(latest updates and bug fixed) DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction
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Updated
Dec 8, 2021 - C++
(latest updates and bug fixed) DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
Linked Dynamic Graph CNN: Learning through Point Cloud by Linking Hierarchical Features
PointNet implementation on Windows (pyTorch version, most of codes are brorrowed from Fxia22)
This is the official repository of the original Point Transformer architecture.
Learning Local Displacements for Point Cloud Completion - CVPR 2022
The code repository of DGCNN on FPGA: Acceleration of The Point Cloud Classifier Using FPGAs
Implementation of "Long-Range Grouping Transformer for Multi-View 3D Reconstruction" [ICCV 2023]
3D-shape compression with a shape-coded auto-decoder and sinusoidal activations.
PointNet & ShapeNet
Explore the impact of occlusion on Pix2Vox, a multi-view 3D reconstruction model, and possible approaches for improving its generated 3D shapes, including inpainting using StableDiffusion.
A python script to convert and down-sample mesh data into pointclouds using FPS algorithm.
Point Cloud Segmentation Using PointNet
Three-dimensional model retrieval in single category.
A lightweight neural network for multi-view classification and reconstruction.
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