Jul 28, 2021 · Motivated by the success of recent point-voxel representation, such as PVCNN, we propose a new convolutional neural network, called Multi Point- ...
In this paper, we propose Multi Point-Voxel Convolution (MPVConv) which takes the advantages of both the voxel- and point-based methods, and can work with ...
Motivated by the success of recent point-voxel representation, such as PVCNN, we propose a new convolutional neural network, called Multi Point-Voxel ...
May 1, 2023 · Motivated by the success of recent point-voxel representation, such as PVCNN and DRINet, we propose a new convolutional neural network, called ...
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Our architecture, named PE-Net, learns the representation of point clouds in high-dimensional space, and encodes the unordered input points to feature vectors, ...
We present a new convolutional neural network, called Multi Voxel-Point Neurons Convolution (MVPConv), for fast and accurate 3D deep learning.
This work presents a new convolutional neural network, called Multi Voxel-Point ... Multi Point-Voxel Convolution (MPVConv) for Deep Learning on Point Clouds.
Mar 31, 2023 · The existing 3D deep learning methods adopt either individual point-based features or local-neighboring voxel-based features, ...
Apr 30, 2021 · We present a new convolutional neural network, called Multi Voxel-Point Neurons Convolution (MVPConv), for fast and accurate 3D deep ...