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What Constitutes Food Similarity? Visual Representations and Retrieval in Indian Cuisine

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Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 30/10/2026, 06:48:24 UTC.

Briefings

A new study using an expanded Indian cuisine dataset and seven visual representations evaluates how food similarity functions beyond simple identity preservation. The research finds that image-to-image retrieval and dish-level neighborhood structures vary significantly across different model types, revealing that visual similarity depends on representation, modality, and abstraction level rather than being a fixed property of the food collection. This challenges the assumption that recognition performance alone characterizes relational structure in food information systems.

Key points

• Seven different visual representations were tested on an expanded Indian cuisine dataset to evaluate food similarity structures.
• Image-to-image retrieval and dish-level neighborhoods vary substantially across representations, including similarities across culinary-family boundaries.

Context

Food similarity underlies retrieval, recommendation, and substitution tasks. Indian cuisine offers a challenging setting where visually similar foods may have different culinary identities, while foods within a culinary family can vary substantially in appearance. Understanding these structures is a prerequisite for combining multiple food information modalities into a coherent notion of similarity.

Limitations

The study uses preprint data from arXiv without peer review. Results are based on aggregated image representations and may not reflect real-world retrieval performance. Specific model details and dataset composition are not fully disclosed, limiting reproducibility and generalizability.

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