English(EN) MamBOA: State-Space Architecture for Video Recognition

MamBOA架构利用状态空间模型增强视频识别能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-16 04:00

研究人员推出了一种新颖的状态空间架构MamBOA，专为视频识别任务设计。该框架不依赖于特定骨干网络，意味着它可以与现有的CNN、Transformer和Mamba架构集成。MamBOA将选择性状态空间递归视为运动合成器，增强了时序推理能力，在Diving48等基准测试中以极低的额外计算成本实现了高精度。 AI

排序理由该集群描述了一篇关于用于视频识别的新型架构的最新研究论文，该论文已提交至arXiv。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Mustafa Bora \c{C}elik · 2026-06-16 04:00

MamBOA：用于视频识别的状态空间架构

arXiv:2606.15275v1 Announce Type: new Abstract: Fine-grained action recognition demands temporal reasoning that general-purpose architectures address through different cost-accuracy tradeoffs: 3D dense operators couple computation to the input volume, while difference-based metho…

本文如何被排名

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MamBOA：用于视频识别的状态空间架构

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