Ruffio, and Marc Van Droogenbroeck. Exoplanet imaging data challenge, phase II: characterization of exoplanet signals in high-contract images. In Dirk Schmidt, Laura Schreiber, and Elise Vernet, editors, Adaptive Optics Systems VIII, volume 12185, pages 8-24, August 2022. SPIE. Keyword(s): Exoplanet, Benchmarking, EIDC, Challenge.
   

   @inproceedings{Cantalloube2022-EIDC-II,
   title = {Exoplanet imaging data challenge, phase {II}: characterization of exoplanet signals in high-contract images},
   author = {Cantalloube, Faustine and Christiaens, Valentin and Cantero, Carles and Nasedkin, Evert and Cioppa, Anthony and Absil, Olivier and Bonse, Markus J. and Delorme, Philippe and Gomez-Gonzalez, Carlos A. and Juillard, Sandrine and Mazoyer, Johan and Samland, Matthias and Ruffio, Jean-Baptiste and Van Droogenbroeck, Marc},
   booktitle = {Adaptive Optics Systems VIII},
   volume = {12185},
   pages = {8-24},
   month = {August},
   year = {2022},
   publisher = {SPIE},
   editor = {Schmidt, Dirk and Schreiber, Laura and Vernet, Elise},
   keywords = {Exoplanet, Benchmarking, EIDC, Challenge},
   doi = {10.1117/12.2627968},
   url = {https://doi.org/10.1117/12.2627968} 
   }
   




2. 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.
   

   @inproceedings{Cioppa2022SoccerNetTracking,
   title = {{SoccerNet}-{T}racking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos},
   author = {Cioppa, Anthony and Giancola, Silvio and Deli{\`e}ge, Adrien and Kang, Le and Zhou, Xin and Cheng, Zhiyu and Ghanem, Bernard and Van Droogenbroeck, Marc},
   booktitle = {IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), CVsports},
   pages = {3490-3501},
   month = {June},
   year = {2022},
   publisher = {IEEE},
   address = {New Orleans, Louisiana, USA},
   keywords = {SoccerNet-v3, Human Tracking, Player Tracking, Soccer, Football, Deep learning, Machine learning, Artificial intelligence, ARIAC},
   doi = {10.1109/cvprw56347.2022.00393},
   url = {https://doi.org/10.1109/CVPRW56347.2022.00393} 
   }
   




3. 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.
   

   @inproceedings{Giancola2022SoccerNet,
   title = {{SoccerNet} 2022 Challenges Results},
   author = {Giancola, Silvio and Cioppa, Anthony and Deli{\`e}ge, Adrien and Magera, Floriane and Somers, Vladimir and Kang, Le and Zhou, Xin and Barnich, Olivier and De Vleeschouwer, Christophe and Alahi, Alexandre and Ghanem, Bernard and Van Droogenbroeck, Marc and et al.},
   booktitle = {International ACM Workshop on Multimedia Content Analysis in Sports (MMSports)},
   pages = {75-86},
   month = {October},
   year = {2022},
   publisher = {ACM},
   address = {Lisboa, Portugal},
   keywords = {Challenge, SoccerNet, Human Tracking, Player Tracking, Soccer, Football, Deep learning, Machine learning, Artificial intelligence, ARIAC},
   doi = {10.1145/3552437.3558545},
   url = {https://doi.org/10.1145/3552437.3558545} 
   }
   




4. Raphaël La Rocca, Anthony Cioppa, Marc Van Droogenbroeck, Gauthier Eppe, and Loïc Quinton. Relational Graph Convolutional Network for Robust Mass Spectrum Classification. In International Mass Spectrometry Conference (IMSC), Maastricht, the Netherlands, August-September 2022. Keyword(s): Mass Spectrometry, Learning, Classification, Graph, Graph convolutional Network.
   

   @inproceedings{LaRocca2022Relational,
   title = {Relational Graph Convolutional Network for Robust Mass Spectrum Classification},
   author = {La Rocca, Rapha{\"e}l and Cioppa, Anthony and Van Droogenbroeck, Marc and Eppe, Gauthier and Quinton, Lo{\"{\i}}c},
   booktitle = {International Mass Spectrometry Conference (IMSC)},
   year = {2022},
   month = {August-September},
   address = {Maastricht, the Netherlands},
   keywords = {Mass Spectrometry, Learning, Classification, Graph, Graph convolutional Network},
   url = {https://hdl.handle.net/2268/293820} 
   }
   




5. 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.
   

   @inproceedings{Vandeghen2022SemiSupervisedSatellite,
   title = {Semi-Supervised Training to Improve Detection for Satellite Images},
   author = {Vandeghen, Renaud and Cioppa, Anthony and Van Droogenbroeck, Marc},
   booktitle = {AI4Copernicus: Earth Observation and Artificial Intelligence for a Safer World},
   month = {May},
   year = {2022},
   address = {Brussels, Belgium},
   keywords = {Semi-supervised, Self training, Satellite, Semantic segmentation, Artificial intelligence, Machine learning, Deep learning} url = {https://hdl.handle.net/2268/290000} 
   }
   




6. 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.
   

   @inproceedings{Vandeghen2022SemiSupervised,
   title = {Semi-Supervised Training to Improve Player and Ball Detection in Soccer},
   author = {Vandeghen, Renaud and Cioppa, Anthony and Van Droogenbroeck, Marc},
   booktitle = {IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), CVsports},
   pages = {3480-3489},
   month = {June},
   year = {2022},
   publisher = {IEEE},
   address = {New Orleans, Louisiana, USA},
   keywords = {Semi-supervised, Self training, Soccer, Semantic segmentation, Artificial intelligence, Machine learning, Deep learning, TRAIL} doi = {10.1109/cvprw56347.2022.00392},
   url = {https://doi.org/10.1109/CVPRW56347.2022.00392} 
   }
   

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.
   

   @misc{Cioppa2022Goal,
   title = {Goal! A practical guide to soccer video understanding},
   author = {Cioppa, Anthony and Giancola, Silvio and Deli\`ege, Adrien and Ghanem, Bernard and {Van Droogenbroeck}, Marc},
   howpublished = {Norwegian Artificial Intelligence Society Symposium, Tutorial},
   address = {Oslo, Norway},
   month = {May},
   year = {2022},
   keywords = {SoccerNet, Dataset, Challennge, Soccer, Football, Classification, Annotation, Deep learning, Machine learning, Artificial intelligence},
   url = {https://hdl.handle.net/2268/289998} 
   }
   




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.
   

   @misc{Vandroogenbroeck2022Foreground-CN,
   title = {Foreground and background detection method},
   author = {{Van Droogenbroeck}, Marc and Braham, Marc and Pi{\'e}rard, S{\'e}bastien},
   month = {March},
   year = {2022},
   howpublished = {Chinese Patent Office, CN 109389618 B2, 18 pages},
   keywords = {Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence} 
   }
   

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