A multimodal fusion network combining CNN, Transformer, PointNet++, and LSTM claims 3.5% higher navigation accuracy than a baseline on KITTI, but the experiments lack reproducibility and the data split appears non-standard.
Personalized FedM2former: An Innovative Approach Towards Federated Multi-Modal 3D Object Detection for Autonomous Driving,
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Deep Learning-Based Multi-Modal Fusion for Robust Robot Perception and Navigation
A multimodal fusion network combining CNN, Transformer, PointNet++, and LSTM claims 3.5% higher navigation accuracy than a baseline on KITTI, but the experiments lack reproducibility and the data split appears non-standard.