1 citations · 1 across the 3 of their papers we have counts for
6 papers
MuRAL: A Multi-Resident Ambient Sensor Dataset Annotated with Natural Language for Activities of Daily Living
Xi Chen, Julien Cumin, Fano Ramparany +1
Recent progress in Large Language Models (LLMs) has enabled advanced reasoning and zero-shot recognition for human activity understanding with ambient sensor data. However, widely…
Towards LLM-Powered Ambient Sensor Based Multi-Person Human Activity Recognition
Xi Chen, Julien Cumin, Fano Ramparany +1
Human Activity Recognition (HAR) is one of the central problems in fields such as healthcare, elderly care, and security at home. However, traditional HAR approaches face challenge…
Generative Resident Separation and Multi-label Classification for Multi-person Activity Recognition
Xi Chen, Julien Cumin, Fano Ramparany +1
This paper presents two models to address the problem of multi-person activity recognition using ambient sensors in a home. The first model, Seq2Res, uses a sequence generation app…
Accommodating Missing Modalities in Time-Continuous Multimodal Emotion Recognition
Juan Vazquez-Rodriguez, Grégoire Lefebvre, Julien Cumin +1
Decades of research indicate that emotion recognition is more effective when drawing information from multiple modalities. But what if some modalities are sometimes missing? To add…
Emotion Recognition with Pre-Trained Transformers Using Multimodal Signals
Juan Vazquez-Rodriguez, Grégoire Lefebvre, Julien Cumin +1
In this paper, we address the problem of multimodal emotion recognition from multiple physiological signals. We demonstrate that a Transformer-based approach is suitable for this t…
Transformer-Based Self-Supervised Learning for Emotion Recognition
Juan Vazquez-Rodriguez, Grégoire Lefebvre, Julien Cumin +1
In order to exploit representations of time-series signals, such as physiological signals, it is essential that these representations capture relevant information from the whole si…