Pith. sign in

Paper Citation Record · LEDGER

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning

As of 18 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.26583.

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

pith.paper-citation-record.v1
2607.26583 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:55:51.404336Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

24 of 24 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5bb906ba-8f49-487c-9ed3-54bb35b21b0d · outbound

This paper cites Multiscale feature line extraction from raw point clouds based on local surface vari- ation and anisotropic contraction,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Multiscale feature line extraction from raw point clouds based on local surface vari- ation and anisotropic contraction,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:49.464237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:49.464237Z digest=sha256:80d92e6add97fee62c3516d04a2d9a2853558a2d3859e9d95c459830010defed

Observation dd2dbc0f-7582-4aa6-9b06-f81c984af3e5 · outbound

This paper cites A feature extraction approach over workpiece point clouds for robotic welding.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning A feature extraction approach over workpiece point clouds for robotic welding

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:49.524182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:49.524182Z digest=sha256:3b47a2dce61e939bec1c559b35e824a24dae6e39514745ba0baf7876dd6cc7d9

Observation 1257dbc6-7ecf-47ad-85a4-02e7ef9c0c6e · outbound

This paper cites Low-latency visual-based high- quality 3-D reconstruction using point cloud optimization,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Low-latency visual-based high- quality 3-D reconstruction using point cloud optimization,

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:49.623566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:49.623566Z digest=sha256:98dff8c34e9f335ee4da19c90c7191f34ed5739e2df0ee7e41db0c9ed8460378

Observation 742fdd73-bdee-4014-bfcc-074dedc70809 · outbound

This paper cites A method for registration of 3-D shapes,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning A method for registration of 3-D shapes,

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:49.697103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:49.697103Z digest=sha256:a99f74aa4b94592683b1ca0b119469a2108a42be2b6788e1626c7cf63840e9a8

Observation a183cd31-e481-4379-8e21-219f36284268 · outbound

This paper cites Fast point feature histograms (FPFH) for 3D registration,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Fast point feature histograms (FPFH) for 3D registration,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:49.834648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:49.834648Z digest=sha256:2d637405191bf4ef249a8c40a95727ed8d427fa8b91872e4b9f1b24c02ddf384

Observation 35442941-60c1-40a5-81a9-d50437418dcd · outbound

This paper cites RPM-net: Robust point matching using learned features,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning RPM-net: Robust point matching using learned features,

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:49.921869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:49.921869Z digest=sha256:4472f992683208b89e418b356e6c82f1b30c667096bf389991464f7366d7ab04

Observation d0321e23-313a-4a8b-a7e5-abec49a92c6c · outbound

This paper cites Pointnetlk: Robust efficient point cloud registration using pointnet,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Pointnetlk: Robust efficient point cloud registration using pointnet,

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:50.039749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:50.039749Z digest=sha256:a7a6ad8d515c3a1200b91a7809a02d513c55ecdbeca9b94127eb66e9fad76e9f

Observation 20204fc8-cc9c-4cf4-b950-8e486fbfbd90 · outbound

This paper cites Using multi-level consistency learning for partial-to-partial point cloud registration,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Using multi-level consistency learning for partial-to-partial point cloud registration,

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:50.101080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:50.101080Z digest=sha256:bb735f915ab380b826cf7269122a5c090c15c9e66a7e1500a1f84228686ca01f

Observation bc9c54ca-119b-422c-b912-b549490adb76 · outbound

This paper cites Vision meets robotics: The KITTI dataset,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Vision meets robotics: The KITTI dataset,

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:50.163971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:50.163971Z digest=sha256:1affd4c9c4a53662e17c56972ec40b348721fd8fabcb9bdfc2e34cfc4bee0d7a

Observation ecb4d07d-24f7-4264-b58c-d3b222ef3747 · outbound

This paper cites A generalized full-to-partial registration framework of 3d point sets for computer-aided or- thopedic surgery,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning A generalized full-to-partial registration framework of 3d point sets for computer-aided or- thopedic surgery,

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:50.229723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:50.229723Z digest=sha256:fdd66d6c9460543204dfd3451e537451bed5ab1b163f4eb25c0e4715ef00a7dd

Observation e69efb8e-3867-430a-aa3f-4cd825c4abc8 · outbound

This paper cites PGPNet: A Novel Iterative Partial- Global-Partial Point Cloud Registration Method,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning PGPNet: A Novel Iterative Partial- Global-Partial Point Cloud Registration Method,

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:50.289045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:50.289045Z digest=sha256:7dc44543e825c2ee289a8a475bca7a2d15f70158b40a266546f738022bcc8de9

Observation a8dc4e18-bb06-4975-a135-5deafff44484 · outbound

This paper cites iLSPR: A Learning-based Scene Point- cloud Registration method for robotic spatial awareness in intelligent manufacturing,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning iLSPR: A Learning-based Scene Point- cloud Registration method for robotic spatial awareness in intelligent manufacturing,

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:50.361870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:50.361870Z digest=sha256:bc298e4d1be82c1c294c9ddc5974b2ea8aa3981f0f0db27441b4b9af32d25cea

Observation 75da2c01-e172-4bed-aa9e-384565f0a045 · outbound

This paper cites Fast r-cnn,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Fast r-cnn,

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:50.431802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:50.431802Z digest=sha256:426803ca85b881c6cd761d1e1a28bdfbb5eeebe2578bca6f7a9a00715f7a731a

Observation 654d5f45-f32f-47cd-a50e-bcba1c9bdf5a · outbound

This paper cites Cascade R-CNN: High quality object detection and instance segmentation,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Cascade R-CNN: High quality object detection and instance segmentation,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:50.555976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:50.555976Z digest=sha256:03e29997ca39c146c2e698f8f48415b792cba78ed911b69011e9422e835a4883

Observation d0b20adc-b580-4528-aea8-c4780b950856 · outbound

This paper cites Facenet: A unified embedding for face recognition and clustering,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Facenet: A unified embedding for face recognition and clustering,

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:50.692638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:50.692638Z digest=sha256:352c54ea7719672d2ebbdc1acfcd4963b6885989eca370b6af88818d7424cb64

Observation 8f396b84-0b62-4522-97dd-4bdf19d557df · outbound

This paper cites Small_GICP: Efficient and Parallel Algorithms for Point Cloud Registration,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Small_GICP: Efficient and Parallel Algorithms for Point Cloud Registration,

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:50.792881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:50.792881Z digest=sha256:49f57bec2428c386cb532a11351e40bf1381b7fd3d2fcf0b273f03b11ed0f62a

Observation b5b4f7c4-8c7a-47a9-9e37-bf33fd4eba6a · outbound

This paper cites Deep closest point: Learning representations for point cloud registration,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Deep closest point: Learning representations for point cloud registration,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:50.865611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:50.865611Z digest=sha256:ec8cb2185039b2405efa3d39f7e8e0bf7f665cb6f698c867bd060f50a8fb6ebd

Observation 16833f9d-7829-45ef-8fe5-8bd920f58a5c · outbound

This paper cites MFGNet: Multibranch feature generation networks for few-shot remote sensing scene classification,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning MFGNet: Multibranch feature generation networks for few-shot remote sensing scene classification,

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:50.959677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:50.959677Z digest=sha256:66bda0d4dd6e07694074a13ec97cdd33443bc08835350b70a1f6a2b16eff8a7c

Observation 9aa7b873-f977-4f61-a432-784ceaecd12c · outbound

This paper cites Deep weighted consensus dense correspondence confidence maps for 3D shape registration,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Deep weighted consensus dense correspondence confidence maps for 3D shape registration,

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:51.037531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:51.037531Z digest=sha256:5d54c12ca361af40c2dddb246a5082b4c7ececd354dba7a6c2b90a8491c89845

Observation d308d3c1-3483-4a82-9d34-4417ef8c12eb · outbound

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

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Dynamic graph cnn for learning on point clouds,

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:51.110665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:51.110665Z digest=sha256:e539b411f96b6ac5a11f10226d8e2edc38ccc8e5ee898afd3c97efe3c0edf395

Observation 4edace89-2e98-43a3-94d1-dd70bf59c05a · outbound

This paper cites Pointnetlk revisited.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Pointnetlk revisited

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:51.187576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:51.187576Z digest=sha256:a45011d53ab1b7b4f46090cb50320b91c38a2a1d4131a44d3890a293050da560

Observation 304e1929-2ff4-48e5-870f-2ce8a527edcc · outbound

This paper cites RORNet: Partial- to-partial registration network with reliable overlapping representations,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning RORNet: Partial- to-partial registration network with reliable overlapping representations,

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:51.260483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:51.260483Z digest=sha256:9ca33f054f55b56af1920c7ce3ef9a4a907785948b1290b0260079c9dc18d305

Observation 862bb017-4c6a-4615-a302-01491f56b6b1 · outbound

This paper cites 3D Shapenets: A Deep Representation for Volumetric Shapes,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning 3D Shapenets: A Deep Representation for Volumetric Shapes,

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:51.330404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:51.330404Z digest=sha256:79108aff9f4d0d0b0b6e3be98bb185f1018d15fd708b5497748c8b079abf3b4b

Observation 2dbf5b5b-f936-42dc-8ab1-974aa7369563 · outbound

This paper cites Measurement of areas on a sphere using Fibonacci and latitude–longitude lattices,.

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning Measurement of areas on a sphere using Fibonacci and latitude–longitude lattices,

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-01T12:55:51.404336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:55:51.404336Z digest=sha256:665e05d02d1ce2dc5f2906b6a292007ad934ff520521c015a90d22729ea62480

Pith citing papers

No inbound Pith citation observations are available.