VolTex: Food Volume Estimation using Text-Guided Segmentation and Neural Surface Reconstruction
Journal:
arXiv
Published Date:
Jun 3, 2025
Abstract
Accurate food volume estimation is crucial for dietary monitoring, medical
nutrition management, and food intake analysis. Existing 3D Food Volume
estimation methods accurately compute the food volume but lack for food
portions selection. We present VolTex, a framework that improves \change{the
food object selection} in food volume estimation. Allowing users to specify a
target food item via text input to be segmented, our method enables the precise
selection of specific food objects in real-world scenes. The segmented object
is then reconstructed using the Neural Surface Reconstruction method to
generate high-fidelity 3D meshes for volume computation. Extensive evaluations
on the MetaFood3D dataset demonstrate the effectiveness of our approach in
isolating and reconstructing food items for accurate volume estimation. The
source code is accessible at https://github.com/GCVCG/VolTex.
