The 6th International Workshop on Gaze Estimation and Prediction in the Wild (GAZE 2024) at CVPR 2024 aims to encourage and highlight novel strategies for eye gaze estimation and prediction. The workshop topics include (but are not limited to):
- Enhancing eye image segmentation, landmark localization, gaze estimation and other tasks in mixed and augmented reality (XR / AR) settings.
- Novel multi-modal systems for incorporating gaze information to improve visual recognition tasks.
- Improving eye detection, gaze estimation, and gaze prediction pipelines in various ways, such as by applying geometric and anatomical constraints, leveraging additional cues such as head pose, scene content, or considering multi-modal inputs.
- Developing adversarial or domain generalization methods to improve cross-dataset performance or to deal with conditions where current methods fail (illumination, appearance, etc.).
- Exploring attention mechanisms and temporal information to predict the point of regard.
- Novel methods for temporal gaze estimation and prediction including Bayesian methods.
- Personalization of gaze estimators with methods such as few-shot learning.
- Semi-/weak-/un-/self- supervised learning methods, domain adaptation methods, and other novel methods towards improved representation learning from eye/face region images or gaze target region images.
Call for Contributions
Full Workshop Papers
Submission: We invite authors to submit unpublished papers (8-page CVPR format) to our workshop, to be presented at a poster session upon acceptance. All submissions will go through a double-blind review process. All contributions must be submitted (along with supplementary materials, if any) at this CMT link.
Accepted papers will be published in the official CVPR Workshops proceedings and the Computer Vision Foundation (CVF) Open Access archive.
Note: Authors of previously rejected main conference submissions are also welcome to submit their work to our workshop. When doing so, you must submit the previous reviewers' comments (named as previous_reviews.pdf
) and a letter of changes (named as letter_of_changes.pdf
) as part of your supplementary materials to clearly demonstrate the changes made to address the comments made by previous reviewers.
Invited Keynote Speakers
Tsinghua University
Feng Xu is currently an associate professor at the School of Software, Tsinghua University, Beijing, China. He earned a Ph.D. in automation and a B.S. in physics from Tsinghua University in 2012 and 2007, respectively. Until 2015, He was a Researcher in the Internet Graphics group, Microsoft Research Asia. His research interests include human body reconstruction, face animation, and medical image analysis. He has authored more than 40 conference and journal papers in the corresponding areas, including Nature Medicine, SIGGRAPH, CVPR, ICCV, ECCV, PAMI, and so on.
Accepted Full Papers
University of Birmingham
Delft University of Technology
NVIDIA Research
Lunit Inc.
EPFL & Idiap Research Institute
University of Birmingham
ETH Zürich
ETH Zürich
University of Birmingham
University of Birmingham
Email: hxw080@student.bham.ac.uk