AICV4Food
Workshop on Deep Learning and Multimodal Approaches for Food Analysis  

The Workshop

As artificial intelligence continues to permeate our daily lives, food-related technologies are emerging as a powerful frontier in vision and multimodal learning. From intelligent kitchens and dietary guidance to food supply monitoring and sustainable consumption, the need for robust, adaptable, and ethical AI systems in the food domain is rapidly growing.

AICV4Food aims to explore this evolving intersection, focusing on how AI can interpret, reason about, and interact with food in visually complex and culturally rich environments. The workshop welcomes interdisciplinary contributions that integrate computer vision, machine learning, knowledge representation, human behavior modeling, and real-time systems.

Rather than focusing solely on food classification, AICV4Food is particularly interested in systems-level intelligence: AI that perceives, learns, and acts within food-related contexts—whether that's estimating food waste, tracking meals in dynamic environments, or enabling dietary interaction through voice, vision, and touch.

Topics of Interest

We invite original research and case studies in (but not limited to) the following areas:

1. Perception and Learning

• Visual recognition, segmentation, and tracking of food items

• Learning from minimal supervision and noisy labels

• 3D scene understanding for food environments

• Temporal modeling of food-related activities

2. Multimodal and Interactive Systems

• Cross-modal food retrieval (vision + text/speech)

• Voice- and gesture-driven interaction in smart kitchens

• Multisensor integration: cameras, weight scales, temperature, etc.

• LLMs and structured knowledge for recipe reasoning

3. Sustainability and Real-World Deployment

• AI for reducing food waste and optimizing consumption

• Nutrition-aware and health-sensitive food AI

• Food recognition for assistive or inclusive technologies

• On-device and privacy-preserving AI applications

4. Ethics, Diversity, and Social Impact

• Addressing cultural and dietary diversity in training data

• Fairness and bias mitigation in food AI systems

• Trust, transparency, and user-centric design

Important Dates

Submission deadline: June 16, 2025

Notification of acceptance: July 3, 2025

Camera-ready papers: July 10, 2025