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Eye tracking research

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Greatest papers with code

Attention Mesh: High-fidelity Face Mesh Prediction in Real-time

19 Jun 2020google/mediapipe

We present Attention Mesh, a lightweight architecture for 3D face mesh prediction that uses attention to semantically meaningful regions.

EYE TRACKING

Pupil: An Open Source Platform for Pervasive Eye Tracking and Mobile Gaze-based Interaction

30 Apr 2014pupil-labs/pupil

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.

EYE TRACKING GAZE ESTIMATION

Eye Tracking for Everyone

CVPR 2016 CSAILVision/GazeCapture

We believe that we can put the power of eye tracking in everyone's palm by building eye tracking software that works on commodity hardware such as mobile phones and tablets, without the need for additional sensors or devices.

EYE TRACKING GAZE ESTIMATION

Predicting the Driver's Focus of Attention: the DR(eye)VE Project

10 May 2017ndrplz/dreyeve

In this work we aim to predict the driver's focus of attention.

EYE TRACKING

Realtime and Accurate 3D Eye Gaze Capture with DCNN-based Iris and Pupil Segmentation

IEEE Transactions on Visualization and Computer Graphics ( Early Access ) 2019 1996scarlet/Laser-Eye

A comparison against Wang et al.[3] shows that our method advances the state of the art in 3D eye tracking using a single RGB camera.

EYE TRACKING

ETH-XGaze: A Large Scale Dataset for Gaze Estimation under Extreme Head Pose and Gaze Variation

ECCV 2020 xucong-zhang/ETH-XGaze

We show that our dataset can significantly improve the robustness of gaze estimation methods across different head poses and gaze angles.

EYE TRACKING GAZE ESTIMATION

Attention Based Glaucoma Detection: A Large-scale Database and CNN Model

CVPR 2019 smilell/AG-CNN

The attention maps of the ophthalmologists are also collected in LAG database through a simulated eye-tracking experiment.

EYE TRACKING

Sequence Classification with Human Attention

CONLL 2018 coastalcph/Sequence_classification_with_human_attention

Learning attention functions requires large volumes of data, but many NLP tasks simulate human behavior, and in this paper, we show that human attention really does provide a good inductive bias on many attention functions in NLP.

ABUSIVE LANGUAGE CLASSIFICATION EYE TRACKING GRAMMATICAL ERROR DETECTION SENTIMENT ANALYSIS

APPD: Adaptive and Precise Pupil Boundary Detection using Entropy of Contour Gradients

19 Sep 2017LeszekSwirski/pupiltracker

Eye tracking spreads through a vast area of applications from ophthalmology, assistive technologies to gaming and virtual reality.

BOUNDARY DETECTION EYE TRACKING