Papers Point Set Upsampling
“Point Set Upsampling” 태그가 달린 논문 5편 · 필터 해제
ASUR3D: Arbitrary Scale Upsampling and Refinement of 3D Point Clouds using Local Occupancy Fields
In this paper, we introduce ASUR3D, a novel methodology for the arbitrary-scale upsampling of 3D point clouds employing Local Occupancy Representation. Our proposed implicit occupancy representation enables efficient poi…
3D Reconstruction3D Shape Generation3D Shape RepresentationPoint Cloud Super Resolution+1Deep Point Cloud Reconstruction
Point cloud obtained from 3D scanning is often sparse, noisy, and irregular. To cope with these issues, recent studies have been separately conducted to densify, denoise, and complete inaccurate point cloud. In this pape…
DenoisingPoint Cloud CompletionPoint cloud reconstructionPoint Set UpsamplingCAD-PU: A Curvature-Adaptive Deep Learning Solution for Point Set Upsampling
Point set is arguably the most direct approximation of an object or scene surface, yet its practical acquisition often suffers from the shortcoming of being noisy, sparse, and possibly incomplete, which restricts its use…
Point Set UpsamplingCNN-based synthesis of realistic high-resolution LiDAR data
This paper presents a novel CNN-based approach for synthesizing high-resolution LiDAR point cloud data. Our approach generates semantically and perceptually realistic results with guidance from specialized loss-functions…
Depth Image UpsamplingPoint Cloud GenerationPoint Set UpsamplingSemantic Segmentation+2Patch-based Progressive 3D Point Set Upsampling
We present a detail-driven deep neural network for point set upsampling. A high-resolution point set is essential for point-based rendering and surface reconstruction. Inspired by the recent success of neural image super…
Point Cloud Super ResolutionPoint Set UpsamplingSuper-ResolutionSurface Reconstruction