# RITnet: Real-time Semantic Segmentation of the Eye for Gaze Tracking

arXiv: https://arxiv.org/abs/1910.00694 · HTML: https://mlsanity.com/paper/1910.00694/

## Key facts

- Cited by 33 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Oct 2019.

## Built on by (most cited first, 30 of 33)

- [Automatic Gaze Analysis: A Survey of Deep Learning based Approaches](https://mlsanity.com/paper/2108.05479/) (2021)
- [Semantic Segmentation with Active Semi-Supervised Learning](https://mlsanity.com/paper/2203.10730/) (2022)
- [XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse](https://mlsanity.com/paper/2211.08675/) (2022)
- [Eye-tracked Virtual Reality: A Comprehensive Survey on Methods and Privacy Challenges](https://mlsanity.com/paper/2305.14080/) (2023)
- [1000 Pupil Segmentations in a Second using Haar Like Features and Statistical Learning](https://mlsanity.com/paper/2102.01921/) (2021)
- [EllSeg-Gen, towards Domain Generalization for head-mounted eyetracking](https://mlsanity.com/paper/2205.01947/) (2022)
- [Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking Systems](https://mlsanity.com/paper/2403.15947/) (2024)
- [HAZE-Net: High-Frequency Attentive Super-Resolved Gaze Estimation in Low-Resolution Face Images](https://mlsanity.com/paper/2209.10167/) (2022)
- [Semi-Supervised Learning for Eye Image Segmentation](https://mlsanity.com/paper/2103.09369/) (2021)
- [Two-headed eye-segmentation approach for biometric identification](https://mlsanity.com/paper/2209.15471/) (2022)
- [BOXR: Body and head motion Optimization framework for eXtended Reality](https://mlsanity.com/paper/2410.13084/) (2024)
- [FlatTrack: Eye-tracking with ultra-thin lensless cameras](https://mlsanity.com/paper/2501.15450/) (2025)
- [CondSeg: Ellipse Estimation of Pupil and Iris via Conditioned Segmentation](https://mlsanity.com/paper/2408.17231/) (2024)
- [EyeTrAES: Fine-grained, Low-Latency Eye Tracking via Adaptive Event Slicing](https://mlsanity.com/paper/2409.18813/) (2024)
- [Towards Unsupervised Eye-Region Segmentation for Eye Tracking](https://mlsanity.com/paper/2410.06131/) (2024)
- [Multistream Gaze Estimation with Anatomical Eye Region Isolation by Synthetic to Real Transfer Learning](https://mlsanity.com/paper/2206.09256/) (2022)
- [Robust Sclera Segmentation for Skin-tone Agnostic Face Image Quality Assessment](https://mlsanity.com/paper/2312.15102/) (2023)
- [Using Deep Learning to Increase Eye-Tracking Robustness, Accuracy, and Precision in Virtual Reality](https://mlsanity.com/paper/2403.19768/) (2024)
- [VRBiom: A New Periocular Dataset for Biometric Applications of HMD](https://mlsanity.com/paper/2407.02150/) (2024)
- [Energy-Efficient & Real-Time Computer Vision with Intelligent Skipping via Reconfigurable CMOS Image Sensors](https://mlsanity.com/paper/2409.17341/) (2024)
- [FovealNet: Advancing AI-Driven Gaze Tracking Solutions for Optimized Foveated Rendering System Performance in Virtual Reality](https://mlsanity.com/paper/2412.10456/) (2024)
- [Iris Style Transfer: Enhancing Iris Recognition with Style Features and Privacy Preservation through Neural Style Transfer](https://mlsanity.com/paper/2503.04707/) (2025)
- [Trade-offs in Privacy-Preserving Eye Tracking through Iris Obfuscation: A Benchmarking Study](https://mlsanity.com/paper/2504.10267/) (2025)
- [Dataset for eye-tracking tasks](https://mlsanity.com/paper/2106.07554/) (2021)
- [Cycle-GAN for eye-tracking](https://mlsanity.com/paper/2205.10556/) (2022)
- [DeepMetricEye: Metric Depth Estimation in Periocular VR Imagery](https://mlsanity.com/paper/2311.07235/) (2023)
- [Topology and Intersection-Union Constrained Loss Function for Multi-Region Anatomical Segmentation in Ocular Images](https://mlsanity.com/paper/2411.00560/) (2024)
- [Stable Tracking of Eye Gaze Direction During Ophthalmic Surgery](https://mlsanity.com/paper/2507.00635/) (2025)
- [A3FR: Agile 3D Gaussian Splatting with Incremental Gaze Tracked Foveated Rendering in Virtual Reality](https://mlsanity.com/paper/2507.04147/) (2025)
- [EyeSeg: An Uncertainty-Aware Eye Segmentation Framework for AR/VR](https://mlsanity.com/paper/2507.09649/) (2025)

## Abstract (arXiv)

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. Here, we present the RITnet model, which is a deep neural network that combines U-Net and DenseNet. RITnet is under 1 MB and achieves 95.3% accuracy on the 2019 OpenEDS Semantic Segmentation challenge. Using a GeForce GTX 1080 Ti, RITnet tracks at > 300Hz, enabling real-time gaze tracking applications. Pre-trained models and source code are available https://bitbucket.org/eye-ush/ritnet/.