remotebiosensing/rppg
Benchmark Framework for fair evaluation of rPPG
Provides PyTorch implementations of 20+ deep learning models for remote heart rate and blood pressure estimation from video, spanning CNNs, transformers, and hybrid architectures from 2018-2023. Enables standardized evaluation across models using unified benchmarking infrastructure with support for Docker containerization and Conda environments. Targets video-based cardiovascular monitoring applications, integrating face detection and signal processing pipelines for fair cross-model comparison on rPPG datasets.
315 stars.
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315
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39
Language
Python
License
Apache-2.0
Category
Last pushed
Dec 09, 2025
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