mlsanityData to 7 Oct 2026

A Review of Driver Gaze Estimation and Application in Gaze Behavior Understanding

arXiv 2307.01470 ↗First posted 4 Jul 2023cs.CV cs.HC cs.LGcited by 12

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Abstract (arXiv)

Driver gaze plays an important role in different gaze-based applications such as driver attentiveness detection, visual distraction detection, gaze behavior understanding, and building driver assistance system. The main objective of this study is to perform a comprehensive summary of driver gaze fundamentals, methods to estimate driver gaze, and it's applications in real world driving scenarios. We first discuss the fundamentals related to driver gaze, involving head-mounted and remote setup based gaze estimation and the terminologies used for each of these data collection methods. Next, we list out the existing benchmark driver gaze datasets, highlighting the collection methodology and the equipment used for such data collection. This is followed by a discussion of the algorithms used for driver gaze estimation, which primarily involves traditional machine learning and deep learning based techniques. The estimated driver gaze is then used for understanding gaze behavior while maneuvering through intersections, on-ramps, off-ramps, lane changing, and determining the effect of roadside advertising structures. Finally, we have discussed the limitations in the existing literature, challenges, and the future scope in driver gaze estimation and gaze-based applications.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 20 of its 216 references that are in the map. First posted on arXiv 4 Jul 2023.

Builds on

20 of 216 references.

References · 20

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8 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 5; 2026: 5.

12 papers.

  1. 2025UniGaze: Towards Universal Gaze Estimation via Large-scale Pre-Trainingcited by 8
  2. 2025myEye2Wheeler: A Two-Wheeler Indian Driver Real-World Eye-Tracking Datasetcited by 2
  3. 2025Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detectioncited by 2
  4. 2025FSDAM: Few-Shot Driving Attention Modeling via Vision-Language Couplingcited by 2
  5. 2024A Survey on Deep Learning-based Gaze Direction Regression: Searching for the State-of-the-artcited by 1
  6. 2026Investigating Bias and Fairness in Appearance-based Gaze Estimationcited by 1
  7. 2026SGAP-Gaze: Scene Grid Attention Based Point-of-Gaze Estimation Network for Driver Gazecited by 1
  8. 2024Multi-task Gaze Estimation Via Unidirectional Convolutioncited by 0
  9. 2025DMAGaze: Gaze Estimation Based on Feature Disentanglement and Multi-Scale Attentioncited by 0
  10. 2026Gaze4HRI: Zero-shot Benchmarking Gaze Estimation Neural-Networks for Human-Robot Interactioncited by 0
  11. 2026TransGaze-Object: Transformer Based Driver Gaze Object Prediction Framework in Real Drivingcited by 0
  12. 2026EyeTAG: Eye Trajectory-Aware Gaze Estimationcited by 0