Shape and surface completion: research map

332 accepted papers on Shape and surface completion in Point clouds, from ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026), grouped into 2 clusters and 6 approaches. The busiest year so far is 2025.

Within Point clouds, its share grew from 19.5% in 2023–24 to 22.2% in 2025–26 (89 → 113 papers at ICML, NeurIPS, CVPR and AAAI, the venues with data for all four years).

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Approaches and key papers

reconstruction · implicit · meshes · 260 papers

Approaches in this cluster:

Unsupervised shape correspondence (102 papers)
Learn dense shape correspondence and implicit structure from raw point clouds.
Point cloud upsampling and normals (64 papers)
Upsample point clouds and estimate normals with learned surface refinement.
Distance-function surface reconstruction (50 papers)
Reconstruct surfaces by learning signed or unsigned distance functions from point clouds.
Point cloud diffusion generation (44 papers)
Generate 3D shapes with diffusion models over point clouds and latent spaces.

Most cited and most cited since 2024:

A Point Set Generation Network for 3D Object Reconstruction From a Single Image (CVPR 2017 · 2,524 citations)
PU-Net: Point Cloud Upsampling Network (CVPR 2018 · 689 citations)
Point2CAD: Reverse Engineering CAD Models from 3D Point Clouds (CVPR 2024 · 42 citations)
A Conditional Denoising Diffusion Probabilistic Model for Point Cloud Upsampling (CVPR 2024 · 32 citations)

cloud completion · complete · shape completion · 72 papers