Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dense Voxel Fusion for 3D Object Detection   Camera and LiDAR sensor modalities provide complementary appearance and
geometric information useful for detecting 3D objects for autonomous vehicle
applications. However, current fusion models underperform state-of-art
LiDAR-only methods on 3D object detection benchmarks. Our proposed solution,
Dense Voxel Fusion (DVF) is a sequential fusion method that generates
multi-scale multi-modal dense voxel feature representations, improving
expressiveness in low point density regions. To enhance multi-modal learning,
we train directly with ground truth 2D bounding box labels, avoiding noisy,
detector-specific, 2D predictions. Additionally, we use LiDAR ground truth
sampling to simulate missed 2D detections and to accelerate training
convergence. Both DVF and the multi-modal training approaches can be applied to
any voxel-based LiDAR backbone without introducing additional learnable
parameters. DVF outperforms existing sparse fusion detectors, ranking $1^{st}$
among all published fusion methods on KITTI's 3D car detection benchmark at the
time of submission and significantly improves 3D vehicle detection performance
of voxel-based methods on the Waymo Open Dataset. We also show that our
proposed multi-modal training strategy results in better generalization
compared to training using erroneous 2D predictions.

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The categories of this paper are: nucl-ex
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The categories of this paper are: nlin
26
The categories of this paper are: bayes-an
3
The categories of this paper are: physics
4
The categories of this paper are: cond-mat
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
37
The categories of this paper are: supr-con
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The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg
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The categories of this paper are: funct-an
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The categories of this paper are: q-bio
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The categories of this paper are: eess
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The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph