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Driver Attention Monitoring

Driver attention monitoring is the task of monitoring the attention of a driver.

( Image credit: Predicting Driver Attention in Critical Situations )

Papers

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Showing 1–14 of 14 papers

TitleStatusHype
Predicting Driver Attention in Critical SituationsCode1
Where, What, Why: Towards Explainable Driver Attention PredictionCode1
DADA: Driver Attention Prediction in Driving Accident ScenariosCode0
Gated Driver Attention PredictorCode0
SecureGaze: Defending Gaze Estimation Against Backdoor AttacksCode0
Combining Deep and Depth: Deep Learning and Face Depth Maps for Driver Attention Monitoring—0
DADA-2000: Can Driving Accident be Predicted by Driver Attention? Analyzed by A Benchmark—0
FBLNet: FeedBack Loop Network for Driver Attention Prediction—0
Latent Embedding Clustering for Occlusion Robust Head Pose Estimation—0
From Depth Data to Head Pose Estimation: a Siamese approach—0
STDA: Spatio-Temporal Dual-Encoder Network Incorporating Driver Attention to Predict Driver Behaviors Under Safety-Critical Scenarios—0
AHMF: Adaptive Hybrid-Memory-Fusion Model for Driver Attention Prediction—0
CoCAtt: A Cognitive-Conditioned Driver Attention Dataset—0
CoCAtt: A Cognitive-Conditioned Driver Attention Dataset (Supplementary Material)—0
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