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 with no code
GazeCLIP: Towards Enhancing Gaze Estimation via Text Guidance
Over the past decade, visual gaze estimation has garnered growing attention within the research community, thanks to its wide-ranging application scenarios.
Zero-Shot Segmentation of Eye Features Using the Segment Anything Model (SAM)
The advent of foundation models signals a new era in artificial intelligence.
GazeForensics: DeepFake Detection via Gaze-guided Spatial Inconsistency Learning
DeepFake detection is pivotal in personal privacy and public safety.
Semi-Synthetic Dataset Augmentation for Application-Specific Gaze Estimation
Although the number of gaze estimation datasets is growing, the application of appearance-based gaze estimation methods is mostly limited to estimating the point of gaze on a screen.
Unsupervised Gaze-aware Contrastive Learning with Subject-specific Condition
Appearance-based gaze estimation has shown great promise in many applications by using a single general-purpose camera as the input device.
PCFGaze: Physics-Consistent Feature for Appearance-based Gaze Estimation
Although recent deep learning based gaze estimation approaches have achieved much improvement, we still know little about how gaze features are connected to the physics of gaze.
An Interpretable and Attention-based Method for Gaze Estimation Using Electroencephalography
Eye movements can reveal valuable insights into various aspects of human mental processes, physical well-being, and actions.
Semi-supervised Contrastive Regression for Estimation of Eye Gaze
Our contrastive regression framework shows good performance in comparison to several state of the art contrastive learning techniques used for gaze estimation.
High-Fidelity Eye Animatable Neural Radiance Fields for Human Face
In this paper, we aim to learn a face NeRF model that is sensitive to eye movements from multi-view images.
A Review of Driver Gaze Estimation and Application in Gaze Behavior Understanding
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.
