all AI news
GazeCLIP: Towards Enhancing Gaze Estimation via Text Guidance
April 29, 2024, 4:45 a.m. | Jun Wang, Hao Ruan, Mingjie Wang, Chuanghui Zhang, Huachun Li, Jun Zhou
cs.CV updates on arXiv.org arxiv.org
Abstract: Over the past decade, visual gaze estimation has garnered increasing attention within the research community, owing to its wide-ranging application scenarios. While existing estimation approaches have achieved remarkable success in enhancing prediction accuracy, they primarily infer gaze from single-image signals, neglecting the potential benefits of the currently dominant text guidance. Notably, visual-language collaboration has been extensively explored across various visual tasks, such as image synthesis and manipulation, leveraging the remarkable transferability of large-scale Contrastive Language-Image …
abstract accuracy application arxiv attention benefits community cs.cv guidance image prediction research research community success text type via visual while
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US
Research Engineer
@ Allora Labs | Remote
Ecosystem Manager
@ Allora Labs | Remote
Founding AI Engineer, Agents
@ Occam AI | New York