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
Most implemented papers
Learning to Find Eye Region Landmarks for Remote Gaze Estimation in Unconstrained Settings
Conventional feature-based and model-based gaze estimation methods have proven to perform well in settings with controlled illumination and specialized cameras.
RITnet: Real-time Semantic Segmentation of the Eye for Gaze Tracking
eye-ush/ritnet
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Accurate eye segmentation can improve eye-gaze estimation and support interactive computing based on visual attention; however, existing eye segmentation methods suffer from issues such as person-dependent accuracy, lack of robustness, and an inability to be run in real-time.
Towards High Performance Low Complexity Calibration in Appearance Based Gaze Estimation
czk32611/GEDDnet
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Appearance-based gaze estimation from RGB images provides relatively unconstrained gaze tracking.
Self-Learning Transformations for Improving Gaze and Head Redirection
Furthermore, we show that in the presence of limited amounts of real-world training data, our method allows for improvements in the downstream task of semi-supervised cross-dataset gaze estimation.
TinyTracker: Ultra-Fast and Ultra-Low-Power Edge Vision In-Sensor for Gaze Estimation
pbonazzi/retina
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We propose TinyTracker, a highly efficient, fully quantized model for 2D gaze estimation designed to maximize the performance of the edge vision systems considered in this study.
Spatio-Temporal Attention and Gaussian Processes for Personalized Video Gaze Estimation
jswati31/stage
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Additionally, our approach integrates Gaussian processes to include individual-specific traits, facilitating the personalization of our model with just a few labeled samples.
Ecological Sampling of Gaze Shifts
Visual attention guides our gaze to relevant parts of the viewed scene, yet the moment-to-moment relocation of gaze can be different among observers even though the same locations are taken into account.
Pupil: An Open Source Platform for Pervasive Eye Tracking and Mobile Gaze-based Interaction
Commercial head-mounted eye trackers provide useful features to customers in industry and research but are expensive and rely on closed source hardware and software.
Deep Pictorial Gaze Estimation
xiamenwcy/pictorial_net
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ECCV 2018
In this paper, we introduce a novel deep neural network architecture specifically designed for the task of gaze estimation from single eye input.
RT-GENE: Real-Time Eye Gaze Estimation in Natural Environments
Tobias-Fischer/rt_gene
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ECCV 2018
We first record a novel dataset of varied gaze and head pose images in a natural environment, addressing the issue of ground truth annotation by measuring head pose using a motion capture system and eye gaze using mobile eyetracking glasses.
