Loris HRTF dataset

This dataset comprises Head-Related Transfer Functions (HRTFs) generated through an advanced data-driven, machine-learning-based approach. These HRTFs are personalized, direction-dense, and lowpass-filtered, derived from detailed meshes of individual user's head and a non-uniform set of dynamic data measurements. Please refer to the paper titled "An Approach for Mesh-Based Generation of Spatially Dense, Lowpass-Filtered, Individualized HRTFs Using Dynamic Data Acquisition" by Quattrini et al., presented at the AES 156th Convention, held from June 15–17, 2024, in Madrid, Spain.