PKS^4 adds a kinematic-prior-driven parallel state space scanner module to 2D vision backbones for linear-complexity temporal modeling in videos, delivering SOTA action recognition with 10x lower training compute and convergence in 20 epochs.
arXiv preprint arXiv:2311.15769 (2023)
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The MOSS module learns and combines multi-order space-time self-similarity features to enhance temporal dynamics modeling in videos across action recognition, VQA, and robotic tasks.
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$\text{PKS}^4$:Parallel Kinematic Selective State Space Scanners for Efficient Video Understanding
PKS^4 adds a kinematic-prior-driven parallel state space scanner module to 2D vision backbones for linear-complexity temporal modeling in videos, delivering SOTA action recognition with 10x lower training compute and convergence in 20 epochs.
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Exploring High-Order Self-Similarity for Video Understanding
The MOSS module learns and combines multi-order space-time self-similarity features to enhance temporal dynamics modeling in videos across action recognition, VQA, and robotic tasks.