rPPG-Toolbox benchmarks state-of-the-art neural and unsupervised methods for remote photoplethysmography, enabling researchers to measure heart rate and other vital signs from ordinary camera footage. The platform supports both traditional unsupervised algorithms like CHROM, ICA, and GREEN, as well as modern deep learning approaches. It provides standardized evaluation frameworks and supports rapid development of new algorithms for contactless health monitoring.