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Doodle to Detect: A Goofy but Powerful Approach to Skeleton-based Hand Gesture Recognition

NeurIPS 2025 · Label-efficient and robust learning › Recognition and long-tail · approach: Dense features and foundation priors · 0 citations (OpenAlex)

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AI-extracted summary. Written by AI from the paper's abstract only. Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Proposes a method for skeleton-based hand gesture recognition that improves on hand-crafted joint-distance and frame-difference features, as indicated by the title "Doodle to Detect".

Problem

Skeleton-based hand gesture recognition for intuitive human-computer interaction; hand-crafted features (joint distances, positional changes across frames) fail to capture full spatio-temporal information.

Approach

Abstract is truncated; the paper's approach is not stated in the available text. Title suggests rendering skeleton sequences as doodle-like images, but this is not confirmed by the abstract.

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