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Found 4 papers, 1 papers with code
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.
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.
ISIA Food-500: A Dataset for Large-Scale Food Recognition via Stacked Global-Local Attention Network
To encourage further progress in food recognition, we introduce the dataset ISIA Food- 500 with 500 categories from the list in the Wikipedia and 399, 726 images, a more comprehensive food dataset that surpasses existing popular benchmark datasets by category coverage and data volume.
A Survey on Food Computing
This is the first comprehensive survey that targets the study of computing technology for the food area and also offers a collection of research studies and technologies to benefit researchers and practitioners working in different food-related fields.
Computers and Society Multimedia
