A new class-adaptive fusion architecture improves multi-class LiDAR 3D object detection in V2X cooperative perception by routing small and large objects through attentive pathways and balancing training objectives.
When2com: Multi-agent perception via communication graph grouping,
2 Pith papers cite this work. Polarity classification is still indexing.
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NeuroMesh introduces a modular decentralized neural inference framework using dual-aggregation and parallel architecture to support heterogeneous multi-robot teams on perception, control, and task assignment tasks.
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Class-Adaptive Cooperative Perception for Multi-Class LiDAR-based 3D Object Detection in V2X Systems
A new class-adaptive fusion architecture improves multi-class LiDAR 3D object detection in V2X cooperative perception by routing small and large objects through attentive pathways and balancing training objectives.
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NeuroMesh: A Unified Neural Inference Framework for Decentralized Multi-Robot Collaboration
NeuroMesh introduces a modular decentralized neural inference framework using dual-aggregation and parallel architecture to support heterogeneous multi-robot teams on perception, control, and task assignment tasks.