# The First Vision For Vitals (V4V) Challenge for Non-Contact Video-Based Physiological Estimation

arXiv: https://arxiv.org/abs/2109.10471 · HTML: https://mlsanity.com/paper/2109.10471/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- Builds on 21 of its 44 references that are in the map.
- First posted on arXiv 22 Sep 2021.

## Builds on (most cited first, 21 of 21)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [A Simple Framework for Contrastive Learning of Visual Representations](https://mlsanity.com/paper/2002.05709/) (2020)
- [Momentum Contrast for Unsupervised Visual Representation Learning](https://mlsanity.com/paper/1911.05722/) (2019)
- [TSM: Temporal Shift Module for Efficient Video Understanding](https://mlsanity.com/paper/1811.08383/) (2018)
- [DeepPhys: Video-Based Physiological Measurement Using Convolutional Attention Networks](https://mlsanity.com/paper/1805.07888/) (2018)
- [S3FD: Single Shot Scale-invariant Face Detector](https://mlsanity.com/paper/1708.05237/) (2017)
- [Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement](https://mlsanity.com/paper/2006.03790/) (2020)
- [Remote Photoplethysmograph Signal Measurement from Facial Videos Using Spatio-Temporal Networks](https://mlsanity.com/paper/1905.02419/) (2019)
- [Video-based Remote Physiological Measurement via Cross-verified Feature Disentangling](https://mlsanity.com/paper/2007.08213/) (2020)
- [On Face Segmentation, Face Swapping, and Face Perception](https://mlsanity.com/paper/1704.06729/) (2017)
- [Towards Inheritable Models for Open-Set Domain Adaptation](https://mlsanity.com/paper/2004.04388/) (2020)
- [VIPL-HR: A Multi-modal Database for Pulse Estimation from Less-constrained Face Video](https://mlsanity.com/paper/1810.04927/) (2018)
- [Meta-rPPG: Remote Heart Rate Estimation Using a Transductive Meta-Learner](https://mlsanity.com/paper/2007.06786/) (2020)
- [Your Classifier can Secretly Suffice Multi-Source Domain Adaptation](https://mlsanity.com/paper/2103.11169/) (2021)
- [Class-Incremental Domain Adaptation](https://mlsanity.com/paper/2008.01389/) (2020)
- [Unsupervised Cross-Modal Alignment for Multi-Person 3D Pose Estimation](https://mlsanity.com/paper/2008.01388/) (2020)
- [iPhys: An Open Non-Contact Imaging-Based Physiological Measurement Toolbox](https://mlsanity.com/paper/1901.04366/) (2019)
- [Semi-Supervised Visual Representation Learning for Fashion Compatibility](https://mlsanity.com/paper/2109.08052/) (2021)
- [The Benefit of Distraction: Denoising Remote Vitals Measurements using Inverse Attention](https://mlsanity.com/paper/2010.07770/) (2020)
- [The 1st Challenge on Remote Physiological Signal Sensing (RePSS)](https://mlsanity.com/paper/2003.11756/) (2020)
- [Deep-HR: Fast Heart Rate Estimation from Face Video Under Realistic Conditions](https://mlsanity.com/paper/2002.04821/) (2020)

## Built on by (most cited first, 19 of 19)

- [Camera Measurement of Physiological Vital Signs](https://mlsanity.com/paper/2111.11547/) (2021)
- [Neuron Structure Modeling for Generalizable Remote Physiological Measurement](https://mlsanity.com/paper/2303.05955/) (2023)
- [Advancing Generalizable Remote Physiological Measurement through the Integration of Explicit and Implicit Prior Knowledge](https://mlsanity.com/paper/2403.06947/) (2024)
- [PhysMLE: Generalizable and Priors-Inclusive Multi-task Remote Physiological Measurement](https://mlsanity.com/paper/2405.06201/) (2024)
- [Efficient Mixture-of-Expert for Video-based Driver State and Physiological Multi-task Estimation in Conditional Autonomous Driving](https://mlsanity.com/paper/2410.21086/) (2024)
- [Bi-TTA: Bidirectional Test-Time Adapter for Remote Physiological Measurement](https://mlsanity.com/paper/2409.17316/) (2024)
- [Instantaneous Physiological Estimation using Video Transformers](https://mlsanity.com/paper/2202.12368/) (2022)
- [Perfusion assessment via local remote photoplethysmography (rPPG)](https://mlsanity.com/paper/2208.13840/) (2022)
- [Align the GAP: Prior-based Unified Multi-Task Remote Physiological Measurement Framework For Domain Generalization and Personalization](https://mlsanity.com/paper/2506.16160/) (2025)
- [Phase-shifted remote photoplethysmography for estimating heart rate and blood pressure from facial video](https://mlsanity.com/paper/2401.04560/) (2024)
- [Deep adaptative spectral zoom for improved remote heart rate estimation](https://mlsanity.com/paper/2403.06902/) (2024)
- [Sage Deer: A Super-Aligned Driving Generalist Is Your Copilot](https://mlsanity.com/paper/2505.10257/) (2025)
- [Remote Bio-Sensing: Open Source Benchmark Framework for Fair Evaluation of rPPG](https://mlsanity.com/paper/2307.12644/) (2023)
- [Periodic-MAE: Periodic Video Masked Autoencoder for rPPG Estimation](https://mlsanity.com/paper/2506.21855/) (2025)
- [Deep Learning Technology for Face Forgery Detection: A Survey](https://mlsanity.com/paper/2409.14289/) (2024)
- [R2I-rPPG: A Robust Region of Interest Selection Method for Remote Photoplethysmography to Extract Heart Rate](https://mlsanity.com/paper/2410.15851/) (2024)
- [Period-LLM: Extending the Periodic Capability of Multimodal Large Language Model](https://mlsanity.com/paper/2505.24476/) (2025)
- [CAST-Phys: Contactless Affective States Through Physiological signals Database](https://mlsanity.com/paper/2507.06080/) (2025)
- [LQ-rPPG: A Label-Quantized Coarse-to-Fine Learning Framework for Remote Physiological Measurement](https://mlsanity.com/paper/2605.23174/) (2026)

## Abstract (arXiv)

Telehealth has the potential to offset the high demand for help during public health emergencies, such as the COVID-19 pandemic. Remote Photoplethysmography (rPPG) - the problem of non-invasively estimating blood volume variations in the microvascular tissue from video - would be well suited for these situations. Over the past few years a number of research groups have made rapid advances in remote PPG methods for estimating heart rate from digital video and obtained impressive results. How these various methods compare in naturalistic conditions, where spontaneous behavior, facial expressions, and illumination changes are present, is relatively unknown. To enable comparisons among alternative methods, the 1st Vision for Vitals Challenge (V4V) presented a novel dataset containing high-resolution videos time-locked with varied physiological signals from a diverse population. In this paper, we outline the evaluation protocol, the data used, and the results. V4V is to be held in conjunction with the 2021 International Conference on Computer Vision.