FoodMask: Real-time food instance counting, segmentation and recognition
Food computing has long been studied and deployed to several applications. Understanding a food image at the instance level, including recognition, counting and segmentation, is essential to quantifying nutrition and calorie consumption. Nevertheless, existing techniques are limited to either catego...
Saved in:
Main Authors: | NGUYEN, Huu-Thanh, CAO, Yu, NGO, Chong-wah, CHAN, Wing-Kwong |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2024
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/8321 https://ink.library.smu.edu.sg/context/sis_research/article/9324/viewcontent/FoodMask_av.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
SibNet: Food instance counting and segmentation
by: NGUYEN, Huu-Thanh., et al.
Published: (2022) -
DietLens-eout: Large scale restaurant food photo recognition
by: WEI, Zhipeng, et al.
Published: (2019) -
DietLens-Eout: Large Scale Restaurant Food Photo Recognition
by: Zhipeng Wei, et al.
Published: (2020) -
From canteen food to daily meals: generalizing food recognition to more practical scenarios
by: LIU, Guoshan, et al.
Published: (2024) -
Food photo recognition for dietary tracking: System and experiment
by: MING, Zhao-Yan, et al.
Published: (2018)