Human pose forecasting is a complex structured-data sequence-modelling task, which has
received increasing attention, also due to numerous potential applications. Research has …

Pushing back the frontiers of collaborative robots in industrial environments, we propose a
new Separable-Sparse Graph Convolutional Network (SeS-GCN) for pose forecasting. For …

Landslide, a kind of destructive natural disaster, often occurs in the mountainous areas of
China. Landslide information instant collection plays an important role in taking appropriate …

Graph neural networks have achieved impressive progress in solving large and complex
graph-structured problems. However, existing methods cannot sufficiently explore the …

Modeling spatial relationship in the data remains critical across many different tasks, such as
image classification, semantic segmentation and protein structure understanding. Previous …

Modeling the 3D structures of proteins is critical for obtaining effective protein structure
representations, which further boosts protein function understanding. Existing protein …

Artificial Intelligence (AI) requires machines capable of learning and generalizing from data
without being explicitly programmed to do so, giving rise to the field of Machine Learning …

The rapid pace of the development of artificial intelligence (AI) solutions is enabled by
leveraging foundational tools and frameworks that allow AI developers to focus on …

Computer Vision emerges as a cornerstone field within Artificial intelligence, enabling digital
systems to sense the world through images, mirroring the human ability to see and interpret …