… the added LiDAR ground truth objects in the image data. … Voxel Fusion (DVF), a sequential
fusion method, that first assigns voxel centers to the 3D location of the occupied LiDAR voxel …

… 3D object detection, named voxel field fusion. … voxel field. To this end, the learnable sampler
is first designed to sample vital features from the image plane that are projected to the voxel …

… object detection. This paper develops a low-level sensor fusion network for 3D object detection,
… The fusion network is trained and evaluated on the nuScenes data set. On the test set, …

… the detection performance … object detection network, named Voxel-Pixel Fusion Network
(VoPiFNet). Within this network, we design a key novel component called the Voxel-Pixel Fusion …

… 3D object detection, named UVTR. The proposed method aims to unify multi-modality
representations in the voxel … cross-view spatial feature fusion for 3d object detection. In European …

… we aggregate voxel-level information from the points within each voxel via max pooling. …
all object classes. For our experiments, we evaluate both 3D and BEV object detection metrics …

… , we take the voxel-based framework and try … voxel-based methods generally perform object
detection on the bird-eye-view (BEV) representation, even if the input data are in 3D voxels (…

… 3d-cvf: Generating joint camera and lidar features using cross-view spatial feature fusion
for 3d object detection. arXiv preprint arXiv:2004.12636, 3, 2020. 7 [39] Manzil Zaheer, Guru …

… a point cloud and encoding the voxels using stacks of Voxel Feature Encoding (VFE) … voxel
features respectively. Details of the 2D detection network, VoxelNet, and the proposed fusion …

… not contribute to the objective of object detection and hence can be deemed … voxel-based
multi-modal 3D object detection, we propose a simple, unified, and effective multi-modal fusion …