VOXEL-LEVEL FEATURE FUSION WITH GRAPH NEURAL NETWORKS AND DIFFUSION FOR 3D OBJECT DETECTION
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United States of America
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Issued Date -
Mar 20, 2025
app pub date -
Sep 14, 2023
filing date -
Sep 14, 2023
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Abstract
An apparatus includes a memory and processing circuitry in communication with the memory. The processing circuitry is configured to process a joint graph representation using a graph neural network (GNN) to form an enhanced graph representation. The joint graph representation includes first features from a voxelized point cloud, and second features from a plurality of camera images. The enhanced graph representation includes enhanced first features and enhanced second features. The processing circuitry is further configured to perform a diffusion processes on the enhanced first features and the enhanced second features of the enhanced graph representation to form a denoised graph representation having denoised first features and denoised second features, and fuse the denoised first features and the denoised second features of the denoised graph representation using a graph attention network (GAT) to form a fused point cloud having fused features.
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