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MamBOA architecture enhances video recognition with state-space models

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced MamBOA, a novel state-space architecture designed for video recognition tasks. This framework is backbone-agnostic, meaning it can integrate with existing CNN, Transformer, and Mamba architectures. MamBOA enhances temporal reasoning by treating selective state-space recurrence as a motion synthesizer, achieving high accuracy on benchmarks like Diving48 with minimal additional computational cost. AI

RANK_REASON The cluster describes a new research paper detailing a novel architecture for video recognition, submitted to arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

MamBOA architecture enhances video recognition with state-space models

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The cluster describes a new research paper detailing a novel architecture for video recognition, submitted to arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Mustafa Bora \c{C}elik ·

    MamBOA: State-Space Architecture for Video Recognition

    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…

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