Mamba, a recent selective structured state space model, performs excellently on long
sequence modeling tasks. Mamba mitigates the modeling constraints of convolutional …

The diffusion model has long been plagued by scalability and quadratic complexity issues,
especially within transformer-based structures. In this study, we aim to leverage the long …

As one of the most representative DL techniques, Transformer architecture has empowered
numerous advanced models, especially the large language models (LLMs) that comprise …

Mamba is emerging as a novel approach to overcome the challenges faced by
Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) in computer vision …

Human motion generation is a cut-edge area of research in generative computer vision, with
promising applications in video creation, game development, and robotic manipulation. The …

Transformer-based architectures have been proven successful in detecting 3D objects from
point clouds. However, the quadratic complexity of the attention mechanism struggles to …