most citedProfVLM: A lightweight video-language model for multi-view proficiency estimation

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

SkillMoV: Mixture-of-View Routing with Prototype-Conditioned Gating for Unified Multi-View Proficiency Estimation

Edoardo Bianchi, Antonio Liotta

Estimating human proficiency from video is a key challenge for automated skill assessment, with applications in sports coaching, music pedagogy, surgical training, and workplace le…

cs.CV2026

Parameter-Efficient Multi-View Proficiency Estimation: From Discriminative Classification to Generative Feedback

Edoardo Bianchi, Antonio Liotta

Estimating how well a person performs an action, rather than which action is performed, is central to coaching, rehabilitation, and talent identification. This task is challenging…

cs.CV20261 cited

ProfVLM: A lightweight video-language model for multi-view proficiency estimation

Edoardo Bianchi, Jacopo Staiano, Antonio Liotta

Most existing approaches formulate action quality assessment and skill proficiency estimation as discriminative prediction tasks, typically producing discrete labels or scores with…

cs.CV2025

PATS: Proficiency-Aware Temporal Sampling for Multi-View Sports Skill Assessment

Edoardo Bianchi, Antonio Liotta

Automated sports skill assessment requires capturing fundamental movement patterns that distinguish expert from novice performance, yet current video sampling methods disrupt the t…

cs.CV2025

SkillFormer: Unified Multi-View Video Understanding for Proficiency Estimation

Edoardo Bianchi, Antonio Liotta

Assessing human skill levels in complex activities is a challenging problem with applications in sports, rehabilitation, and training. In this work, we present SkillFormer, a param…