Author

G. Amprimo

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Preprint Aug 2026

TransHands: Repurposing Human Pose Encoders as Hand Pose Encoders

This work introduces TransHands, a backbone-agnostic transfer learning framework that enables pre-trained human motion encoders to be effectively adapted for 3D hand pose estimation from 2D pose inputs, and evaluates TransHands across four state-of-the-art motion modeling architectures.

M. Piccioli, G. Amprimo, Claudia Ferraris et al. · 0 citations

Biomedical Signal Processing and Control

This study proves that GMH-D is a reliable framework for assessing 3D hand movements in clinical applications and contributes to the advancement of hand tracking technology, and the establishment of a validation procedure as a good-practice to prove efficacy of deep-learning-based hand-tracking.

G. Amprimo, Giulia Masi, G. Pettiti et al. · 0 citations