Paper Citation Record · LEDGER

Efficient Point Clouds Upsampling via Flow Matching

As of 12 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 2 inbound Pith citation observations for arXiv:2501.15286.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.15286 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:30:48.481689Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-11T01:06:08.695404Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T16:31:09.272137Z

Reference resolution

50 of 50 outbound references displayed

verified exact0
verified fuzzy45
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0b9278e4-3f47-4838-8ea1-e815bf548258 · outbound

This paper cites Bernardini and et al.

Efficient Point Clouds Upsampling via Flow Matching Bernardini and et al

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.988485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 978286b0-6217-404f-a876-50e8f4608b88 · outbound

This paper cites Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner.

Efficient Point Clouds Upsampling via Flow Matching Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.937563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3ff2ac4f-2d7c-400f-83cd-243812395103 · outbound

This paper cites Inversion by direct iteration: An alternative to denoising diffusion for image restoration.

Efficient Point Clouds Upsampling via Flow Matching Inversion by direct iteration: An alternative to denoising diffusion for image restoration

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.927875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b7564c7e-c4aa-4808-b84b-46daa87efc1f · outbound

This paper cites Neural points: Point cloud representation with neural fields for arbitrary upsampling.

Efficient Point Clouds Upsampling via Flow Matching Neural points: Point cloud representation with neural fields for arbitrary upsampling

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.918412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 31fb97e2-90c4-4986-a83f-8bbad6c775db · outbound

This paper cites Grad-pu: Arbitrary- scale point cloud upsampling via gradient descent with learned distance functions.

Efficient Point Clouds Upsampling via Flow Matching Grad-pu: Arbitrary- scale point cloud upsampling via gradient descent with learned distance functions

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.879474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 492c4a0f-0602-402b-b015-4c4490a53c6b · outbound

This paper cites Denoising diffu- sion probabilistic models.

Efficient Point Clouds Upsampling via Flow Matching Denoising diffu- sion probabilistic models

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.869915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2bc78e2a-016f-4ea0-86b1-5fa1fb1c2426 · outbound

This paper cites Surface reconstruction from unorganized points.

Efficient Point Clouds Upsampling via Flow Matching Surface reconstruction from unorganized points

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.859779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6a7c4dda-160d-4f6e-892a-54ca79070367 · outbound

This paper cites Tp- node: Topology-aware progressive noising and denoising of point clouds towards upsampling.

Efficient Point Clouds Upsampling via Flow Matching Tp- node: Topology-aware progressive noising and denoising of point clouds towards upsampling

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.841915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e1723bd0-84a9-42e9-af55-bccb914ca074 · outbound

This paper cites and et al., 2007] Yaron L.

Efficient Point Clouds Upsampling via Flow Matching and et al., 2007] Yaron L

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.832006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 906bab22-70ea-46c8-b3df-54bcb4ea2b24 · outbound

This paper cites an unresolved cited work.

Efficient Point Clouds Upsampling via Flow Matching Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:30:48.802475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2f01913f-4e32-408e-947a-6947094b1a7e · outbound

This paper cites Flow matching for generative modeling.

Efficient Point Clouds Upsampling via Flow Matching Flow matching for generative modeling

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.793244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 39efc461-4cac-4737-a509-a0432eab65dc · outbound

This paper cites Flow match- ing for generative modeling.

Efficient Point Clouds Upsampling via Flow Matching Flow match- ing for generative modeling

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.784348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 53e18d03-7cdd-45ce-96b2-51e5cf937afe · outbound

This paper cites Arbitrary point cloud upsampling via dual back-projection network.

Efficient Point Clouds Upsampling via Flow Matching Arbitrary point cloud upsampling via dual back-projection network

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.775516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 197778b9-f0f4-470c-92b8-99e93a516e86 · outbound

This paper cites Low rank matrix approximation for 3d geometry filtering.

Efficient Point Clouds Upsampling via Flow Matching Low rank matrix approximation for 3d geometry filtering

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.766057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b0cfb3ff-4010-492e-9fca-ff7e61321741 · outbound

This paper cites Diffusion probabilistic models for 3d point cloud generation.

Efficient Point Clouds Upsampling via Flow Matching Diffusion probabilistic models for 3d point cloud generation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.756737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 31ff2e26-bd5c-4927-8068-c4773b910a41 · outbound

This paper cites Rethinking network design and local geometry in point cloud: A simple resid- ual mlp framework.

Efficient Point Clouds Upsampling via Flow Matching Rethinking network design and local geometry in point cloud: A simple resid- ual mlp framework

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.746654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation faea659a-a247-451b-bebd-cf4ab8eb0462 · outbound

This paper cites Pu-flow: A point cloud upsampling network with normalizing flows.

Efficient Point Clouds Upsampling via Flow Matching Pu-flow: A point cloud upsampling network with normalizing flows

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.736748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b412e70a-f5be-4617-855d-a0f97a718f01 · outbound

This paper cites Self- sampling for neural point cloud consolidation.

Efficient Point Clouds Upsampling via Flow Matching Self- sampling for neural point cloud consolidation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.726010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0c95ef9e-6755-4075-8d09-966f838df377 · outbound

This paper cites Fast point transformer.

Efficient Point Clouds Upsampling via Flow Matching Fast point transformer

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.716403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ecb60d73-0a49-4285-90ea-70b01d12bf64 · outbound

This paper cites Qi and et al.

Efficient Point Clouds Upsampling via Flow Matching Qi and et al

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.706586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7fdd4852-c0c5-4c11-a56f-f9583abd81f1 · outbound

This paper cites PUGeo-Net: A Geometry-centric Network for 3D Point Cloud Upsampling.

Efficient Point Clouds Upsampling via Flow Matching PUGeo-Net: A Geometry-centric Network for 3D Point Cloud Upsampling

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T14:30:48.426014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac27bc66-7e7c-473d-b790-720d3ea01352 · outbound

This paper cites Pu-gcn: Point cloud upsampling using graph convolutional net- works.

Efficient Point Clouds Upsampling via Flow Matching Pu-gcn: Point cloud upsampling using graph convolutional net- works

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.697038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8ea23182-ef0c-4623-a4b9-340d8d13ce3c · outbound

This paper cites Pointnext: revisiting pointnet++ with improved training and scaling strategies.

Efficient Point Clouds Upsampling via Flow Matching Pointnext: revisiting pointnet++ with improved training and scaling strategies

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.687582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1d510b50-8c41-4d82-bba4-a2f7739b84f5 · outbound

This paper cites A conditional de- noising diffusion probabilistic model for point cloud up- sampling.

Efficient Point Clouds Upsampling via Flow Matching A conditional de- noising diffusion probabilistic model for point cloud up- sampling

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.678090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fc6a48f7-036c-49cd-ab76-4be77bf65ee4 · outbound

This paper cites Repkpu: Point cloud upsampling with kernel point representation and de- formation.

Efficient Point Clouds Upsampling via Flow Matching Repkpu: Point cloud upsampling with kernel point representation and de- formation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.668859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4dcd2971-3050-4cee-8f28-daa936a6b2c4 · outbound

This paper cites Singh and et al.

Efficient Point Clouds Upsampling via Flow Matching Singh and et al

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.660129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5473c82a-3deb-406d-b711-0a94b1ae876a · outbound

This paper cites Kp- conv: Flexible and deformable convolution for point clouds.

Efficient Point Clouds Upsampling via Flow Matching Kp- conv: Flexible and deformable convolution for point clouds

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.650783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f37bda7f-b949-4010-ab74-d5095f07ee0f · outbound

This paper cites Atten- tion is all you need.

Efficient Point Clouds Upsampling via Flow Matching Atten- tion is all you need

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.641701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 373a1520-214c-48b7-a904-ffbb182402b1 · outbound

This paper cites P2p-bridge: Diffusion bridges for 3d point cloud denoising.

Efficient Point Clouds Upsampling via Flow Matching P2p-bridge: Diffusion bridges for 3d point cloud denoising

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.632149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6e3eb1bb-e879-4672-ab71-28f1d5ce508f · outbound

This paper cites Dynamic graph cnn for learning on point clouds.

Efficient Point Clouds Upsampling via Flow Matching Dynamic graph cnn for learning on point clouds

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.622008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0c7377cf-a12c-4ff9-b897-ee5c73fed7b1 · outbound

This paper cites Self- supervised arbitrary-scale point clouds upsampling via im- plicit neural representation.

Efficient Point Clouds Upsampling via Flow Matching Self- supervised arbitrary-scale point clouds upsampling via im- plicit neural representation

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.611462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 24d7263c-8848-4910-89e3-c73796082e4e · outbound

This paper cites Point trans- former v2: Grouped vector attention and partition-based pooling.

Efficient Point Clouds Upsampling via Flow Matching Point trans- former v2: Grouped vector attention and partition-based pooling

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.600737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 650cd9e0-538c-447a-9263-a85ee3472209 · outbound

This paper cites Point transformer v2: Grouped vector attention and partition-based pooling.

Efficient Point Clouds Upsampling via Flow Matching Point transformer v2: Grouped vector attention and partition-based pooling

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.590153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f2e3e578-8f60-4349-b3ff-8bd645f52929 · outbound

This paper cites Visual point cloud forecasting enables scalable autonomous driving.

Efficient Point Clouds Upsampling via Flow Matching Visual point cloud forecasting enables scalable autonomous driving

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.579868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3c3b7298-b296-4be5-b781-b3262d166977 · outbound

This paper cites Yifan and et al.

Efficient Point Clouds Upsampling via Flow Matching Yifan and et al

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.569236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 100ec8ae-5864-45ae-8d95-2df022d2231a · outbound

This paper cites Yu and et al.

Efficient Point Clouds Upsampling via Flow Matching Yu and et al

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.558113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3b8a9995-702f-485d-a1f3-00030f03c057 · outbound

This paper cites Linked Dynamic Graph CNN: Learning on Point Cloud via Linking Hierarchical Features.

Efficient Point Clouds Upsampling via Flow Matching Linked Dynamic Graph CNN: Learning on Point Cloud via Linking Hierarchical Features

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-10T14:30:48.478533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 415fa823-f31e-4ec6-a5e9-77d3aad70906 · outbound

This paper cites Point transformer.

Efficient Point Clouds Upsampling via Flow Matching Point transformer

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.537237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cfc5a81a-23fc-4d69-a48d-f9141aeba73c · outbound

This paper cites 3d gaus- sian splatting for real-time radiance field rendering.

Efficient Point Clouds Upsampling via Flow Matching 3d gaus- sian splatting for real-time radiance field rendering

Reference 1992

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.850555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7223ffd1-b012-4cc1-a142-f6291dca2d94 · outbound

This paper cites Charles, H.

Efficient Point Clouds Upsampling via Flow Matching Charles, H

Reference 1999

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.978920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e9876b82-f959-4ab4-8c87-b3488d1c33d6 · outbound

This paper cites Spot- compose: A framework for open-vocabulary object re- trieval and drawer manipulation in point clouds.

Efficient Point Clouds Upsampling via Flow Matching Spot- compose: A framework for open-vocabulary object re- trieval and drawer manipulation in point clouds

Reference 2007

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.822649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6141cd1e-2d07-408b-9a1f-7329c9de6ac2 · outbound

This paper cites an unresolved cited work.

Efficient Point Clouds Upsampling via Flow Matching Unresolved cited work

Reference 2013

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:30:48.898083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dda3a7c2-a6c2-4587-b725-4b8a6d12d0f3 · outbound

This paper cites Pointmixup: Augmentation for point clouds.

Efficient Point Clouds Upsampling via Flow Matching Pointmixup: Augmentation for point clouds

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.969468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8b15e780-d696-4142-baef-71b0dacb608f · outbound

This paper cites Pointr: Diverse point cloud completion with geometry-aware transform- ers.

Efficient Point Clouds Upsampling via Flow Matching Pointr: Diverse point cloud completion with geometry-aware transform- ers

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.548023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f45fd44e-e231-4116-ad94-83ccb12fdd9e · outbound

This paper cites Joint Point Cloud Upsampling and Cleaning with Octree-based CNNs.

Efficient Point Clouds Upsampling via Flow Matching Joint Point Cloud Upsampling and Cleaning with Octree-based CNNs

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-10T14:30:48.389921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0249a01-c3d5-4e52-b48e-a26af5f37bf0 · outbound

This paper cites Deep point set resampling via gradient fields.

Efficient Point Clouds Upsampling via Flow Matching Deep point set resampling via gradient fields

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.959549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 224469d3-9774-4561-8a4e-173ab43afa2f · outbound

This paper cites Point2mesh: A self-prior for deformable meshes.

Efficient Point Clouds Upsampling via Flow Matching Point2mesh: A self-prior for deformable meshes

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.888673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1ef96fb1-2377-45a8-9636-93106770ffc3 · outbound

This paper cites Vision meets robotics: The kitti dataset.

Efficient Point Clouds Upsampling via Flow Matching Vision meets robotics: The kitti dataset

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.907822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 14254d8b-9cec-4f55-9724-c74d351af8d0 · outbound

This paper cites Pointcept: A codebase for point cloud perception research.

Efficient Point Clouds Upsampling via Flow Matching Pointcept: A codebase for point cloud perception research

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.947932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8bfe4475-05d3-4a49-a056-560154b6f37b · outbound

This paper cites Point cloud upsam- pling via disentangled refinement.

Efficient Point Clouds Upsampling via Flow Matching Point cloud upsam- pling via disentangled refinement

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:30:48.812622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

Observation 0a9bd28f-4e4d-4a62-bf5e-11c0594d07e2 · inbound

Super-Resolution of Airborne Laser Scanning Point Clouds for Forest Inventory cites this paper.

Super-Resolution of Airborne Laser Scanning Point Clouds for Forest Inventory Efficient Point Clouds Upsampling via Flow Matching

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:31:09.279132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 497cef4d-8fd3-4cbd-940e-17cbb1f41a5d · inbound

Super-Resolution of Airborne Laser Scanning Point Clouds for Forest Inventory cites this paper.

Super-Resolution of Airborne Laser Scanning Point Clouds for Forest Inventory Efficient Point Clouds Upsampling via Flow Matching

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:45:58.073340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.