Each layer has two parallel branches, namely the voxel branch and the point branch. For the voxel branch specifically, we aggregate local features on non-empty voxel centers to reduce geometric information loss
We visualized a sparse tensor network operation on a sparse tensor, convolution, below. The convolution layer on a sparse tensor works similarly to that on a dense tensor. However, on a sparse tensor, we compute convolution outputs on a few specified points which we can control in thegeneraliz...
We visualized a sparse tensor network operation on a sparse tensor, convolution, below. The convolution layer on a sparse tensor works similarly to that on a dense tensor. However, on a sparse tensor, we compute convolution outputs on a few specified points which we can control in thegeneraliz...
467 DNMP Generation Primitive Latent Code Shape Decoder (shared) DNMP , # " $ , , # = # # #,) % Feature Rasterization & Interpolation Rendered Image Voxelization ! ! "#$ "#$ Radiance View- Features dependent Embed. F! !, ! !"#, !"# Point-Cloud Re...
Due to the sparsity of point clouds, the voxelization is inefficient and fine-details are missed to avoid high computation cost. Besides, the accuracy is limited because all points within the same voxel are assigned with the same semantic label. To make use of 2D frameworks, snapshots of 2D ...
We visualized a sparse tensor network operation on a sparse tensor, convolution, below. The convolution layer on a sparse tensor works similarly to that on a dense tensor. However, on a sparse tensor, we compute convolution outputs on a few specified points which we can control in thegeneraliz...
Due to the sparsity of point clouds, the voxelization is inefficient and fine-details are missed to avoid high computation cost. Besides, the accuracy is limited because all points within the same voxel are assigned with the same semantic label. To make use of 2D frameworks, snapshots of 2D ...
4、Every View Counts: Cross-View Consistency in 3DObject Detectionwith Hybrid-Cylindrical-Spherical Voxelization Qi Chen (Johns Hopkins University) · Lin Sun (Samsung, Stanford, HKUST) · Ernest Cheung (Samsung) · Alan Yuille (Johns Hopkins University) ...
We visualized a sparse tensor network operation on a sparse tensor, convolution, below. The convolution layer on a sparse tensor works similarly to that on a dense tensor. However, on a sparse tensor, we compute convolution outputs on a few specified points which we can control in thegeneraliz...
These methods, each uniquely addressing the complexities of point cloud data, span from direct processing techniques to advanced approaches like voxelization and multiview projections. This diversity highlights the dynamic and multifaceted nature of research in point cloud analysis. Table 1 presents a ...