GCN-Transformer: Graph Convolutional Network and Transformer for Multi-Person Pose Forecasting Using Sensor-Based Motion Data

GCN-Transformer: Graph Convolutional Network and Transformer for Multi-Person Pose Forecasting Using Sensor-Based Motion Data

Multi-person pose forecasting involves predicting the future body poses of multiple individuals over time, involving complex movement dynamics and interaction dependencies. Its relevance spans various fields, including computer vision, robotics, human–computer interaction, and surveillance. This tas...

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Bibliographic Details
Main Authors: Romeo Šajina, Goran Oreški, Marina Ivašić-Kos
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Sensors
Subjects:
multi-person pose forecasting
transformer architecture
GCN
GCN-Transformer
SoMoF Benchmark
ExPI dataset
Online Access:https://www.mdpi.com/1424-8220/25/10/3136
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