Tim Lebailly

École Polytechnique Fédérale de Lausanne

Papers

Total Citations

H-Index

About

Tim Lebailly is a researcher whose work lies at the intersection of computer vision, robotics, and autonomous systems, with a primary focus on human motion prediction. His most impactful contribution, the "Motion Prediction Using Temporal Inception Module," introduces a novel deep learning architecture that addresses a critical limitation in existing sequence-to-sequence models: their inability to effectively exploit multiple temporal scales for varying input lengths. By adapting the Inception module—originally designed for spatial feature extraction—to the temporal domain, Lebailly’s approach enables more robust and accurate predictions of human movement, a vital capability for safe and responsive autonomous driving and robotic interaction. This work, published in 2021, has garnered 41 citations, underscoring its relevance and influence in a rapidly evolving field. A prior version from 2020 also received recognition, demonstrating the iterative refinement of his ideas. Lebailly’s research bridges the gap between theoretical deep learning advances and practical, real-world applications, making him a notable contributor to the development of intelligent systems that must anticipate and react to human behavior.