point cloud upsampling

PUFM: Efficient Point Cloud Upsampling via Flow Matching AAAI 2026 PUNO: A Neural Operator Framework for Point Cloud Upsampling AAAI 2026 GET-UP: GEomeTric-Aware Depth Estimation with Radar Points UPsampling WACV 2025 PLATYPUS: Progressive Local Surface Estimator for Arbitrary-Scale Point Cloud Upsampling AAAI 2025 Point Cloud Upsampling Using Conditional Diffusion Module with Adaptive Noise Suppression CVPR 2025 SPU-IMR: Self-supervised Arbitrary-scale Point Cloud Upsampling via Iterative Mask-recovery Network AAAI 2025 SuperPC: A Single Diffusion Model for Point Cloud Completion, Upsampling, Denoising, and Colorization CVPR 2025 A Conditional Denoising Diffusion Probabilistic Model for Point Cloud Upsampling CVPR 2024 Arbitrary-Scale Point Cloud Upsampling by Voxel-Based Network with Latent Geometric-Consistent Learning AAAI 2024 Learning Continuous Implicit Field with Local Distance Indicator for Arbitrary-Scale Point Cloud Upsampling AAAI 2024 RepKPU: Point Cloud Upsampling with Kernel Point Representation and Deformation CVPR 2024 SPU-PMD: Self-Supervised Point Cloud Upsampling via Progressive Mesh Deformation CVPR 2024 TULIP: Transformer for Upsampling of LiDAR Point Clouds CVPR 2024 Grad-PU: Arbitrary-Scale Point Cloud Upsampling via Gradient Descent With Learned Distance Functions CVPR 2023 Invertible Residual Neural Networks with Conditional Injector and Interpolator for Point Cloud Upsampling IJCAI 2023 Parametric Surface Constrained Upsampler Network for Point Cloud AAAI 2023 Density-Preserving Deep Point Cloud Compression CVPR 2022 Self-Supervised Arbitrary-Scale Point Clouds Upsampling via Implicit Neural Representation CVPR 2022 Point Cloud Upsampling via Disentangled Refinement CVPR 2021 PU-EVA: An Edge-Vector Based Approximation Solution for Flexible-Scale Point Cloud Upsampling ICCV 2021 PU-GCN: Point Cloud Upsampling Using Graph Convolutional Networks CVPR 2021