Bastien Rigault
Papers
2
Total Citations
70
H-Index
2
About
Bastien Rigault is a leading researcher at the intersection of computer vision, deep learning, and autonomous drone systems. His work focuses on enabling drones to perceive and interpret their environment in real time, with a strong emphasis on disaster relief and surveillance applications. Rigault’s most influential contribution is his 2022 paper on deep learning with RGB and thermal imagery for drone-based monitoring, which has garnered 68 citations. This work demonstrated how combining visual and thermal data can significantly enhance object detection and situational awareness in restricted disaster scenarios, as defined by Japan’s Advanced Robotics Foundation. More recently, Rigault has pushed the boundaries of zero-shot learning by integrating YOLO-World and GPT-4V large multimodal models (LMMs) for person detection and action recognition in drone imagery. His 2024 paper, though newly published, signals a paradigm shift toward adaptable, language-guided perception systems that require no task-specific training data. Rigault’s research is pivotal for advancing autonomous drones capable of operating in unpredictable, high-stakes environments, making him a key figure in the next generation of intelligent aerial robotics.
Research Focus
Key Achievements
Top Papers
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- 2