Two MoE integration strategies (joint canonical MoDE vs. independent-then-route MoE-GS) improve dynamic Gaussian Splatting by composing complementary deformation priors.
Slowfast networks for video recognition
3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3representative citing papers
iPay fuses RGB and skeleton expert streams via dual-attention and a prior-driven Spatial Difference Discriminator to reach 83.45% accuracy on 500+ real-world payment clips from onboard transit cameras.
A self-attention-only aggregator over frozen visual embeddings, optionally guided by CLIP-title frame selection, improves short-video recommendation accuracy while cutting training cost.
citing papers explorer
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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting
Two MoE integration strategies (joint canonical MoDE vs. independent-then-route MoE-GS) improve dynamic Gaussian Splatting by composing complementary deformation priors.
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iPay: Integrated Payment Action Recognition via Multimodal Networks and Adaptive Spatial Prior Learning
iPay fuses RGB and skeleton expert streams via dual-attention and a prior-driven Spatial Difference Discriminator to reach 83.45% accuracy on 500+ real-world payment clips from onboard transit cameras.
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Compressed Video Aggregator: Content-driven Module for Efficient Micro-Video Recommendation
A self-attention-only aggregator over frozen visual embeddings, optionally guided by CLIP-title frame selection, improves short-video recommendation accuracy while cutting training cost.