most citedGaitFormer: Learning Gait Representations with Noisy Multi-Task Learning

20 citations · 21 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV202320 cited

GaitFormer: Learning Gait Representations with Noisy Multi-Task Learning

Adrian Cosma, Emilian Radoi

Gait analysis is proven to be a reliable way to perform person identification without relying on subject cooperation. Walking is a biometric that does not significantly change in s…

cs.CV2023

Learning to Simplify Spatial-Temporal Graphs in Gait Analysis

Adrian Cosma, Emilian Radoi

Gait analysis leverages unique walking patterns for person identification and assessment across multiple domains. Among the methods used for gait analysis, skeleton-based approache…

cs.CV2023

PsyMo: A Dataset for Estimating Self-Reported Psychological Traits from Gait

Adrian Cosma, Emilian Radoi

Psychological trait estimation from external factors such as movement and appearance is a challenging and long-standing problem in psychology, and is principally based on the psych…

cs.CV2023

GaitMorph: Transforming Gait by Optimally Transporting Discrete Codes

Adrian Cosma, Emilian Radoi

Gait, the manner of walking, has been proven to be a reliable biometric with uses in surveillance, marketing and security. A promising new direction for the field is training gait…

cs.CL20231 cited

It's Just a Matter of Time: Detecting Depression with Time-Enriched Multimodal Transformers

Ana-Maria Bucur, Adrian Cosma, Paolo Rosso +1

Depression detection from user-generated content on the internet has been a long-lasting topic of interest in the research community, providing valuable screening tools for psychol…

cs.CL2022

An End-to-End Set Transformer for User-Level Classification of Depression and Gambling Disorder

Ana-Maria Bucur, Adrian Cosma, Liviu P. Dinu +1

This work proposes a transformer architecture for user-level classification of gambling addiction and depression that is trainable end-to-end. As opposed to other methods that oper…