The KITTI Vision Benchmark Suite

This is the latest version of RAFDet. We propose a
straightforward yet effective fusion network
termed RAFDet that combines the merits of raw
point and its range view to mitigate the sparsity
problem of point cloud, thus boosting the
detection performance. In particular, we introduce
a novel bidirectional attentive fusion module to
equip sparse points with interacted fine-grained
in-depth point features. Then, we devise the
range-view augmented fusion module to fully
exploit the supplementary relationship between
different perspectives with the aim of enhancing
original point view features. In the end, a
single-stage detection head is utilized to predict
final 3D bounding boxes based on the enhanced
semantics.

TBD

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