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miscellaneous-8

Food recommendation

3260 papers • 126 benchmarks • 313 datasets

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Benchmarks

These leaderboards are used to track progress in food-recommendation-8

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Dataset

Best Model

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Oktoberfest Food Dataset

Libraries

Use these libraries to find food-recommendation-8 models and implementations

Datasets

Oktoberfest Food Dataset

Water Footprint Recommender System Data

Indian Food Image Dataset

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Most implemented papers

Characterizing and Predicting Repeat Food Consumption Behavior for Just-in-Time Interventions

Ee-Peng Lim, Helena H. Lee, Palakorn Achananuparp, Yue Liu, Tzu-Ling Cheng, Shou-de Lin•Mon Sep 16 2019

The experiment results show that algorithms incorporating the exploration-and-exploitation and temporal dynamics are more effective in the next-day recommendation task than most state-of-the-art algorithms.

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Introduction Benchmarks Datasets Subtasks Libraries Papers

Paper Graph

FoodLogoDet-1500: A Dataset for Large-Scale Food Logo Detection via Multi-Scale Feature Decoupling Network

Weiqing Min, Shuqiang Jiang, Jing Wang, Sujuan Hou, Yuanjie Zheng, Qiang Hou•Mon Aug 09 2021

A novel food logo detection method Multi-scale Feature Decoupling Network (MFDNet), which decouples classification and regression into two branches and focuses on the classification branch to solve the problem of distinguishing multiple food logo categories is proposed.

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Market2Dish: Health-aware Food Recommendation

Wenjie Wang, Liqiang Nie, Xuemeng Song, Ling-Yu Duan, Hao Jiang, Peiguang Jing•Thu Dec 10 2020

A personalized health-aware food recommendation scheme, namely, Market2Dish, mapping the ingredients displayed in the market to the healthy dishes eaten at home and a novel category-aware hierarchical memory network–based recommender to learn thehealth-aware user-recipe interactions for better food recommendation is presented.

85 0

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Personalized Food Recommendation as Constrained Question Answering over a Large-scale Food Knowledge Graph

Yu Chen, Mohammed J. Zaki, Ananya Subburathinam, Ching-Hua Chen•Mon Jan 04 2021

A KBQA-based personalized food recommendation framework which is equipped with novel techniques for handling negations and numerical comparisons in the queries, and is able to recommend more relevant and healthier recipes.

78 0

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Food Recommendations for Reducing Water Footprint

Ignazio Gallo, Nicola Landro, Riccardo La Grassa, A. Turconi•Wed Mar 23 2022

A personalized food recommendation scheme, mapping the ingredients to the most resource-friendly dishes on the planet and in particular, selecting recipes that contain ingredients that consume as little water as possible for their production.

17 0

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Cook-Gen: Robust Generative Modeling of Cooking Actions from Recipes

Amit P. Sheth, Kaushik Roy, Yuxin Zi, Vignesh Narayanan, R. Venkataramanan, Kanak Raj, Renjith Prasad•Wed May 31 2023

This work proposes novel aggregation-based generative AI methods, Cook-Gen, that reliably generate cooking actions from recipes, despite difficulties with irregular data patterns, while also outperforming Large Language Models and other strong baselines.

18 0

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Explainable Active Learning for Preference Elicitation

Furkan Cantürk, Reyhan Aydoğan•Thu Aug 31 2023

This study implements the proposed preference elicitation methodology for food recommendation in a specific scenario of the cold-start problem, where the recommendation system lacks adequate user presence or access to other users' data is restricted, obstructing employing user profiling methods utilizing existing data in the system.

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SeeDS: Semantic Separable Diffusion Synthesizer for Zero-shot Food Detection

Pengfei Zhou, Weiqing Min, Ying Jin, Jiajun Song, Yang Zhang, Shuqiang Jiang•Fri Oct 06 2023

The Semantic Separable Diffusion Synthesizer (SeeDS) framework for Zero-Shot Food Detection (ZSFD) is proposed, which learns the disentangled semantic representation for complex food attributes from ingredients and cuisines, and synthesizes discriminative food features via enhanced semantic information.

15 0

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Food recommendation | State-of-the-Art