SF-SAM-Adapter: SAM-based segmentation model integrates prior knowledge for gaze image reflection noise removal
Gaze tracking technology in HMDs (Head-Mounted Displays) suffers from decreased accuracy due to highlight reflection noise from users' glasses. To address this, we present a denoising method which directly pinpoints the noisy regions through advanced segmentation models and then fills the flawe...
Saved in:
Main Authors: | Ting Lei, Jing Chen, Jixiang Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-01-01
|
Series: | Alexandria Engineering Journal |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016824012572 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Gaze Assistance for Efficient Segmentation Correction of Medical Images
by: Leila Khaertdinova, et al.
Published: (2025-01-01) -
MEAT-SAM: More Efficient Automated Tongue Segmentation Model
by: Fudong Zhong, et al.
Published: (2025-01-01) -
Tongue-LiteSAM: A Lightweight Model for Tongue Image Segmentation With Zero-Shot
by: Daiqing Tan, et al.
Published: (2025-01-01) -
Tuning a SAM-Based Model With Multicognitive Visual Adapter to Remote Sensing Instance Segmentation
by: Linghao Zheng, et al.
Published: (2025-01-01) -
Prompt-based three-dimensional tooth segmentation method based on pre-trained SAM(基于预训练SAM的提示式三维牙齿分割方法)
by: 刘复昌(LIU Fuchang), et al.
Published: (2025-01-01)