This is the official PyTorch implementation of our paper "Grad-PU: Arbitrary-Scale Point Cloud Upsampling via Gradient Descent with Learned Distance Functions" (CVPR 2023).
☆92May 5, 2023Updated 2 years ago
Alternatives and similar repositories for Grad-PU
Users that are interested in Grad-PU are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Self-Supervised Arbitrary-Scale Implicit Point Clouds Upsampling (TPAMI 2023)☆16Jul 7, 2023Updated 2 years ago
- Code Release for AAAI 2024, "Learning Continuous Implicit Field with Local Distance Indicator for Arbitrary-Scale Point Cloud Upsampling"☆33Mar 8, 2024Updated 2 years ago
- SPU-Net: Self-supervised Point Cloud Upsampling by Coarse-to-Fine Reconstruction with Self-Projection Optimization☆12Mar 21, 2023Updated 3 years ago
- Unofficial Implement PU-Transformer☆19Jul 15, 2022Updated 3 years ago
- Point Cloud Upsampling with Kernel Point Representation and Deformation☆48Jun 19, 2024Updated last year
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click and start building anything your business needs.
- Self-Supervised Arbitrary-Scale Point Clouds Upsampling via Implicit Neural Representation (CVPR 2022)☆44Dec 10, 2023Updated 2 years ago
- [A Conditional Denoising Diffusion Probabilistic Model for Point Cloud Upsampling, 2024, CVPR]☆160Dec 10, 2024Updated last year
- Meta-PU: An Arbitrary-Scale Upsampling Network for Point Cloud (TVCG 2021)☆34Apr 17, 2021Updated 4 years ago
- [CVPR'21] PU-GCN: Point Cloud Upsampling using Graph Convolutional Networks