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PC 2 -PU: Patch Correlation and Point Correlation for Effective Point Cloud Upsampling

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-58595-2_31openalex-snapshot

Detail Preserved Point Cloud Completion via Separated Feature Aggregation

inferredcites →https://doi.org/10.1007/s11263-021-01564-7openalex-snapshot

RePCD-Net: Feature-Aware Recurrent Point Cloud Denoising Network

inferredcites →https://doi.org/10.1016/j.cagd.2020.101925openalex-snapshot

Multi-stage point completion network with critical set supervision

inferredcites →https://doi.org/10.1016/j.imavis.2017.07.003openalex-snapshot

3D visual perception for self-driving cars using a multi-camera system: Calibration, mapping, localization, and obstacle detection

inferredcites →https://doi.org/10.1109/2945.817351openalex-snapshot

The ball-pivoting algorithm for surface reconstruction

inferredcites →https://doi.org/10.1109/access.2021.3116304openalex-snapshot

Point Transformer

inferredcites →https://doi.org/10.1109/cvpr.2017.16openalex-snapshot

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

inferredcites →https://doi.org/10.1109/cvpr.2017.264openalex-snapshot

A Point Set Generation Network for 3D Object Reconstruction from a Single Image

inferredcites →https://doi.org/10.1109/cvpr.2017.268openalex-snapshot

Scalable Surface Reconstruction from Point Clouds with Extreme Scale and Density Diversity

inferredcites →https://doi.org/10.1109/cvpr.2018.00295openalex-snapshot

PU-Net: Point Cloud Upsampling Network

inferredcites →https://doi.org/10.1109/cvpr.2019.00407openalex-snapshot

GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud

inferredcites →https://doi.org/10.1109/cvpr.2019.00611openalex-snapshot

Patch-Based Progressive 3D Point Set Upsampling

inferredcites →https://doi.org/10.1109/cvpr.2019.01272openalex-snapshot

PCAN: 3D Attention Map Learning Using Contextual Information for Point Cloud Based Retrieval

inferredcites →https://doi.org/10.1109/cvpr35066.2017openalex-snapshot

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

inferredcites →https://doi.org/10.1109/cvpr42600.2020.01112openalex-snapshot

RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds

inferredcites →https://doi.org/10.1109/cvpr46437.2021.00041openalex-snapshot

Point Cloud Upsampling via Disentangled Refinement

inferredcites →https://doi.org/10.1109/cvpr52688.2022.00204openalex-snapshot

Self-Supervised Arbitrary-Scale Point Clouds Upsampling via Implicit Neural Representation

inferredcites →https://doi.org/10.1109/iccv.2019.00167openalex-snapshot

Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data

inferredcites →https://doi.org/10.1109/iccv.2019.00730openalex-snapshot

PU-GAN: A Point Cloud Upsampling Adversarial Network

inferredcites →https://doi.org/10.1109/iccv48922.2021.00454openalex-snapshot

Score-Based Point Cloud Denoising

inferredcites →https://doi.org/10.1109/iccv48922.2021.01595openalex-snapshot

Point Transformer

inferredcites →https://doi.org/10.1109/icme52920.2022.9859662openalex-snapshot

“Zero-Shot” Point Cloud Upsampling

inferredcites →https://doi.org/10.1109/tip.2021.3115385openalex-snapshot

Deep Magnification-Flexible Upsampling Over 3D Point Clouds

inferredcites →https://doi.org/10.1109/tip.2022.3182266openalex-snapshot

SPU-Net: Self-Supervised Point Cloud Upsampling by Coarse-to-Fine Reconstruction With Self-Projection Optimization

inferredcites →https://doi.org/10.1109/tvcg.2003.1175093openalex-snapshot

Computing and rendering point set surfaces

inferredcites →https://doi.org/10.1109/tvcg.2021.3058311openalex-snapshot

Meta-PU: An Arbitrary-Scale Upsampling Network for Point Cloud

inferredcites →https://doi.org/10.1109/tvcg.2022.3170695openalex-snapshot

Rank-PointRetrieval: Reranking Point Cloud Retrieval via a Visually Consistent Registration Evaluation

inferredcites →https://doi.org/10.1109/tvcg.2022.3185247openalex-snapshot

Point Cloud Completion Via Skeleton-Detail Transformer

inferredcites →https://doi.org/10.1140/epjst/e2012-01703-3openalex-snapshot

Smart cities of the future

inferredcites →https://doi.org/10.1145/1276377.1276405openalex-snapshot

Parameterization-free projection for geometry reconstruction

inferredcites →https://doi.org/10.1145/1390156openalex-snapshot

Proceedings of the 25th international conference on Machine learning - ICML '08

inferredcites →https://doi.org/10.1145/2421636.2421645openalex-snapshot

Edge-aware point set resampling

inferredcites →https://doi.org/10.1145/3343031.3351085openalex-snapshot

iDFusion

inferredcites →https://doi.org/10.1145/3394171.3413920openalex-snapshot

Surface Reconstruction with Unconnected Normal Maps: An Efficient Mesh-based Approach

inferredcites →https://doi.org/10.1145/3474085.3475381openalex-snapshot

SSPU-Net: Self-Supervised Point Cloud Upsampling via Differentiable Rendering

inferredcites →https://doi.org/10.1561/2300000035openalex-snapshot

A Review of Point Cloud Registration Algorithms for Mobile Robotics

inferredcites →https://doi.org/10.5220/0010211600700079openalex-snapshot

Point Cloud Upsampling and Normal Estimation using Deep Learning for Robust Surface Reconstruction

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4650262openalex-extracted

Spu-Emvs: Self-Supervised Point Cloud Upsampling Based on Edge-Aware Multiple Views

inferred← citeshttps://doi.org/10.1007/978-3-031-26319-4_7openalex-snapshot

Point Cloud Upsampling via Cascaded Refinement Network

inferred← citeshttps://doi.org/10.1007/978-3-031-73254-6_24openalex-snapshot

Explicitly Guided Information Interaction Network for Cross-Modal Point Cloud Completion

inferred← citeshttps://doi.org/10.1007/978-981-97-5600-1_32openalex-snapshot

Sparse Point Cloud Upsampling Based on Neural Implicit Functions

inferred← citeshttps://doi.org/10.1007/s00138-026-01931-9openalex-snapshot

A structure-preserving diffusion model for point cloud upsampling

inferred← citeshttps://doi.org/10.1007/s00371-024-03535-8openalex-snapshot

Point cloud upsampling via a coarse-to-fine network with transformer-encoder

inferred← citeshttps://doi.org/10.1007/s11263-026-02990-1openalex-snapshot

LatentFlow3D: Unified Point Cloud Processing via Latent Space Modeling in Invertible Neural Networks

inferred← citeshttps://doi.org/10.1016/j.displa.2025.103053openalex-snapshot

Point cloud upsampling via implicit shape priors discovery and refinement

inferred← citeshttps://doi.org/10.1016/j.eswa.2025.126638openalex-snapshot

Denoise yourself: Self-supervised point cloud upsampling with pretrained denoising

inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2026.07.018openalex-snapshot

Aerial–ground LiDAR place recognition with patch-level self-supervised learning and expanded reciprocal re-ranking

inferred← citeshttps://doi.org/10.1016/j.patcog.2026.114668openalex-snapshot

AUPOME: Unifying Anchor-guided UPsampling and Octree Mesh Extraction for Surface Reconstruction

inferred← citeshttps://doi.org/10.1049/cit2.70052openalex-snapshot

Arbitrary‐Scale Point Cloud Upsampling via Enhanced Geometric Spatial Consistency

inferred← citeshttps://doi.org/10.1109/cvpr52733.2024.00496openalex-snapshot

SPU-PMD: Self-Supervised Point Cloud Upsampling via Progressive Mesh Deformation

inferred← citeshttps://doi.org/10.1109/iccv51701.2025.02417openalex-snapshot

Omni-Scene Perception-Oriented Point Cloud Geometry Enhancement for Coordinate Quantization

inferred← citeshttps://doi.org/10.1109/iccvw69036.2025.00275openalex-snapshot

PU-Gaussian: Point Cloud Upsampling using 3D Gaussian Representation

inferred← citeshttps://doi.org/10.1109/icra57147.2024.10611144openalex-snapshot

PillarGen: Enhancing Radar Point Cloud Density and Quality via Pillar-based Point Generation Network

inferred← citeshttps://doi.org/10.1109/jiot.2026.3702155openalex-snapshot

PU-TransMamba: A Hybrid Point Cloud Upsampling Framework With Detail-Aware Transformer and Spatially Coherent Mamba

inferred← citeshttps://doi.org/10.1109/lsp.2025.3631424openalex-snapshot

Contrastive Attention-Based Network for Self-Supervised Point Cloud Completion

inferred← citeshttps://doi.org/10.1109/tim.2024.3500074openalex-snapshot

HFCI-PU: High-Frequency Compensation Interpolation Network for Point Cloud Upsampling

inferred← citeshttps://doi.org/10.1109/tip.2025.3571680openalex-snapshot

SPU+: Dimension Folding for Semantic Point Cloud Upsampling

inferred← citeshttps://doi.org/10.1109/tip.2025.3620666openalex-snapshot

PVNet: Point-Voxel Interaction LiDAR Scene Upsampling via Diffusion Models

inferred← citeshttps://doi.org/10.1109/tits.2024.3454309openalex-snapshot

Pavement Point Cloud Upsampling Based on Transformer: Toward Enhancing 3D Pavement Data

inferred← citeshttps://doi.org/10.1109/tits.2025.3595285openalex-snapshot

WIN: Variable-View Implicit LiDAR Upsampling Network

inferred← citeshttps://doi.org/10.1109/tmm.2023.3289752openalex-snapshot

SGSR-Net: Structure Semantics Guided LiDAR Super-Resolution Network for Indoor LiDAR SLAM

inferred← citeshttps://doi.org/10.1109/tvcg.2026.3679696openalex-snapshot

Arbitrary-Scale Point Cloud Upsampling With Saliency-Aware Implicit Surface Guidance

inferred← citeshttps://doi.org/10.1145/3664647.3680590openalex-snapshot

Reverse2Complete: Unpaired Multimodal Point Cloud Completion via Guided Diffusion

inferred← citeshttps://doi.org/10.1145/3664647.3680767openalex-snapshot

Informative Point cloud Dataset Extraction for Classification via Gradient-based Points Moving

inferred← citeshttps://doi.org/10.1145/3664647.3681500openalex-snapshot

Point Cloud Upsampling with Geometric Algebra Driven Inverse Heat Dissipation

inferred← citeshttps://doi.org/10.1145/3672608.3707900openalex-snapshot

PULLM: A Multimodal Framework for Enhanced 3D Point Cloud Upsampling Using Large Language Models

inferred← citeshttps://doi.org/10.12677/jisp.2023.121003openalex-snapshot

Research on Point Cloud Upsampling Algorithms Based on Deep Learning

inferred← citeshttps://doi.org/10.3233/jifs-232490openalex-snapshot

PU-FPG: Point cloud upsampling via form preserving graph convolutional networks

inferred← citeshttps://doi.org/10.3390/app14156814openalex-snapshot

RE-PU: A Self-Supervised Arbitrary-Scale Point Cloud Upsampling Method Based on Reconstruction

inferred← citeshttps://doi.org/10.3390/app15010174openalex-snapshot

Geometric Detail-Preserved Point Cloud Upsampling via a Feature Enhanced Self-Supervised Network

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