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cs.CV2025

MoME: Estimating Psychological Traits from Gait with Multi-Stage Mixture of Movement Experts

Andy Cǎtrunǎ, Adrian Cosma, Emilian Rǎdoi

Gait encodes rich biometric and behavioural information, yet leveraging the manner of walking to infer psychological traits remains a challenging and underexplored problem. We intr…

cs.CV2025

Database-Agnostic Gait Enrollment using SetTransformers

Nicoleta Basoc, Adrian Cosma, Andy Cǎtrunǎ +1

Gait recognition has emerged as a powerful tool for unobtrusive and long-range identity analysis, with growing relevance in surveillance and monitoring applications. Although recen…

cs.CV2025

On Model and Data Scaling for Skeleton-based Self-Supervised Gait Recognition

Adrian Cosma, Andy Cǎtrunǎ, Emilian Rǎdoi

Gait recognition from video streams is a challenging problem in computer vision biometrics due to the subtle differences between gaits and numerous confounding factors. Recent adva…

cs.CV2024

Aligning Actions and Walking to LLM-Generated Textual Descriptions

Radu Chivereanu, Adrian Cosma, Andy Catruna +2

Large Language Models (LLMs) have demonstrated remarkable capabilities in various domains, including data augmentation and synthetic data generation. This work explores the use of…

cs.CV2024

Gait Recognition from Highly Compressed Videos

Andrei Niculae, Andy Catruna, Adrian Cosma +2

Surveillance footage represents a valuable resource and opportunities for conducting gait analysis. However, the typical low quality and high noise levels in such footage can sever…