mamba-vision
NVIDIA-MambaVision 摘要 主要工作：integrating Vision Transformers (ViT) with Mamba， 目的：improves its capacity to capture long-range spatial dependencies 适用于哪些下游任务：object detection, instance segmentation,and semantic segmentation 开源链接：GitHub - NVlabs/MambaVision: [CVPR 2025] Official PyTorch Implementation of MambaVision: A Hybrid Mamba-Transformer Vision Backbone 引言 transformer训练成本高：the quadratic complexity of the attention mechanism with respect to sequence length makes Transformers computationally expensive to train and deploy 本篇的前置知识：Vit、Mamba、SSM 等 Mamba 通过 new State Space Model (SSM) 关注该关注的，通过ardware-aware considerations并行计算：new State Space Model (SSM) that achieves linear time complexity，enables efficient input-dependent processing of long sequences with ardware-aware considerations. ...
