Gaze Estimation
73 papers with code • 9 benchmarks • 16 datasets
Gaze Estimation is a task to predict where a person is looking at given the person’s full face. The task contains two directions: 3-D gaze vector and 2-D gaze position estimation. 3-D gaze vector estimation is to predict the gaze vector, which is usually used in the automotive safety. 2-D gaze position estimation is to predict the horizontal and vertical coordinates on a 2-D screen, which allows utilizing gaze point to control a cursor for human-machine interaction.
Source: A Generalized and Robust Method Towards Practical Gaze Estimation on Smart Phone
Benchmarks
These leaderboards are used to track progress in Gaze Estimation
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AVA
MPIIGaze
Gaze360
GazeCapture
EYEDIAP
ETH-XGaze
OpenEDS
Latest papers
Spatio-Temporal Attention and Gaussian Processes for Personalized Video Gaze Estimation
Additionally, our approach integrates Gaussian processes to include individual-specific traits, facilitating the personalization of our model with just a few labeled samples.
Denoising Distillation Makes Event-Frame Transformers as Accurate Gaze Trackers
Technically, we propose a two-stage learning-based gaze estimation framework to divide the whole gaze estimation process into a coarse-to-fine process of anchor state selection and final gaze location.
Test-Time Personalization with Meta Prompt for Gaze Estimation
Despite the recent remarkable achievement in gaze estimation, efficient and accurate personalization of gaze estimation without labels is a practical problem but rarely touched on in the literature.
UVAGaze: Unsupervised 1-to-2 Views Adaptation for Gaze Estimation
To address these challenges, we propose a novel 1-view-to-2-views (1-to-2 views) adaptation solution in this paper, the Unsupervised 1-to-2 Views Adaptation framework for Gaze estimation (UVAGaze).
Appearance-based gaze estimation enhanced with synthetic images using deep neural networks
Human eye gaze estimation is an important cognitive ingredient for successful human-robot interaction, enabling the robot to read and predict human behavior.
End-to-end Video Gaze Estimation via Capturing Head-face-eye Spatial-temporal Interaction Context
zgchen33/mcgaze
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In this letter, we propose a new method, Multi-Clue Gaze (MCGaze), to facilitate video gaze estimation via capturing spatial-temporal interaction context among head, face, and eye in an end-to-end learning way, which has not been well concerned yet.
LEyes: A Lightweight Framework for Deep Learning-Based Eye Tracking using Synthetic Eye Images
This problem is exacerbated by both hardware-induced variations in eye images and inherent biological differences across the recorded participants, leading to both feature and pixel-level variance that hinders the generalizability of models trained on specific datasets.
Gaze Estimation on Spresense
Gaze estimation is a valuable technology with numerous applications in fields such as human-computer interaction, virtual reality, and medicine.
DVGaze: Dual-View Gaze Estimation
yihuacheng/dvgaze
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ICCV 2023
We further propose a dual-view transformer to estimate gaze from dual-view features.
Investigation of Architectures and Receptive Fields for Appearance-based Gaze Estimation
With the rapid development of deep learning technology in the past decade, appearance-based gaze estimation has attracted great attention from both computer vision and human-computer interaction research communities.
