Food Recognition
11 papers with code • 0 benchmarks • 8 datasets
Benchmarks
These leaderboards are used to track progress in Food Recognition
Datasets
Recipe1M+
FoodX-251
ISIA Food-500
ChineseFoodNet
KenyanFood13
CNFOOD-241-Chen
Indian Food Image Dataset
Latest papers with no code
Learning to Classify New Foods Incrementally Via Compressed Exemplars
Therefore, food image classification systems should adapt to and manage data that continuously evolves.
GCAM: Gaussian and causal-attention model of food fine-grained recognition
Currently, most food recognition relies on deep learning for category classification.
From Canteen Food to Daily Meals: Generalizing Food Recognition to More Practical Scenarios
These two datasets are used to evaluate the transferability of approaches from the well-curated food image domain to the everyday-life food image domain.
FoodLMM: A Versatile Food Assistant using Large Multi-modal Model
In the second stage, we construct a multi-round conversation dataset and a reasoning segmentation dataset to fine-tune the model, enabling it to conduct professional dialogues and generate segmentation masks based on complex reasoning in the food domain.
Dining on Details: LLM-Guided Expert Networks for Fine-Grained Food Recognition
Trained through an end-to-end multi-task learning process, this method enhances performance in the fine-grained food recognition task, showing exceptional prowess with highly similar classes.
Long-Tailed Continual Learning For Visual Food Recognition
First, as new foods appear sequentially overtime, a trained model needs to learn the new classes continuously without causing catastrophic forgetting for already learned knowledge of existing food types.
Food Recognition and Nutritional Apps
Food recognition and nutritional apps are trending technologies that may revolutionise the way people with diabetes manage their diet.
Learn More for Food Recognition via Progressive Self-Distillation
The training of PSD simultaneously contains multiple self-distillations, in which a teacher network and a student network share the same embedding network.
From Plate to Prevention: A Dietary Nutrient-aided Platform for Health Promotion in Singapore
In this paper, we share our experience in addressing this issue and attaining medical-grade nutrient intake information to benefit Singaporeans in different aspects.
A Mobile Food Recognition System for Dietary Assessment
With the model achieving 94% accuracy on 23 food classes, the developed mobile application has potential to serve the visually impaired in automatic food recognition via images.
