A Survey on Large Language Models for Motion Generation from Text

Andres Obludzyner, Fabio Zaldivar, Oscar E. Ramos

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

Over these last years, Large Language Models (LLMs) have evolved as an ubiquitous tool for different applications. One of those rapidly growing applications is motion generation, traditionally performed by a specific human design. This paper provides an overview of how motion is generated from text with the use of Large Language Models, targeted at 3D human representations and robots. We describe the different methodologies and techniques of the most used architectures, and the motion generation process in order to achieve the final motion. This survey aims to provide a comprehensive resource for researchers and developers seeking to leverage the power of LLMs to bridge the gap between text understanding and motion generation.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2024 IEEE 31st International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2024
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9798350378344
DOI
EstadoPublicada - 2024
Evento31st IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2024 - Lima, Perú
Duración: 6 nov. 20248 nov. 2024

Serie de la publicación

NombreProceedings of the 2024 IEEE 31st International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2024

Conferencia

Conferencia31st IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2024
País/TerritorioPerú
CiudadLima
Período6/11/248/11/24

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