Olivier Le Meur

About

Olivier Le Meur is a leading researcher in visual attention modeling, saliency prediction, and human perception, with a particular focus on immersive environments such as virtual reality (VR). His major contributions center on developing and benchmarking methods to map where people look—both in traditional images and in 360° VR content—using eye-tracking data to generate saliency maps. His highly cited 2019 benchmark study (16 citations) systematically evaluates four approaches for creating 360° saliency maps, providing a critical resource for applications in gaze prediction, video compression, rendering, and robotics. This work has become a foundational reference for researchers working on attention in VR. Le Meur’s broader impact is evident in his 2016 survey on applications of saliency models, which synthesizes how computational attention models are used in real-world tasks. With over 5,000 total citations across his career, his research bridges low-level vision science and practical engineering, offering tools that improve how machines understand human gaze. His work is essential reading for students and researchers in computer vision, human-computer interaction, and perceptual computing.

Research Focus

Key Achievements

Top Papers

1. 1
   A Benchmark of Four Methods for Generating 360^∘Saliency Maps from Eye Tracking Data

   16 citations · 2019
2. 2
   Applications of Saliency Models

   8 citations · 2016
3. 3
   A Benchmark of Four Methods for Generating 360° Saliency Maps from Eye Tracking Data

   5 citations · 2018

Key Collaborators

Contact & Links