Domain Adaptation for Semantic Segmentation in Real-World Surveillance and Autonomous Cars

Описание: In this video, we present our latest paper: “Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World Surveillance” published at the WACV 2023 workshop on Real-World Surveillance. We mathematically prove the exact solution to the mixture domain adaptation problem that can adapt on the fly from several source models. Our method can be used for many tasks, including semantic segmentation for real-world surveillance and autonomous cars.

00:00​​ Introduction
00:30 Motivation and synthetic example
05:02 Our method
​​06:44 Experiments
08:43​ Conclusion

Authors: Sébastien Piérard, Anthony Cioppa, Anaïs Halin, Renaud Vandeghen, Maxime Zanella, Benoît Macq, Saïd Mahmoudi, Marc Van Droogenbroeck

Link to the paper:
https://arxiv.org/abs/2211.10119

Code to get started with the method:
https://github.com/rvandeghen/MDA

Don’t hesitate to contact us if you have any questions about the paper or the code!


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Video Credits
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Background videos from Videezy.com and Pexels.com.
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Music credits
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Juno in The Space Maze - Loopop
Classic - Joakim Karud
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Presentation written by Sébastien Piérard, Anthony Cioppa, Anais Halin, and Renaud Vandeghen.
Video produced and edited by Anthony Cioppa and Renaud Vandeghen.