A routing framework maintains three parallel 3D feature streams for LiDAR, 4D radar, and fusion, with a lightweight router using weather prompts to dynamically weight them and auxiliary supervision to keep branches distinct, achieving SOTA on K-Radar.
MVFusion: Multi- View 3D Object Detection with Semantic-aligned Radar and Camera Fusion,
2 Pith papers cite this work. Polarity classification is still indexing.
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Describes a camera-radar fusion network that uses raw RD spectra and BEV-polar camera features for BEV object detection, evaluated for accuracy and compute on the RADIal dataset.
citing papers explorer
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Weather-Conditioned Branch Routing for Robust LiDAR-Radar 3D Object Detection
A routing framework maintains three parallel 3D feature streams for LiDAR, 4D radar, and fusion, with a lightweight router using weather prompts to dynamically weight them and auxiliary supervision to keep branches distinct, achieving SOTA on K-Radar.
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A Resource Efficient Fusion Network for Object Detection in Bird's-Eye View using Camera and Raw Radar Data
Describes a camera-radar fusion network that uses raw RD spectra and BEV-polar camera features for BEV object detection, evaluated for accuracy and compute on the RADIal dataset.