Point Cloud Completion

34 papers with code • 2 benchmarks • 3 datasets

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Most implemented papers

Pointer Networks

PaddlePaddle/models NeurIPS 2015

It differs from the previous attention attempts in that, instead of using attention to blend hidden units of an encoder to a context vector at each decoder step, it uses attention as a pointer to select a member of the input sequence as the output.

PCN: Point Completion Network

wentaoyuan/pcn 2 Aug 2018

Shape completion, the problem of estimating the complete geometry of objects from partial observations, lies at the core of many vision and robotics applications.

AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation

ThibaultGROUEIX/AtlasNet 15 Feb 2018

We introduce a method for learning to generate the surface of 3D shapes.

Unpaired Point Cloud Completion on Real Scans using Adversarial Training

xuelin-chen/pcl2pcl-gan-pub ICLR 2020

As 3D scanning solutions become increasingly popular, several deep learning setups have been developed geared towards that task of scan completion, i. e., plausibly filling in regions there were missed in the raw scans.

Morphing and Sampling Network for Dense Point Cloud Completion

Colin97/MSN-Point-Cloud-Completion 30 Nov 2019

3D point cloud completion, the task of inferring the complete geometric shape from a partial point cloud, has been attracting attention in the community.

PF-Net: Point Fractal Network for 3D Point Cloud Completion

zztianzz/PF-Net-Point-Fractal-Network CVPR 2020

Unlike existing point cloud completion networks, which generate the overall shape of the point cloud from the incomplete point cloud and always change existing points and encounter noise and geometrical loss, PF-Net preserves the spatial arrangements of the incomplete point cloud and can figure out the detailed geometrical structure of the missing region(s) in the prediction.

Multi-View Partial (MVP) Point Cloud Challenge 2021 on Completion and Registration: Methods and Results

paul007pl/MVP_Benchmark 22 Dec 2021

Based on the MVP dataset, this paper reports methods and results in the Multi-View Partial Point Cloud Challenge 2021 on Completion and Registration.

TopNet: Structural Point Cloud Decoder

lynetcha/completion3d CVPR 2019

a collection of manifolds or surfaces, for the generated point cloud of a 3D object.

GRNet: Gridding Residual Network for Dense Point Cloud Completion

hzxie/GRNet ECCV 2020

In particular, we devise two novel differentiable layers, named Gridding and Gridding Reverse, to convert between point clouds and 3D grids without losing structural information.