ArticleScientific data2023
GazeBaseVR, a large-scale, longitudinal, binocular eye-tracking dataset collected in virtual reality.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Eye-tracking-while-reading: A living survey of datasets with open library support.Behavior research methods · 2026Article
- Do Two Eyes Identify Better than One? Interpretable Binocular Dynamics for Virtual Reality Gaze Biometrics.Journal of eye movement research · 2026Article
- Comprehensive dataset of features describing eye-gaze dynamics across multiple tasks.Scientific data · 2026Article
- Exploring, walking, and interacting in virtual reality with simulated low vision: a living contextual dataset.Scientific data · 2025Article
- Unstable foveation's impact on reading, object tracking, and its implications for diagnosing and intervening in reading difficulties.Scientific reports · 2025Article
- The percentile-matching technique for synthetic eye tracking signal degradation: A biometric case study.PloS one · 2025Article
- Exploring Gaze Dynamics in Virtual Reality through Multiscale Entropy Analysis.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
We present GazeBaseVR, a large-scale, longitudinal, binocular eye-tracking (ET) dataset collected at 250 Hz with an ET-enabled virtual-reality (VR) headset. GazeBaseVR comprises 5,020 binocular recordings from a diverse population of 407 college-aged participants. Participants were recorded up to six times each over a 26-month period, each time performing a series of five different ET tasks: (1) a vergence task, (2) a horizontal smooth pursuit task, (3) a video-viewing task, (4) a self-paced reading task, and (5) a random oblique saccade task. Many of these participants have also been recorded for two previously published datasets with different ET devices, and 11 participants were recorded before and after COVID-19 infection and recovery. GazeBaseVR is suitable for a wide range of research on ET data in VR devices, especially eye movement biometrics due to its large population and longitudinal nature. In addition to ET data, additional participant details are provided to enable further research on topics such as fairness.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.