SToRe3D: Sparse Token Relevance in ViTs for Efficient Multi-View 3D Object Detection · DeepSignal
SToRe3D: Sparse Token Relevance in ViTs for Efficient Multi-View 3D Object Detection arXiv cs.CV · Sandro Papais, Lezhou Feng, Charles Cossette, Lingting Ge 2d ago · · · · SToRe3D enhances ViT-based 3D object detection by improving inference speed through relevance-aligned sparsity.
Key Points Introduces relevance-aligned sparsity for ViTs. Achieves up to 3x faster inference with minimal accuracy loss. Evaluated on nuScenes and new nuScenes-Relevance benchmark. Reader Mode unavailable (could not extract clean content).
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📰 Read Original Signal Score
Moderate signal — interesting but narrower impact.
Weight Score
Source authority 20% 78
Community heat 20% 0
Technical impact 30%
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≥75 high · 50–74 medium · <50 low
Why Featured
SToRe3D's relevance-aligned sparsity boosts ViT-based 3D object detection efficiency, signaling developers and PMs to optimize performance while attracting investor interest in scalable AI solutions.