Paper Citation Record · LEDGER

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning

As of 4 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2606.06255.

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

pith.paper-citation-record.v1
2606.06255 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T01:02:09.467939Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+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

41 of 41 outbound references displayed

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verified fuzzy0
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External citation measurements

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Outbound references

Observation 904858a6-6366-4506-9e4f-97b8c8378a1c · outbound

This paper cites Comparative evaluation of lidar systems for transport infrastructure: case studies and perfor- mance analysis.European Journal of Remote Sensing, 57(1):2316304, 2024.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Comparative evaluation of lidar systems for transport infrastructure: case studies and perfor- mance analysis.European Journal of Remote Sensing, 57(1):2316304, 2024

Reference 1

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Observation 99608b8b-722d-42d3-b527-183b56a4c441 · outbound

This paper cites Meta architecture for point cloud analysis.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Meta architecture for point cloud analysis

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 485c4a41-fcb0-498a-a707-9c8113464632 · outbound

This paper cites Pointvector: A vector representation in point cloud analysis.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Pointvector: A vector representation in point cloud analysis

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation c860676e-d502-4fd6-979d-e7bacb152197 · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space.Advances in neural information processing systems, 30, 2017.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Pointnet++: Deep hierarchical feature learning on point sets in a metric space.Advances in neural information processing systems, 30, 2017

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation b583dd05-50ca-408e-871d-f130f0d3e087 · outbound

This paper cites Point transformer v3: Simpler, faster, stronger.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Point transformer v3: Simpler, faster, stronger

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 48abdef7-8f47-488c-9de4-a89743c5d1c9 · outbound

This paper cites Towards large-scale 3d representation learning with multi-dataset point prompt training.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Towards large-scale 3d representation learning with multi-dataset point prompt training

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation f4c2f5c6-2125-4e46-b7b7-212b3c3e1658 · outbound

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

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Point transformer v2: Grouped vector attention and partition-based pooling

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 2829be4c-9d9b-4006-938d-033a53ba9b1d · outbound

This paper cites Pointcept: A codebase for point cloud perception research.https://github.com/ Pointcept/Pointcept, 2023.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Pointcept: A codebase for point cloud perception research.https://github.com/ Pointcept/Pointcept, 2023

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation a8021cab-ec70-4cb0-b537-e5a0b61ca9fc · outbound

This paper cites Randla-net: Efficient semantic segmentation of large-scale point clouds.Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2020.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Randla-net: Efficient semantic segmentation of large-scale point clouds.Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2020

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 954d576a-a7cf-4853-a35c-7f4741a40c95 · outbound

This paper cites Pointrcnn: 3d object proposal generation and detection from point cloud.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Pointrcnn: 3d object proposal generation and detection from point cloud

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation dc974b17-8693-4f34-80ca-fe700e0caf19 · outbound

This paper cites Not all points are equal: Learning highly efficient point-based detectors for 3d lidar point clouds.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Not all points are equal: Learning highly efficient point-based detectors for 3d lidar point clouds

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation e9bc9589-fada-4a54-b932-6888d8b6c478 · outbound

This paper cites 3dssd: Point-based 3d single stage object detector.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning 3dssd: Point-based 3d single stage object detector

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 18d5a17f-5ecf-4a68-bed3-4d93efa3ebe1 · outbound

This paper cites STD: sparse-to-dense 3d object detector for point cloud.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning STD: sparse-to-dense 3d object detector for point cloud

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 09c7b8fa-c405-4adf-8d91-4ecadc453046 · outbound

This paper cites Point- mamba: A simple state space model for point cloud analysis.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Point- mamba: A simple state space model for point cloud analysis

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 62e72862-3410-4d95-b681-e65bd2808149 · outbound

This paper cites Point-bert: Pre-training 3d point cloud transformers with masked point modeling.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Point-bert: Pre-training 3d point cloud transformers with masked point modeling

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation fdd5d25b-5e1c-4288-b39c-78b2fe7b9806 · outbound

This paper cites Masked autoencoders for point cloud self-supervised learning.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Masked autoencoders for point cloud self-supervised learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation f7b05027-3f32-4ab6-8362-0ffdfad74531 · outbound

This paper cites 3dctn: 3d convolution-transformer network for point cloud classification.IEEE Transactions on Intelligent Transportation Systems, pages 1–12, 2022.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning 3dctn: 3d convolution-transformer network for point cloud classification.IEEE Transactions on Intelligent Transportation Systems, pages 1–12, 2022

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation e7eaabcf-472f-48db-8d4f-1cae588efe43 · outbound

This paper cites Point-gn: A non-parametric network using gaussian positional en- coding for point cloud classification.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Point-gn: A non-parametric network using gaussian positional en- coding for point cloud classification

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 228757f9-2910-4700-937e-2f024f727344 · outbound

This paper cites 3d semantic parsing of large-scale indoor spaces.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning 3d semantic parsing of large-scale indoor spaces

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation c4f5ac56-5524-4212-bd3f-a128671897c6 · outbound

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

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 6ec2e81e-2316-45db-9f08-6cdc072bd87a · outbound

This paper cites An efficient accelerator for point-based and voxel-based point cloud neural networks.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning An efficient accelerator for point-based and voxel-based point cloud neural networks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99842945-7509-4651-a1a5-73354d1daaef · outbound

This paper cites A point transformer accelerator with fine-grained pipelines and distribution-aware dynamic fps.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning A point transformer accelerator with fine-grained pipelines and distribution-aware dynamic fps

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

Source-reported events for the cited work

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Observation 2149b274-6a2d-4193-903a-746d88274a16 · outbound

This paper cites an unresolved cited work.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 14e11e94-321f-447c-b715-0bf7c47623a7 · outbound

This paper cites Lee, and Hongil Yoon.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Lee, and Hongil Yoon

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation e3f67ce5-c537-409e-b564-1c308e0aec46 · outbound

This paper cites 4d spatio-temporal convnets: Minkowski convolutional neural networks.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning 4d spatio-temporal convnets: Minkowski convolutional neural networks

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 6e9e8016-1cb8-42f6-b06c-c5ac90eaeaf4 · outbound

This paper cites Frustum pointnets for 3d object detection from rgb-d data.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Frustum pointnets for 3d object detection from rgb-d data

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 9c21813b-2514-4bcc-ac12-cac826d64d6d · outbound

This paper cites Semantic segmentation for real point cloud scenes via bilateral aug- mentation and adaptive fusion.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Semantic segmentation for real point cloud scenes via bilateral aug- mentation and adaptive fusion

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation ea607d48-d385-4362-a721-fbfd7bf8fe50 · outbound

This paper cites A volumetric method for building complex models from range images.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning A volumetric method for building complex models from range images

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation e18738e7-c9db-4941-bd41-10890e9f77c2 · outbound

This paper cites Pointacc: Efficient point cloud accelerator.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Pointacc: Efficient point cloud accelerator

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Unavailable: canonical work link unavailable.

Observation 1b22c510-235e-4d17-a064-c03ee061d45b · outbound

This paper cites A point transformer acceler- ator with distribution-aware heuristic distance calculation.IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2024.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning A point transformer acceler- ator with distribution-aware heuristic distance calculation.IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2024

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 1096adb1-9d0b-4f81-a540-debcc94d69d4 · outbound

This paper cites Accelerating point cloud sampling by parallel structure deconstruction.IEEE Transactions on Parallel and Distributed Systems, 37(1):60–75, 2026.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Accelerating point cloud sampling by parallel structure deconstruction.IEEE Transactions on Parallel and Distributed Systems, 37(1):60–75, 2026

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 5b1aacfc-fa67-41e9-b058-996c2d1e2567 · outbound

This paper cites 3D is here: Point Cloud Library (PCL).

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning 3D is here: Point Cloud Library (PCL)

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 7ef956a6-579c-428e-933d-8d54d2a5a5dc · outbound

This paper cites Grid-gcn for fast and scalable point cloud learning.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Grid-gcn for fast and scalable point cloud learning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation f3b3f386-6f54-4f49-8251-184c6b7ecd30 · outbound

This paper cites Kpconv: Flexible and deformable convolution for point clouds.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Kpconv: Flexible and deformable convolution for point clouds

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 0cf80759-56ef-4163-a99e-cbb495731cd5 · outbound

This paper cites Pgformer: a point cloud segmentation network for urban scenes combining grouped transformer and kpconv.IEEE Transactions on Geoscience and Remote Sensing, 2025.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Pgformer: a point cloud segmentation network for urban scenes combining grouped transformer and kpconv.IEEE Transactions on Geoscience and Remote Sensing, 2025

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Observation 2dc07ef1-6073-43c2-b292-cdbf19bc3607 · outbound

This paper cites Edgepc: Ef- ficient deep learning analytics for point clouds on edge devices.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Edgepc: Ef- ficient deep learning analytics for point clouds on edge devices

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b052bac8-6ed0-4cb6-a70f-6605b640a367 · outbound

This paper cites An adjustable farthest point sampling method for approximately-sorted point cloud data.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning An adjustable farthest point sampling method for approximately-sorted point cloud data

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Unavailable: canonical work link unavailable.

Observation 5dd83467-5ee7-4246-9366-de5f2a1c4360 · outbound

This paper cites Van-icp: Gpu-accelerated approximate nearest neighbor search for icp regis- tration via voxel dilation.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Van-icp: Gpu-accelerated approximate nearest neighbor search for icp regis- tration via voxel dilation

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4997ac62-1a8d-46c3-b7d5-ba4df51c4446 · outbound

This paper cites Accelerating nearest neighbor search in 3d point cloud regis- tration on gpus.ACM Transactions on Architecture and Code Optimization, 22(1):1–24, 2025.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Accelerating nearest neighbor search in 3d point cloud regis- tration on gpus.ACM Transactions on Architecture and Code Optimization, 22(1):1–24, 2025

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Unavailable: canonical work link unavailable.

Observation 60443667-2991-46ba-b262-c1dd84b57819 · outbound

This paper cites Behley, M.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning Behley, M

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-28T01:02:09.467939Z

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Unavailable: canonical work link unavailable.

Observation 9285bfc8-5a28-47bd-9bb1-6c2fe2e1777e · outbound

This paper cites PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies.

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T13:46:59.169496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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