point cloud upsampling

Benchmarks archive 2025-07-28

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Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 36 papers with code (62 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Point Cloud Upsampling via Disentangled Refinement
  9 Jun 2021 3 repositories listed Syntology ran 9 of 22 samples · 13 unverified · 11 pointer-only (licence)
  Point clouds produced by 3D scanning are often sparse, non-uniform, and noisy.
• PU-GAN: a Point Cloud Upsampling Adversarial Network
  25 Jul 2019 3 repositories listed
  Point clouds acquired from range scans are often sparse, noisy, and non-uniform.
• PU-Net: Point Cloud Upsampling Network
  21 Jan 2018 3 repositories listed
  Learning and analyzing 3D point clouds with deep networks is challenging due to the sparseness and irregularity of the data.
• Learning a More Continuous Zero Level Set in Unsigned Distance Fields through Level Set Projection
  22 Aug 2023 2 repositories listed Syntology ran 4 of 4 samples · 0 unverified
  We pull the non-zero level sets onto the zero level set with gradient constraints which align gradients over different level sets and correct unsigned distance errors on the zero level set, leading to a smoother and…
• PU-Transformer: Point Cloud Upsampling Transformer
  24 Nov 2021 2 repositories listed
  Given the rapid development of 3D scanners, point clouds are becoming popular in AI-driven machines.
• Score-Based Point Cloud Denoising
  23 Jul 2021 2 repositories listed Syntology ran 2 of 3 samples · 1 unverified
  Since p * n is unknown at test-time, and we only need the score (i.
• SPU-IMR: Self-supervised Arbitrary-scale Point Cloud Upsampling via Iterative Mask-recovery Network
  26 Feb 2025 1 repository listed
  Point cloud upsampling aims to generate dense and uniformly distributed point sets from sparse point clouds.
• Efficient Point Clouds Upsampling via Flow Matching
  25 Jan 2025 1 repository listed
  To address these inefficiencies, we propose PUFM, a flow matching approach to directly map sparse point clouds to their high-fidelity dense counterparts.
• Point Cloud Upsampling Using Conditional Diffusion Module with Adaptive Noise Suppression
  1 Jan 2025 1 repository listed
  Point cloud upsampling can improve the quality of the initial point cloud, significantly enhancing the performance of downstream tasks such as classification and segmentation.
• Joint Point Cloud Upsampling and Cleaning with Octree-based CNNs
  22 Oct 2024 1 repository listed
  Recovering dense and uniformly distributed point clouds from sparse or noisy data remains a significant challenge.
• GET-UP: GEomeTric-aware Depth Estimation with Radar Points UPsampling
  2 Sep 2024 1 repository listed
  However, existing algorithms process the inherently noisy and sparse radar data by projecting 3D points onto the image plane for pixel-level feature extraction, overlooking the valuable geometric information contained…
• Arbitrary-Scale Point Cloud Upsampling by Voxel-Based Network with Latent Geometric-Consistent Learning
  8 Mar 2024 1 repository listed Syntology ran 14 of 14 samples · 0 unverified
  Recently, arbitrary-scale point cloud upsampling mechanism became increasingly popular due to its efficiency and convenience for practical applications.
• SPU-PMD: Self-Supervised Point Cloud Upsampling via Progressive Mesh Deformation
  1 Jan 2024 1 repository listed
  Motivated by this we present SPU-PMD a self-supervised topological mesh deformation network for 3D densification.
• RepKPU: Point Cloud Upsampling with Kernel Point Representation and Deformation
  1 Jan 2024 1 repository listed
  Moreover we propose a novel paradigm namely Kernel-to-Displacement generation for point generation where point cloud upsampling is reformulated as the deformation of kernel points.
• A Conditional Denoising Diffusion Probabilistic Model for Point Cloud Upsampling
  3 Dec 2023 1 repository listed
  Most of the existing point cloud upsampling methods focus on sparse point cloud feature extraction and upsampling module design.
• iPUNet:Iterative Cross Field Guided Point Cloud Upsampling
  13 Oct 2023 1 repository listed
  To solve the non-uniformity of input points, on top of the cross field guided upsampling, we further introduce an iterative strategy that refines the point distribution by moving sparse points onto the desired…
• PU-Ray: Domain-Independent Point Cloud Upsampling via Ray Marching on Neural Implicit Surface
  12 Oct 2023 1 repository listed
  While recent advancements in deep-learning point cloud upsampling methods have improved the input to intelligent transportation systems, they still suffer from issues of domain dependency between synthetic and…
• TP-NoDe: Topology-aware Progressive Noising and Denoising of Point Clouds towards Upsampling
  2 Oct 2023 1 repository listed
  TP-NoDe mitigates the need for task-specific training of upsampling networks for a specific upsampling ratio by reusing a point cloud denoising framework.
• PU-EdgeFormer: Edge Transformer for Dense Prediction in Point Cloud Upsampling
  2 May 2023 1 repository listed
  We employ graph convolution using EdgeConv, which learns the local geometry and global structure of point cloud better than existing point-to-feature method.
• Grad-PU: Arbitrary-Scale Point Cloud Upsampling via Gradient Descent with Learned Distance Functions
  24 Apr 2023 1 repository listed
  Most existing point cloud upsampling methods have roughly three steps: feature extraction, feature expansion and 3D coordinate prediction.
• Parametric Surface Constrained Upsampler Network for Point Cloud
  14 Mar 2023 1 repository listed Syntology ran 4 of 6 samples · 2 unverified · 6 pointer-only (licence)
  Designing a point cloud upsampler, which aims to generate a clean and dense point cloud given a sparse point representation, is a fundamental and challenging problem in computer vision.
• Point Cloud Upsampling via Cascaded Refinement Network
  8 Oct 2022 1 repository listed
  In this manner, the proposed cascaded refinement network can be easily optimized without extra learning strategies.
• CU-Net: Real-Time High-Fidelity Color Upsampling for Point Clouds
  12 Sep 2022 1 repository listed
  Point cloud upsampling is essential for high-quality augmented reality, virtual reality, and telepresence applications, due to the capture, processing, and communication limitations of existing technologies.
• Arbitrary Point Cloud Upsampling with Spherical Mixture of Gaussians
  10 Aug 2022 1 repository listed
  Generating dense point clouds from sparse raw data benefits downstream 3D understanding tasks, but existing models are limited to a fixed upsampling ratio or to a short range of integer values.
• Neural Points: Point Cloud Representation with Neural Fields for Arbitrary Upsampling
  8 Dec 2021 1 repository listed
  Different from traditional point cloud representation where each point only represents a position or a local plane in the 3D space, each point in Neural Points represents a local continuous geometric shape via neural…
• TPU-GAN: Learning temporal coherence from dynamic point cloud sequences
  29 Sep 2021 1 repository listed
  Our model, Temporal Point cloud Upsampling GAN (TPU-GAN), can implicitly learn the underlying temporal coherence from point cloud sequence, which in turn guides the generator to produce temporally coherent output.
• PC²-PU: Patch Correlation and Point Correlation for Effective Point Cloud Upsampling
  20 Sep 2021 1 repository listed
  Point cloud upsampling is to densify a sparse point set acquired from 3D sensors, providing a denser representation for the underlying surface.
• SSPU-Net: Self-Supervised Point Cloud Upsampling via Differentiable Rendering
  1 Aug 2021 1 repository listed
  To achieve this, we exploit the consistency between the input sparse point cloud and generated dense point cloud for the shapes and rendered images.
• PU-Flow: a Point Cloud Upsampling Network with Normalizing Flows
  13 Jul 2021 1 repository listed
  Point cloud upsampling aims to generate dense point clouds from given sparse ones, which is a challenging task due to the irregular and unordered nature of point sets.
• "Zero-Shot" Point Cloud Upsampling
  25 Jun 2021 1 repository listed
  Recent supervised point cloud upsampling methods are restricted by the size of training data and are limited in terms of covering all object shapes.

Syntology lines on 5 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.