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Research map / Point clouds / Shape and surface completion

Point cloud completion networks

Complete partial point clouds with refinement, folding and cycle-based unpaired learning.

50 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2018–2026) · an approach in Shape and surface completion, keyword cluster “cloud completion · complete · shape completion”

State History Tried Checklist Preprints Who Export

Where it stands

Not enough benchmark data Fewer than four papers report the same benchmark, so there is no record to follow.

11 papers in 2023–24 and 19 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic grew, from 12.4% to 16.8%.

How this is decided

A benchmark is tracked when at least four papers of this approach report their own method on the same dataset and metric in at least two different years. Its record is the best number reported up to 2024 compared with the best reported in 2025–26: still improving means at least 1% better, flat means at most 0.2% better with at least two papers from 2025–26 trying. Numbers on a different scale from the rest (a fraction among percentages) and far outliers are left out. Results come from different papers with different setups, so they are signals, not head-to-head comparisons. The share of papers is counted at ICML, NeurIPS, ICLR, CVPR and AAAI.

How it got here

2016: 0162017: 0172018: 1182019: 2192020: 4202021: 7212022: 6222023: 7232024: 4242025: 11252026: 826

Most cited paper of each year

Earliest papers here

What has been tried

42 papers here report 440 measured changes (a component added, removed or swapped, compared with a baseline): helped 79%, no clear effect 3%, hurt 17%, mixed 2%. Papers mostly publish changes that helped, so "helped" is over-represented.

Ablations in recent papers

What was changedMeasured onResultEffectPaper
Add a salient branch to the extensive branchShapeNet seen categories, 64 points · CD-ℓ110.53 -> 9.78HelpedFSC: Few-point Shape Completion (CVPR 2024 · 12 citations)
Add both key-geometry features Fk and missing-part features Fm as SGFormer guidancePCN · CD (L1 × 10³)6.51 -> 6.28HelpedSymmCompletion: High-Fidelity and High-Consistency Point Cloud Completion with Symmetry Guidance (AAAI 2025 · 11 citations)
Add naive shape completionKITTI Car · success63.0 -> 65.2HelpedRobust 3D Tracking with Quality-Aware Shape Completion (AAAI 2024 · 10 citations)
Fuse partial point cloud features with multi-view depth-image features instead of using depth images alonePCN test · CD-Avg (ℓ1 ×103)17.69 -> 6.49HelpedPCDreamer: Point Cloud Completion Through Multi-view Diffusion Priors (CVPR 2025 · 8 citations)
Add SDS refiningRedwood · CD1.98 -> 1.74HelpedGenPC: Zero-shot Point Cloud Completion via 3D Generative Priors (CVPR 2025 · 7 citations)
add mixed samplingShapeNet-ViPC (ablation slice) · L2 Chamfer Distance × 10^-3 (Avg.)2.96 -> 2.21HelpedDigging into Intrinsic Contextual Information for High-fidelity 3D Point Cloud Completion (AAAI 2025 · 3 citations)
Replace polar coordinates with Cartesian coordinatesABC test, architecture ablation · CD2.11 -> 3.34HurtParametric Point Cloud Completion for Polygonal Surface Reconstruction (CVPR 2025 · 3 citations)
Add patch-based self-supervision rather than applying image-level self-supervision directlyUnbalanced MCOP images · completion sharpnessHelpedSelf-Supervised Large Scale Point Cloud Completion for Archaeological Site Restoration (CVPR 2025 · 3 citations)
add the local moduleShape-generator training set · reconstruction loss0.336 -> 0.153HelpedFaceCom: Towards High-fidelity 3D Facial Shape Completion via Optimization and Inpainting Guidance (CVPR 2024 · 3 citations)
Add curvature-based Ball Query anchor refinement with radius 0.075PCN subset · CD-L1 (×1000)14.74 -> 13.58HelpedESCAPE: Equivariant Shape Completion via Anchor Point Encoding (CVPR 2025 · 2 citations)
add Bi-Aux UnitsPCN · CD-ℓ16.62 -> 6.42HelpedPointMAC: Meta-Learned Adaptation for Robust Test-Time Point Cloud Completion (NeurIPS 2025 · 2 citations)
Add explicit geometric guidance via projected point cloudsRealBench · PSNR14.78 -> 16.37HelpedGeoComplete: Geometry-Aware Diffusion for Reference-Driven Image Completion (NeurIPS 2025 · 1 citation)

What reviewers will expect

Datasets and baselines named in the 11 papers of this approach from 2025–2026 that have a full-text summary. Leaving out the common ones is a frequent review question.

Datasets

  • PCN · 5 of 11 papers
  • KITTI · 4 of 11 papers
  • MVP · 3 of 11 papers
  • ShapeNet-ViPC · 2 of 11 papers
  • ShapeNet-55 · 2 of 11 papers
  • ShapeNet-34 · 2 of 11 papers

Baselines

  • PoinTr · 8 of 11 papers
  • PCN · 6 of 11 papers
  • SeedFormer · 5 of 11 papers
  • SnowflakeNet · 5 of 11 papers
  • FoldingNet · 3 of 11 papers
  • TopNet · 3 of 11 papers
  • GRNet · 3 of 11 papers
  • AnchorFormer · 3 of 11 papers

Recent preprints

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    Who publishes on it

    Institutions on the most papers of this approach since 2023 (of 30 papers; from OpenAlex and the papers' affiliations).

    Use it

    Download BibTeX of 40 key papersOpen the topic in the interactive map

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    Same keyword cluster

    Elsewhere in the topic

    Benchmark numbers, ablations and baseline numbers are extracted by AI from each paper's full text and can be wrong; the paper is the authority. Data: results index of 2026-11-02, citation counts from OpenAlex (2026-10-09).

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