LINet achieves 45.2% mean class accuracy on SUN RGB-D 19-class scene classification from scratch using continuous linear integration across dedicated RGB, depth, and integration streams.
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Complex multimodal architectures do not reliably outperform unimodal baselines or a simple multimodal baseline under standardized evaluation.
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MSNN-LINet: Cross-Modal Learning via Continuous Linear Integration
LINet achieves 45.2% mean class accuracy on SUN RGB-D 19-class scene classification from scratch using continuous linear integration across dedicated RGB, depth, and integration streams.
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Fusion or Confusion? Multimodal Complexity Is Not All You Need
Complex multimodal architectures do not reliably outperform unimodal baselines or a simple multimodal baseline under standardized evaluation.