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https://github.com/AndrewZhuZJU/Awesome-FoodAI
AI Research Resources in Food Domain
https://github.com/AndrewZhuZJU/Awesome-FoodAI
List: Awesome-FoodAI
Last synced: about 2 months ago
JSON representation
AI Research Resources in Food Domain
- Host: GitHub
- URL: https://github.com/AndrewZhuZJU/Awesome-FoodAI
- Owner: AndrewZhuZJU
- Created: 2020-02-29T12:54:44.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-07-03T10:01:38.000Z (about 4 years ago)
- Last Synced: 2024-05-23T03:00:37.735Z (4 months ago)
- Size: 19.5 KB
- Stars: 26
- Watchers: 6
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-artificial-intelligence - Awesome-FoodAI - AI Research Resources in Food Domain. (Other awesome AI lists)
- ultimate-awesome - Awesome-FoodAI - AI Research Resources in Food Domain. (Other Lists / PowerShell Lists)
README
# Awesome-FoodAI
## Datasets
- [Food-101](https://www.vision.ee.ethz.ch/datasets_extra/food-101/) (101 food categories)
- [VireoFood-172](http://vireo.cs.cityu.edu.hk/VireoFood172/) (172 food categories & 353 ingredients)
- [Recipe1M](http://pic2recipe.csail.mit.edu/) (1M English recipes & 13M food images)
- [ChineseFoodNet](https://sites.google.com/view/chinesefoodnet/) (208 food categories)
- [Cookpad](https://dl.acm.org/doi/10.1145/3077136.3080686) (Janpanese recipes & food images)
- [YouCook2](http://youcook2.eecs.umich.edu/) (Instructional video)
- [EPIC-Kitchens](https://epic-kitchens.github.io/2020-100) (Instructional video)
## Recognition
- [Multi-Scale Multi-View Deep Feature Aggregation for Food Recognition](http://vipl.ict.ac.cn/homepage/jsq/publication/2019-Min-TIP-Multi-scale.pdf) (TIP, 2020)
- [Zero-shot Ingredient Recognition by Multi-Relational Graph Convolutional Network](http://www.liangmingpan.com/files/publications/AAAI20_Paper.pdf) (AAAI, 2020)
- [FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging](https://arxiv.org/pdf/1909.11946.pdf) (KDD, 2019)
- [Mixed-dish Recognition with Contextual Relation Networks](http://staff.ustc.edu.cn/~hexn/papers/mm19-mixed-dish.pdf) (MM, 2019)
- [Wide-Slice Residual Networks for Food Recognition](https://arxiv.org/abs/1612.06543) (WACV, 2018)
- [Cross-modal Recipe Retrieval with Rich Food Attributes](http://vireo.cs.cityu.edu.hk/papers/jingjingmm2017.pdf) (MM, 2017)
- [Deep-based Ingredient Recognition for Cooking Recipe Retrieva](http://vireo.cs.cityu.edu.hk/jingjing/papers/chen2016deep.pdf) (MM, 2016)
## Retrieval
- [MCEN: Bridging Cross-Modal Gap between Cooking Recipes and Dish Images with Latent Variable Model](https://openaccess.thecvf.com/content_CVPR_2020/papers/Fu_MCEN_Bridging_Cross-Modal_Gap_between_Cooking_Recipes_and_Dish_Images_CVPR_2020_paper.pdf) (CVPR, 2020)
- [Learning Cross-Modal Embeddings with Adversarial Networks for Cooking Recipes and Food Images](http://openaccess.thecvf.com/content_CVPR_2019/papers/Wang_Learning_Cross-Modal_Embeddings_With_Adversarial_Networks_for_Cooking_Recipes_and_CVPR_2019_paper.pdf) (CVPR, 2019)[[code](https://github.com/hwang1996/ACME)]
- [R2GAN: Cross-modal Recipe Retrieval with Generative Adversarial Network](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhu_R2GAN_Cross-Modal_Recipe_Retrieval_With_Generative_Adversarial_Network_CVPR_2019_paper.pdf) (CVPR, 2019)
- [Cross-Modal Retrieval in the Cooking Context: Learning Semantic Text-Image Embeddings](https://arxiv.org/abs/1804.11146) (SIGIR, 2018) [[code](https://github.com/Cadene/recipe1m.bootstrap.pytorch)]
- [Deep Understanding of Cooking Procedure for Cross-modal Recipe Retrieval](http://vireo.cs.cityu.edu.hk/papers/2018_p1020-chen.pdf) (MM, 2018)
- [Recipe1M+: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images](http://pic2recipe.csail.mit.edu/tpami19.pdf) (TPAMI, 2019)
- [Learning Cross-modal Embeddings for Cooking Recipes and Food Images](http://pic2recipe.csail.mit.edu/im2recipe.pdf) (CVPR, 2017) [[code](https://github.com/torralba-lab/im2recipe-Pytorch)]
- [Cross-modal Recipe Retrieval with Rich Food Attributes](http://vireo.cs.cityu.edu.hk/papers/jingjingmm2017.pdf) (MM, 2017)
- [Cross-modal Recipe Retrieval: How to Cook This Dish?](http://vireo.cs.cityu.edu.hk/allpage.files/paper_jingjing_MMM17.pdf) (MMM, 2017)
## Generation
- [CookGAN: Causality based Text-to-Image Synthesis](https://openaccess.thecvf.com/content_CVPR_2020/papers/Zhu_CookGAN_Causality_Based_Text-to-Image_Synthesis_CVPR_2020_paper.pdf) (CVPR, 2020)
- [CookGAN: Meal Image Synthesis from Ingredients](http://openaccess.thecvf.com/content_WACV_2020/papers/Han_CookGAN_Meal_Image_Synthesis_from_Ingredients_WACV_2020_paper.pdf) (WACV, 2020)
- [The art of food: Meal image synthesis from ingredients](https://arxiv.org/pdf/1905.13149.pdf)(arxiv, 2019)
- [Inverse Cooking: Recipe Generation from Food Images](https://arxiv.org/abs/1812.06164) (CVPR, 2019) [[code](https://github.com/facebookresearch/inversecooking)]
- [How to make a pizza: Learning a compositional layer-based GAN model](http://openaccess.thecvf.com/content_CVPR_2019/papers/Papadopoulos_How_to_Make_a_Pizza_Learning_a_Compositional_Layer-Based_GAN_CVPR_2019_paper.pdf) (CVPR, 2019)
## Instructional Video Analysis
- [Action Modifiers: Learning from Adverbs in Instructional Videos](https://openaccess.thecvf.com/content_CVPR_2020/papers/Doughty_Action_Modifiers_Learning_From_Adverbs_in_Instructional_Videos_CVPR_2020_paper.pdf) (CVPR, 2020)
- [Multi-Modal Domain Adaptation for Fine-Grained Action Recognition](https://openaccess.thecvf.com/content_CVPR_2020/papers/Munro_Multi-Modal_Domain_Adaptation_for_Fine-Grained_Action_Recognition_CVPR_2020_paper.pdf) (CVPR, 2020)
- [DDLSTM: Dual-Domain LSTM for Cross-Dataset Action Recognition](https://openaccess.thecvf.com/content_CVPR_2019/papers/Perrett_DDLSTM_Dual-Domain_LSTM_for_Cross-Dataset_Action_Recognition_CVPR_2019_paper.pdf) (CVPR, 2019)
- [Towards Automatic Learning of Procedures from Web Instructional Videos](https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/download/17344/16367) (AAAI, 2018)
- [Scaling Egocentric Vision:The EPIC-KITCHENS Dataset](https://openaccess.thecvf.com/content_ECCV_2018/papers/Dima_Damen_Scaling_Egocentric_Vision_ECCV_2018_paper.pdf) (ECCV, 2018)
- [CVF Finding “It”: Weakly-Supervised Reference-Aware Visual Grounding in Instructional Videos](https://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Finding_It_Weakly-Supervised_CVPR_2018_paper.pdf) (CVPR, 2018)
- [Unsupervised Visual-Linguistic Reference Resolution in Instructional Videos](https://openaccess.thecvf.com/content_cvpr_2017/papers/Huang_Unsupervised_Visual-Linguistic_Reference_CVPR_2017_paper.pdf) (CVPR, 2017)
## Recommendation
## Nutrition Estimation
## Survey
- [A survey on food computing](https://arxiv.org/abs/1808.07202) (ACM Computing Surveys, 2019)
## Demo
## Contact
If you have anything related in FoodAI and want to add in this repo, feel free to contact me at [email protected].