EM-Net, a MobileNetV3-based gaze estimator with a Swin-style attention branch and an EM refinement module, reports angular-error gains of 0.08 to 0.24 degrees over GazeNAS-ETH using 50% training data.
Experimental road safety study of the actual driver reaction to the street ads using eye tracking, multiple linear regression and decision trees methods,
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EM-Net: Gaze Estimation with Expectation Maximization Algorithm
EM-Net, a MobileNetV3-based gaze estimator with a Swin-style attention branch and an EM refinement module, reports angular-error gains of 0.08 to 0.24 degrees over GazeNAS-ETH using 50% training data.