RESEARCH

COMPUTER VISION

Inverse Cooking: Recipe Generation from Food Images

June 16, 2019

Abstract

People enjoy food photography because they appreciate food. Behind each meal there is a story described in a complex recipe and, unfortunately, by simply looking at a food image we do not have access to its preparation process. Therefore, in this paper we introduce an inverse cooking system that recreates cooking recipes given food images. Our system predicts ingredients as sets by means of a novel architecture, modeling their dependencies without imposing any order, and then generates cooking instructions by attending to both image and its inferred ingredients simultaneously. We extensively evaluate the whole system on the large-scale Recipe1M dataset and show that (1) we improve performance w.r.t. previous baselines for ingredient prediction; (2) we are able to obtain high quality recipes by leveraging both image and ingredients; (3) our system is able to produce more compelling recipes than retrieval-based approaches according to human judgment. We make code and models publicly available at: https://github.com/ facebookresearch/inversecooking.

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AUTHORS

Written by

Michal Drozdzal

Adriana Romero Soriano

Amaia Salvador Aguilera

Xavier Giro-i-Nieto

Publisher

CVPR

Research Topics

Computer Vision

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