PointVST: Self-supervised pre-training for 3d point clouds via view-specific point-to-image translation
The past few years have witnessed the great success and prevalence of self-supervised
representation learning within the language and 2D vision communities. However, such …
representation learning within the language and 2D vision communities. However, such …
MPR-GAN: A novel neural rendering framework for MLS point cloud with deep generative learning
Efficient point cloud visualization is indispensable for practical applications. In the context of
point cloud visualization, 3-D rendering can be viewed as the kernel that transforms 3-D …
point cloud visualization, 3-D rendering can be viewed as the kernel that transforms 3-D …
Robust 3D point clouds classification based on declarative defenders
Abstract 3D point cloud classification requires distinct models from 2D image classification
due to the divergent characteristics of the respective input data. While 3D point clouds are …
due to the divergent characteristics of the respective input data. While 3D point clouds are …
Video reconstruction from a single motion blurred image using learned dynamic phase coding
Video reconstruction from a single motion-blurred image is a challenging problem, which
can enhance the capabilities of existing cameras. Recently, several works addressed this …
can enhance the capabilities of existing cameras. Recently, several works addressed this …
Hashed, binned A-buffer for real-time outlier removal and rendering of noisy point clouds
Typical point-based rendering algorithms cannot directly handle large outliers or high
amounts of noise without either a costly pre-processing of the point cloud or using multiple …
amounts of noise without either a costly pre-processing of the point cloud or using multiple …