Food Segmentation

Food segmentation, the automated identification and isolation of food items within images or videos, aims to improve various applications, from nutritional analysis to agricultural monitoring and food processing optimization. Current research focuses on developing robust and efficient segmentation models, employing techniques like transformers, large multi-modal models, and attention-based mechanisms to overcome challenges such as varying lighting, complex backgrounds, and the need for minimal annotation. These advancements are crucial for enhancing the accuracy and speed of dietary assessments, improving agricultural practices, and streamlining food production processes, ultimately impacting food security and public health.