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Paper Citation Record · LEDGER

Deep Learning For Point Cloud Denoising: A Survey

As of 7 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2508.11932.

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

pith.paper-citation-record.v1
2508.11932 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:44:35.943986Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

55 of 55 outbound references displayed

  • verified exact4
  • verified fuzzy47
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 02057199-5cb9-4a5c-8e56-9775c766e521 · outbound

This paper cites Slide: Self-supervised lidar de-snowing through reconstruction difficulty.

Deep Learning For Point Cloud Denoising: A Survey Slide: Self-supervised lidar de-snowing through reconstruction difficulty

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation d7beaab7-126c-48c0-a556-dff80ffa98dd · outbound

This paper cites Deep point set resampling via gradient fields.

Deep Learning For Point Cloud Denoising: A Survey Deep point set resampling via gradient fields

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation fc84a44b-2fae-4137-8aac-11394c87a6f1 · outbound

This paper cites Repcd-net: Feature-aware recurrent point cloud denoising network.

Deep Learning For Point Cloud Denoising: A Survey Repcd-net: Feature-aware recurrent point cloud denoising network

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation f0c2478f-0642-45ce-af19-00146da77bed · outbound

This paper cites Geogcn: Geometric dual-domain graph convolution network for point cloud denoising.

Deep Learning For Point Cloud Denoising: A Survey Geogcn: Geometric dual-domain graph convolution network for point cloud denoising

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.750368Z digest=sha256:ac08892ec7487e3d234fa499306e9e623ee0c345cba626fed03d17c0ae705644

Observation b8518470-c830-4a9c-b7bf-629a9c44c728 · outbound

This paper cites Inferring neural signed distance functions by overfitting on single noisy point clouds through finetuning data-driven based priors.

Deep Learning For Point Cloud Denoising: A Survey Inferring neural signed distance functions by overfitting on single noisy point clouds through finetuning data-driven based priors

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.754218Z digest=sha256:e5fa29f15cc511235abed91b49c2aa06dcc3bef0e440e2378f167371a447b926

Observation bc1049dd-0dc6-4052-80f5-f6e7b33e7e01 · outbound

This paper cites A survey on graph neural networks and graph transformers in computer vision: A task-oriented perspective.

Deep Learning For Point Cloud Denoising: A Survey A survey on graph neural networks and graph transformers in computer vision: A task-oriented perspective

Reference 6

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Source-reported events for the cited work

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Observation 9afb26b2-21bd-4556-9ef8-6da9bc1d6fb1 · outbound

This paper cites Progressive point cloud denoising with cross-stage cross-coder adaptive edge graph convolution network.

Deep Learning For Point Cloud Denoising: A Survey Progressive point cloud denoising with cross-stage cross-coder adaptive edge graph convolution network

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.762823Z digest=sha256:549067981df0c53ef59a725597da2c3fe2014119024fb67969ffa283778daa24

Observation 71691e78-1d95-40a4-8a54-75afc96f9916 · outbound

This paper cites Contrastive learning for joint normal estimation and point cloud filtering.

Deep Learning For Point Cloud Denoising: A Survey Contrastive learning for joint normal estimation and point cloud filtering

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation cd9fb343-5de1-418a-98ab-a9ac2cbfbdc5 · outbound

This paper cites Iterativepfn: True iterative point cloud filtering.

Deep Learning For Point Cloud Denoising: A Survey Iterativepfn: True iterative point cloud filtering

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 93a21de3-881a-4861-a890-5f4dd0daf402 · outbound

This paper cites Straightpcf: Straight point cloud filtering.

Deep Learning For Point Cloud Denoising: A Survey Straightpcf: Straight point cloud filtering

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 01d7752f-dd44-445d-894c-05ec4bb8f6ff · outbound

This paper cites Cnn-based lidar point cloud de-noising in adverse weather.

Deep Learning For Point Cloud Denoising: A Survey Cnn-based lidar point cloud de-noising in adverse weather

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 540c0198-6543-4cd8-8648-7767745d8eef · outbound

This paper cites Dynamic Point Cloud Denoising via Gradient Fields.

Deep Learning For Point Cloud Denoising: A Survey Dynamic Point Cloud Denoising via Gradient Fields

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation efaffb05-f063-4ba7-9a06-209c11341360 · outbound

This paper cites Surface reconstruction from point clouds: A survey and a benchmark.

Deep Learning For Point Cloud Denoising: A Survey Surface reconstruction from point clouds: A survey and a benchmark

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 2506ec4c-4c46-456e-9385-9f92843147d6 · outbound

This paper cites A single-stage point cloud cleaning network for outlier removal and denoising.

Deep Learning For Point Cloud Denoising: A Survey A single-stage point cloud cleaning network for outlier removal and denoising

Reference 14

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raw_fallback, observed 2026-08-05T19:44:36.434189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 0118725f-32e2-4eab-82be-68eb2de772e8 · outbound

This paper cites Pointcvar: Risk-optimized outlier removal for robust 3d point cloud classification.

Deep Learning For Point Cloud Denoising: A Survey Pointcvar: Risk-optimized outlier removal for robust 3d point cloud classification

Reference 15

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4d7563b5-aca6-4eaa-ac72-69ba5be989f1 · outbound

This paper cites Pcdnf: Revisiting learning-based point cloud denoising via joint normal filtering.

Deep Learning For Point Cloud Denoising: A Survey Pcdnf: Revisiting learning-based point cloud denoising via joint normal filtering

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 5f512170-227d-4ea3-a524-64b8bf5ab778 · outbound

This paper cites Pyramidpcd: A novel pyramid network for point cloud denoising.

Deep Learning For Point Cloud Denoising: A Survey Pyramidpcd: A novel pyramid network for point cloud denoising

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation b418d444-3727-4cba-84e8-dbc208f4ec44 · outbound

This paper cites Deep feature-preserving normal estimation for point cloud filtering.

Deep Learning For Point Cloud Denoising: A Survey Deep feature-preserving normal estimation for point cloud filtering

Reference 18

Resolution
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9638058d-7b1e-42cc-a812-91a64d47ed9d · outbound

This paper cites Differentiable manifold reconstruction for point cloud denoising.

Deep Learning For Point Cloud Denoising: A Survey Differentiable manifold reconstruction for point cloud denoising

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 5aff754c-d06c-48f0-8929-8b037a9be1e1 · outbound

This paper cites Score-based point cloud denoising.

Deep Learning For Point Cloud Denoising: A Survey Score-based point cloud denoising

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 564944c5-fd9a-4044-8fc0-f7a62a1e2f2b · outbound

This paper cites Learning signed distance functions from noisy 3d point clouds via noise to noise mapping.

Deep Learning For Point Cloud Denoising: A Survey Learning signed distance functions from noisy 3d point clouds via noise to noise mapping

Reference 21

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.814387Z digest=sha256:fa5ae40634a17632427782b0f317d703ff1086b9b6a719f11e2d37a95a361934

Observation 1d3dea11-825d-4e82-be0d-8d86edac4568 · outbound

This paper cites Pd-flow: A point cloud denoising framework with normalizing flows.

Deep Learning For Point Cloud Denoising: A Survey Pd-flow: A point cloud denoising framework with normalizing flows

Reference 22

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation c7b1731d-38ba-4df8-8ace-39b299997e35 · outbound

This paper cites Denoising point clouds in latent space via graph convolution and invertible neural network.

Deep Learning For Point Cloud Denoising: A Survey Denoising point clouds in latent space via graph convolution and invertible neural network

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.821440Z digest=sha256:1bd9eccca7e82ddd08c199d479e3ad43cf1a038802e6379d62c083803c13f3ba

Observation e9ebd00d-ee75-498d-b253-17c3857cc61a · outbound

This paper cites Mixing-denoising generalizable occupancy networks.

Deep Learning For Point Cloud Denoising: A Survey Mixing-denoising generalizable occupancy networks

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4944e287-ce82-4019-9580-38f1a9de7164 · outbound

This paper cites 4denoisenet: Adverse weather denoising from adjacent point clouds.

Deep Learning For Point Cloud Denoising: A Survey 4denoisenet: Adverse weather denoising from adjacent point clouds

Reference 25

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.827942Z digest=sha256:52ad225bd8593f667e1796d34f237c6bf7cc2d5c4a5c0c91f017dd3f36354a2d

Observation fdd7aeb4-32e0-4b8d-8917-b805ee814272 · outbound

This paper cites Paris-rue-madame database: A 3d mobile laser scanner dataset for benchmarking urban detection, segmentation and classification methods.

Deep Learning For Point Cloud Denoising: A Survey Paris-rue-madame database: A 3d mobile laser scanner dataset for benchmarking urban detection, segmentation and classification methods

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 151f8a60-42e4-4e4c-bb63-94d4f8771a29 · outbound

This paper cites Advancing 3d point cloud understanding through deep transfer learning: A comprehensive survey.

Deep Learning For Point Cloud Denoising: A Survey Advancing 3d point cloud understanding through deep transfer learning: A comprehensive survey

Reference 27

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.834681Z digest=sha256:a04705463019ada417432b87a8ad404cc6a6b110ec8a5765dc2018358d6b2a72

Observation db041a78-c21f-4058-bb38-b587077b17b2 · outbound

This paper cites Sitf: A self-supervised iterative training framework for point cloud denoising.

Deep Learning For Point Cloud Denoising: A Survey Sitf: A self-supervised iterative training framework for point cloud denoising

Reference 28

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.839177Z digest=sha256:7cadc789664beef388a25c3da007aee62a6362e6b9ed80243dc5b76263010d2a

Observation 39d85436-35ba-4eae-bc3b-c81faf91f2b5 · outbound

This paper cites Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions.

Deep Learning For Point Cloud Denoising: A Survey Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T19:44:35.842873Z digest=sha256:3f179db3cb7fb73efb1a9456a894da2e725e0c28527abd3c422656708cf072f1

Observation 8b126933-7b1d-4519-9ded-79261deedeb9 · outbound

This paper cites A critical revisit of adversarial robustness in 3d point cloud recognition with diffusion-driven purification.

Deep Learning For Point Cloud Denoising: A Survey A critical revisit of adversarial robustness in 3d point cloud recognition with diffusion-driven purification

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.279024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.847013Z digest=sha256:b59acda3dc53b4fc5e06d194ad0e221f67666d6c3acd48b62a08e74d6f4f548b

Observation 1bf36b53-1f09-44c1-9ed6-67821b34ac6f · outbound

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

Deep Learning For Point Cloud Denoising: A Survey P2p-bridge: Diffusion bridges for 3d point cloud denoising

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.268489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.850736Z digest=sha256:77f283eb04c2c4a51056e52fd7a7f672409f7960c017d86f01cc2cbaa00691ae

Observation 707a5377-a575-4bae-bd05-0024175cd26e · outbound

This paper cites Mesh denoising via cascaded normal regression.

Deep Learning For Point Cloud Denoising: A Survey Mesh denoising via cascaded normal regression

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.854849Z digest=sha256:90ba7303d7fdeb8ab31116c61cee30f2ad950e99bc9425483b67b0981a8f7159

Observation 66bd13b5-2ccd-4b6c-bc85-9553c79b0468 · outbound

This paper cites Pointfilternet: A filtering network for point cloud denoising.

Deep Learning For Point Cloud Denoising: A Survey Pointfilternet: A filtering network for point cloud denoising

Reference 33

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.858306Z digest=sha256:35da58c25632053971669d6358ec687c7082910554d70666caafc8e809cd0962

Observation f0ee0a55-ff7f-4de0-891e-796a45ab5bf0 · outbound

This paper cites Random screening-based feature aggregation for point cloud denoising.

Deep Learning For Point Cloud Denoising: A Survey Random screening-based feature aggregation for point cloud denoising

Reference 34

Resolution
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raw_fallback, observed 2026-08-05T19:44:36.234680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.862041Z digest=sha256:158fabc8e00f2a24de07366936104cf5366f85fce1ddf66607f127114da9e56a

Observation 01c11900-9281-4c1e-8be0-90ccdc6565e9 · outbound

This paper cites Fcnet: Learning noise-free features for point cloud denoising.

Deep Learning For Point Cloud Denoising: A Survey Fcnet: Learning noise-free features for point cloud denoising

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.224300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.865447Z digest=sha256:e2d06865e7c5bafac4c4ed8139f8a701f16d7c8c3c62d26e8ff1951ff8c76819

Observation 534e596f-23e4-4122-9b9f-bd84d2ab02b2 · outbound

This paper cites Learning implicit fields for point cloud filtering.

Deep Learning For Point Cloud Denoising: A Survey Learning implicit fields for point cloud filtering

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.214076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.869549Z digest=sha256:474380c057031aea60101b98632b3621948470c2ac663a0d2af158c70961b8f6

Observation 1d3fedc1-3219-41a0-8d60-952a8f32f84b · outbound

This paper cites Noise4denoise: Leveraging noise for unsupervised point cloud denoising.

Deep Learning For Point Cloud Denoising: A Survey Noise4denoise: Leveraging noise for unsupervised point cloud denoising

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.203993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.873988Z digest=sha256:657a92cec06a22de96c25336dc34abc38c047a0927b587c26435b4d180ead2da

Observation a124b416-2b92-4518-a85e-b59e323db82c · outbound

This paper cites Geodualcnn: Geometry-supporting dual convolutional neural network for noisy point clouds.

Deep Learning For Point Cloud Denoising: A Survey Geodualcnn: Geometry-supporting dual convolutional neural network for noisy point clouds

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.193888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.877377Z digest=sha256:950bf0bae341422f624006ff09df9572e240c006911fa8cdd965c2e764d49ca4

Observation af383314-6fbb-4038-9456-8fc0428edce8 · outbound

This paper cites Pathnet: Path-selective point cloud denoising.

Deep Learning For Point Cloud Denoising: A Survey Pathnet: Path-selective point cloud denoising

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.183548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.881057Z digest=sha256:019b75015a8c0b83eb3d4b91997319133f2d4f4062e3bea5616e90c745482a58

Observation ecc846a5-a834-462f-bb7b-29edef32b04b · outbound

This paper cites Attention-based point cloud edge sampling.

Deep Learning For Point Cloud Denoising: A Survey Attention-based point cloud edge sampling

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.173277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.884658Z digest=sha256:ac1941a25a8c3f17fdc3e6cfee20e883ec51f042174633b0e4636aad8f80aad5

Observation f3750110-494e-47d9-8da7-c57109b584da · outbound

This paper cites Gradient-based Point Cloud Denoising with Uniformity.

Deep Learning For Point Cloud Denoising: A Survey Gradient-based Point Cloud Denoising with Uniformity

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-05T19:44:36.037314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.888111Z digest=sha256:4bc14576675ce7902b7d1ec50181485aa2b7106f775d8adbc6d37676099341b6

Observation d4af37b0-9088-4b8e-aeaa-421d23e7a44d · outbound

This paper cites Point Cloud Denoising With Fine-Granularity Dynamic Graph Convolutional Networks.

Deep Learning For Point Cloud Denoising: A Survey Point Cloud Denoising With Fine-Granularity Dynamic Graph Convolutional Networks

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-05T19:44:36.021240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.892126Z digest=sha256:55d18ac3e0111bba1d5b2ff44673b1901ecfdff67b980383e934b90d021f76ab

Observation 2ed4152b-56fa-46b7-9bfd-a16651864a0c · outbound

This paper cites Point Cloud Resampling with Learnable Heat Diffusion.

Deep Learning For Point Cloud Denoising: A Survey Point Cloud Resampling with Learnable Heat Diffusion

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-05T19:44:36.004171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.896023Z digest=sha256:4a8834caea3c8638938373c642e8abdfb7e79d33f3c1ef73c022a57798d7ee1b

Observation 4d8f30b5-603c-409b-b8a6-fdf3514d658d · outbound

This paper cites Benchmarking the robustness of lidar semantic segmentation models.

Deep Learning For Point Cloud Denoising: A Survey Benchmarking the robustness of lidar semantic segmentation models

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.162501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.900214Z digest=sha256:9eba1bcdc0cab90edbfff2ba7d749af6b65d50cb4667e27ad691ccfffee199a0

Observation 345683a3-c058-4811-a436-c1ae45e1558e · outbound

This paper cites Pn-internet: Point-and-normal interactive network for noisy point clouds.

Deep Learning For Point Cloud Denoising: A Survey Pn-internet: Point-and-normal interactive network for noisy point clouds

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.152847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.903730Z digest=sha256:8144b8824c930b2c0d0b0d12f652e59e70a86d2271ea58b99f0e3541da47117e

Observation 94469f9e-4821-4857-8924-c0f7b6476d25 · outbound

This paper cites Lisnownet: Real-time snow removal for lidar point clouds.

Deep Learning For Point Cloud Denoising: A Survey Lisnownet: Real-time snow removal for lidar point clouds

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.143313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.907320Z digest=sha256:e2a5029af3c0c11fedce7018ffabeaac4810bb38ebc25f69b4cb317db0286022

Observation 123eaf55-7bc0-4b2f-ba3b-613964da6b99 · outbound

This paper cites Pointfilter: Point cloud filtering via encoder-decoder modeling.

Deep Learning For Point Cloud Denoising: A Survey Pointfilter: Point cloud filtering via encoder-decoder modeling

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.132997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.911068Z digest=sha256:132e6b0ba12a1000d6c878002c5381ba8f8d010bba5175f9c7a2b6db05c753d1

Observation 95ff9f81-3050-4ec8-b6e4-7ec04392c640 · outbound

This paper cites Pd-refiner: An underlying surface inheritance refiner with adaptive edge-aware supervision for point cloud denoising.

Deep Learning For Point Cloud Denoising: A Survey Pd-refiner: An underlying surface inheritance refiner with adaptive edge-aware supervision for point cloud denoising

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.122683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.915076Z digest=sha256:b3306b732bf2919f207f89a821bb3b04b2674bc7c88595d93f672c86306ae5aa

Observation 1d9e758a-ed90-448f-ac84-b336cabbfeab · outbound

This paper cites A comprehensive study of the robustness for lidar-based 3d object detectors against adversarial attacks.

Deep Learning For Point Cloud Denoising: A Survey A comprehensive study of the robustness for lidar-based 3d object detectors against adversarial attacks

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.113148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.919363Z digest=sha256:d63496e71cc1fa260c1dc91840e1cd3a2f57cb6f24dbc39300c1277b169e24f6

Observation 0d4de72c-5649-43a6-87ae-60f781e3481a · outbound

This paper cites From noise addition to denoising: A self-variation capture network for point cloud optimization.

Deep Learning For Point Cloud Denoising: A Survey From noise addition to denoising: A self-variation capture network for point cloud optimization

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.103346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.924239Z digest=sha256:a7d55e03a6fbcacca1bc5b74ce4a7d1ec501d313c72589fe3791ff799a8ca960

Observation 6cd00e62-5eac-4028-bfad-b30e2d0cb8ea · outbound

This paper cites Point cloud denoising via momentum ascent in gradient fields.

Deep Learning For Point Cloud Denoising: A Survey Point cloud denoising via momentum ascent in gradient fields

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.092340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.927902Z digest=sha256:ad0ccdb7f608759499b2e7a17b0e62bc043447b33c644c0b812d0d20986f7452

Observation 2c986b3e-6c20-4542-9a46-0df83cda5847 · outbound

This paper cites TripleMixer: A 3D Point Cloud Denoising Model for Adverse Weather.

Deep Learning For Point Cloud Denoising: A Survey TripleMixer: A 3D Point Cloud Denoising Model for Adverse Weather

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-05T19:44:35.931754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T19:44:35.931754Z digest=sha256:e0a1d28c26eb31306b0e6c973ee3762d8035ec7dce389d8398b7a951772f9265

Observation 377be3a1-417a-4222-866f-a5dba35cf7be · outbound

This paper cites Fast learning of signed distance functions from noisy point clouds via noise to noise mapping.

Deep Learning For Point Cloud Denoising: A Survey Fast learning of signed distance functions from noisy point clouds via noise to noise mapping

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:44:36.080589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:35.936208Z digest=sha256:e370eaf55fb196045ec404d04c6479211e8a362225aa164a2b0acb8fb6696c41

Observation fd44302b-3822-48e6-bfbb-61e9284d1074 · outbound

This paper cites 3DMambaIPF: A State Space Model for Iterative Point Cloud Filtering via Differentiable Rendering.

Deep Learning For Point Cloud Denoising: A Survey 3DMambaIPF: A State Space Model for Iterative Point Cloud Filtering via Differentiable Rendering

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-05T19:44:35.939819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T19:44:35.939819Z digest=sha256:c17b2844365b61467263f75e0cfcaa84e8c416ace99b021be68bcae52e65035b

Observation 3607f25f-0692-43f5-b746-caf1face6286 · outbound

This paper cites write newline.

Deep Learning For Point Cloud Denoising: A Survey write newline

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-05T19:44:35.943986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T19:44:35.943986Z digest=sha256:cfc90fc4771e3bc6f0e6bbcb46f20289de5f97f523586f475cb53ba6c801adeb

Pith citing papers

No inbound Pith citation observations are available.