Browse State-of-the-Art › Driver Attention Monitoring
Driver Attention Monitoring
5 papers with code · 0 benchmarks · 7 datasets archive 2025-07-28
Driver attention monitoring is the task of monitoring the attention of a driver.
( Image credit: Predicting Driver Attention in Critical Situations )
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
7 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
5 shown of 5 papers with code (14 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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17 Nov 2017 2 repositories listedBecause critical driving moments are so rare, collecting enough data for these situations is difficult with the conventional in-car data collection protocol---tracking eye movements during driving.
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29 Jun 2025 1 repository listedTo bridge this gap, we introduce Explainable Driver Attention Prediction, a novel task paradigm that jointly predicts spatial attention regions (where), parses attended semantics (what), and provides cognitive reasoning…
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27 Feb 2025 1 repository listedIn such attacks, adversaries inject backdoor triggers by poisoning the training data, creating a backdoor vulnerability: the model performs normally with benign inputs, but produces manipulated gaze directions when a…
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1 Aug 2023 1 repository listedIn this work, we explore the network connection gating mechanism for driver attention prediction (Gate-DAP).
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18 Dec 2019 1 repository listed1) With the semantic images, we introduce their semantic context features and verified the manifest promotion effect for helping the driver attention prediction, where the semantic context features are modeled by a…
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