# Recurrent CNN for 3D Gaze Estimation using Appearance and Shape Cues

arXiv: https://arxiv.org/abs/1805.03064 · HTML: https://mlsanity.com/paper/1805.03064/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 May 2018.

## Built on by (most cited first, 21 of 21)

- [Appearance-based Gaze Estimation With Deep Learning: A Review and Benchmark](https://mlsanity.com/paper/2104.12668/) (2021)
- [Gaze Estimation using Transformer](https://mlsanity.com/paper/2105.14424/) (2021)
- [Automatic Gaze Analysis: A Survey of Deep Learning based Approaches](https://mlsanity.com/paper/2108.05479/) (2021)
- [Retina : Low-Power Eye Tracking with Event Camera and Spiking Hardware](https://mlsanity.com/paper/2312.00425/) (2023)
- [An End-to-End Review of Gaze Estimation and its Interactive Applications on Handheld Mobile Devices](https://mlsanity.com/paper/2307.00122/) (2023)
- [Spatio-Temporal Attention and Gaussian Processes for Personalized Video Gaze Estimation](https://mlsanity.com/paper/2404.05215/) (2024)
- [Enhancing 3D Gaze Estimation in the Wild using Weak Supervision with Gaze Following Labels](https://mlsanity.com/paper/2502.20249/) (2025)
- [MambaPupil: Bidirectional Selective Recurrent model for Event-based Eye tracking](https://mlsanity.com/paper/2404.12083/) (2024)
- [Towards Self-Supervised Gaze Estimation](https://mlsanity.com/paper/2203.10974/) (2022)
- [Quantifying the Impact of Motion on 2D Gaze Estimation in Real-World Mobile Interactions](https://mlsanity.com/paper/2502.10570/) (2025)
- [OmniGaze: Reward-inspired Generalizable Gaze Estimation In The Wild](https://mlsanity.com/paper/2510.13660/) (2025)
- [A Novel Framework for Multi-Person Temporal Gaze Following and Social Gaze Prediction](https://mlsanity.com/paper/2403.10511/) (2024)
- [SLYKLatent: A Learning Framework for Gaze Estimation Using Deep Facial Feature Learning](https://mlsanity.com/paper/2402.01555/) (2024)
- [Smartphone-based Eye Tracking System using Edge Intelligence and Model Optimisation](https://mlsanity.com/paper/2408.12463/) (2024)
- [A Survey on Deep Learning-based Gaze Direction Regression: Searching for the State-of-the-art](https://mlsanity.com/paper/2410.17082/) (2024)
- [Gaze Estimation for Human-Robot Interaction: Analysis Using the NICO Platform](https://mlsanity.com/paper/2509.24001/) (2025)
- [TinyGaze: Lightweight Gaze-Gesture Recognition on Commodity Mobile Devices](https://mlsanity.com/paper/2604.09658/) (2026)
- [DHECA-SuperGaze: Dual Head-Eye Cross-Attention and Super-Resolution for Unconstrained Gaze Estimation](https://mlsanity.com/paper/2505.08426/) (2025)
- [MAGE: A Multi-task Architecture for Gaze Estimation with an Efficient Calibration Module](https://mlsanity.com/paper/2505.16384/) (2025)
- [GazeD: Context-Aware Diffusion for Accurate 3D Gaze Estimation](https://mlsanity.com/paper/2601.12948/) (2026)
- [Real-time Appearance-based Gaze Estimation for Open Domains](https://mlsanity.com/paper/2603.26945/) (2026)

## Abstract (arXiv)

Gaze behavior is an important non-verbal cue in social signal processing and human-computer interaction. In this paper, we tackle the problem of person- and head pose-independent 3D gaze estimation from remote cameras, using a multi-modal recurrent convolutional neural network (CNN). We propose to combine face, eyes region, and face landmarks as individual streams in a CNN to estimate gaze in still images. Then, we exploit the dynamic nature of gaze by feeding the learned features of all the frames in a sequence to a many-to-one recurrent module that predicts the 3D gaze vector of the last frame. Our multi-modal static solution is evaluated on a wide range of head poses and gaze directions, achieving a significant improvement of 14.6% over the state of the art on EYEDIAP dataset, further improved by 4% when the temporal modality is included.