  The increasing interest in computer vision applications for nutrition and
dietary monitoring has led to the development of advanced 3D reconstruction
techniques for food items. However, the scarcity of high-quality data and
limited collaboration between industry and academia have constrained progress
in this field. Building on recent advancements in 3D reconstruction, we host
the MetaFood Workshop and its challenge for Physically Informed 3D Food
Reconstruction. This challenge focuses on reconstructing volume-accurate 3D
models of food items from 2D images, using a visible checkerboard as a size
reference. Participants were tasked with reconstructing 3D models for 20
selected food items of varying difficulty levels: easy, medium, and hard. The
easy level provides 200 images, the medium level provides 30 images, and the
hard level provides only 1 image for reconstruction. In total, 16 teams
submitted results in the final testing phase. The solutions developed in this
challenge achieved promising results in 3D food reconstruction, with
significant potential for improving portion estimation for dietary assessment
and nutritional monitoring. More details about this workshop challenge and
access to the dataset can be found at
https://sites.google.com/view/cvpr-metafood-2024.
