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New Patch-level Gaze Distribution Prediction Method Improves Gaze Following Accuracy

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method called Patch-level Gaze Distribution Prediction (PDP) to improve gaze following accuracy. This approach predicts a patch-level gaze distribution, which accounts for variations in annotations and better integrates the prediction of the gaze target with the determination of whether the target is within or outside the image. Experiments on public datasets demonstrate that PDP enhances performance on both subtasks compared to previous methods. AI

IMPACT This research could lead to more accurate gaze tracking systems for applications in human-computer interaction and augmented reality.

RANK_REASON The cluster contains an academic paper detailing a new method for a computer vision task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Patch-level Gaze Distribution Prediction Method Improves Gaze Following Accuracy

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The cluster contains an academic paper detailing a new method for a computer vision task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Qiaomu Miao, Minh Hoai, Dimitris Samaras ·

    Patch-level Gaze Distribution Prediction for Gaze Following

    arXiv:2211.11062v2 Announce Type: replace Abstract: Gaze following aims to predict where a person is looking in a scene, by predicting the target location, or indicating that the target is located outside the image. Recent works detect the gaze target by training a heatmap regres…

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