Pauline Luc

Papers

Total Citations

272

H-Index

About

Pauline Luc is a computer vision researcher whose work sits at the intersection of deep learning, video understanding, and scene anticipation. She is best known for her pioneering contributions to the field of future frame prediction, particularly her highly influential 2017 paper "Predicting Deeper into the Future of Semantic Segmentation," which has garnered over 235 citations and represents a landmark advance in visual anticipation research. Rather than predicting raw pixel values, Luc's approach focuses on forecasting future semantic segmentation maps — a richer, more structured representation of visual scenes — making her work directly applicable to safety-critical real-time systems such as autonomous vehicles and robotics. By enabling machines to anticipate how a scene will evolve before it happens, her research addresses one of the fundamental challenges in building intelligent systems capable of proactive decision-making. Her contributions have had a meaningful impact on how the research community approaches video prediction tasks, shifting focus toward semantically meaningful outputs over low-level pixel generation. Her work continues to serve as a foundational reference for researchers working on video understanding, predictive modeling, and embodied AI.