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Publications about 'Semantic segmentation'
Thesis
  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. Benjamin Laugraud. Motion-aware temporal median filtering for robust background estimation. PhD thesis, University of Liège, Belgium, March 2020. Keyword(s): Background estimation, Background initialization, Background generation, Motion detection, Background subtraction, Optical flow, Semantic segmentation, Scene parsing, Median filtering, SBI dataset, SBMnet dataset, LaBGen, LaBGen-P, LaBGen-OF, LaBGen-P-Semantic, Computer vision, Image processing. [bibtex-entry]


Articles in journal or book chapters
  1. Anthony Cioppa, Marc Braham, and Marc Van Droogenbroeck. Asynchronous semantic background subtraction. Journal of Imaging, 6(50):1-20, June 2020. Keyword(s): Background subtraction, Real time, Change detection, Semantic segmentation, Semantic background subtraction, CDNet 2014, DeepSport. [bibtex-entry]


  2. Benjamin Laugraud, Sébastien Piérard, and Marc Van Droogenbroeck. LaBGen-P-Semantic: A First Step for Leveraging Semantic Segmentation in Background Generation. Journal of Imaging, 4(7):86, June 2018. Keyword(s): Background generation, Background initialization, LaBGen, Semantics. [bibtex-entry]


Conference articles
  1. Sébastien Piérard, Anthony Cioppa, Anaï Halin, Renaud Vandeghen, Maxime Zanella, Benoît Macq, Saïd Mahmoudi, and Marc Van Droogenbroeck. Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World Surveillance. In IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), waikoloa, January 2023. Note: Accepted for publication. Keyword(s): Domain adaptation, Semantic segmentation, ARIAC. [bibtex-entry]


  2. 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]


  3. 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]


  4. Anthony Cioppa, Marc Van Droogenbroeck, and Marc Braham. Real-Time Semantic Background Subtraction. In IEEE International Conference on Image Processing (ICIP), Abu Dhabi, United Arab Emirates, pages 3214-3218, October 2020. Keyword(s): Background subtraction, Real time, Change detection, Semantic segmentation, Semantic background subtraction, DeepSport, CDNet 2014. [bibtex-entry]


  5. 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]


  6. 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]


  7. 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]


Miscellaneous
  1. 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]


  2. 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]


  3. 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]


  4. 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]


  5. 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]



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Last modified: Thu Dec 1 17:02:14 2022