Food Recognition
11 papers with code • 0 benchmarks • 8 datasets
Benchmarks
These leaderboards are used to track progress in Food Recognition
Datasets
Most implemented papers
ChineseFoodNet: A large-scale Image Dataset for Chinese Food Recognition
In this paper, we introduce a new and challenging large-scale food image dataset called "ChineseFoodNet", which aims to automatically recognizing pictured Chinese dishes.
NU-InNet: Thai Food Image Recognition Using Convolutional Neural Networks on Smartphone
In this paper, the image recognition for Thai food using a smartphone is studied.
Deep learning approaches in food recognition
Automatic image-based food recognition is a particularly challenging task.
Mining Discriminative Food Regions for Accurate Food Recognition
Taking inspiration from Adversarial Erasing, a strategy that progressively discovers discriminative object regions for weakly supervised semantic segmentation, we propose a novel network architecture in which a primary network maintains the base accuracy of classifying an input image, an auxiliary network adversarially mines discriminative food regions, and a region network classifies the resulting mined regions.
Learning Multi-Subset of Classes for Fine-Grained Food Recognition
We validated our proposed method using two recent state-of-the-art vision transformers on three public food recognition datasets.
Food Ingredients Recognition through Multi-label Learning
Within this framework, we focus on one of the core functionalities to visually recognize various ingredients.
Vision and Structured-Language Pretraining for Cross-Modal Food Retrieval
Finally, we validate the generalization of the approach to other tasks (i. e, Food Recognition) and domains with structured text such as the Medical domain on the ROCO dataset.
A Central Asian Food Dataset for Personalized Dietary Interventions
Nowadays, it is common for people to take photographs of every beverage, snack, or meal they eat and then post these photographs on social media platforms.
A Central Asian Food Dataset for Personalized Dietary Interventions, Extended Abstract
Nowadays, it is common for people to take photographs of every beverage, snack, or meal they eat and then post these photographs on social media platforms.
Feature-Suppressed Contrast for Self-Supervised Food Pre-training
As the similar contents of the two views are salient or highly responsive in the feature map, the proposed FeaSC uses a response-aware scheme to localize salient features in an unsupervised manner.