Code 3DGazeNet: Generalizing Gaze Estimation with Weak-Supervision from Synthetic Views vagver/3dgazenet• •6 Dec 2022 To close the gap between image domains, we create a large-scale dataset of diverse faces with gaze pseudo-annotations, which we extract based on the 3D geometry of the sce...
gaze range, illumination conditions, and facial appearance variation. We show that image resolution and the use of both eyes affect gaze estimation performance while head pose and pupil centre information are less informative. Finally, we propose GazeNet, the first deep appearance-based gaze ...
[Cheng-etal2024 TPAMI] Appearance-based Gaze Estimation With Deep Learning: A Review and Benchmark [PDF] Yihua Cheng, Haofei Wang, Yiwei Bao, Feng Lu[Kar-Corcoran2017 IEEE] A Review and Analysis of Eye-Gaze Estimation Systems, Algorithms and Performance Evaluation Methods in Consumer Platforms...
Code Latest commit History 68 Commits Repository files navigation README Awesome Work on Gaze Estimation Table of Contents Review Papers [Kar-Corcoran2017 IEEE] A Review and Analysis of Eye-Gaze Estimation Systems, Algorithms and Performance Evaluation Methods in Consumer Platforms.[PDF] ...
CNN-based gaze estimation methods are usually trained in an end-to-end manner with substantial amount of la- beled data. The performance of CNN-based gaze estimation methods highly relies on the quantity and diversity of the training dataset. Unfortunately, annotating ...
Estimation Error (mean ± SD in degree) of MGTC (S = 1) on MPIIGaze. matched the performance of other methods for all cases in SGTC and for MGTC when the number of images was less than or equal to 32. For example, for SGTC with 16 sam- pl...
When examined from the perspective of someone with- out background or experience in computer science, however, the researcher interested in applying computer-vision-based gaze estimation is faced with two major problems. First, the developers of these methods either do not publish their code or ...
This research delves into the intricate connection between self-attention mechanisms in large-scale pre-trained language models, like BERT, and human gaze
head pose estimation, facial action unit recognition, and eye-gaze estimation with available source code for both running and training the models. The computer vision algorithms which represent the core of OpenFace demonstrate state-of-the-art results in all of the above mentioned tasks. Furthermore...
Paper tables with annotated results for Offset Calibration for Appearance-Based Gaze Estimation via Gaze Decomposition