Paper Citation Record · LEDGER

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting

As of 11 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 2 inbound Pith citation observations for arXiv:2501.13971.

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

pith.paper-citation-record.v1
2501.13971 v2

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:50:53.896372Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T21:13:20.089629Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T19:22:50.664171Z

Reference resolution

54 of 54 outbound references displayed

verified exact0
verified fuzzy39
unresolved14
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a0d80b76-3766-415d-b278-74c259b15736 · outbound

This paper cites write newline.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting write newline

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f375c6c-9a3d-4db9-9de0-153165d91e4c · outbound

This paper cites Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.762762Z

Source-reported events for the cited work

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Observation dc14c729-fd9b-4a22-b4d9-5091e1473432 · outbound

This paper cites Barron, Ben Mildenhall, Dor Verbin, Pratul P.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Barron, Ben Mildenhall, Dor Verbin, Pratul P

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.739193Z

Source-reported events for the cited work

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Observation 04eebfef-7228-4d07-939a-dd3af0fcac2e · outbound

This paper cites Zip-nerf: Anti-aliased grid-based neural radiance fields.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Zip-nerf: Anti-aliased grid-based neural radiance fields

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.715424Z

Source-reported events for the cited work

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Observation 2c9ece44-77e3-4d28-99c8-0fc30cdc1e6c · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting nuscenes: A multimodal dataset for autonomous driving

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.619284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6ea9eb9-81e6-42da-9cea-15fa157f8390 · outbound

This paper cites Tensorf: Tensorial radiance fields.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Tensorf: Tensorial radiance fields

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.686170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6d0bdbe3-473f-4fb9-8533-429693d7e3fc · outbound

This paper cites Periodic vibration gaussian: Dynamic urban scene reconstruction and real-time rendering.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Periodic vibration gaussian: Dynamic urban scene reconstruction and real-time rendering

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.672433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0aacbcd0-1bba-4943-b0ac-1236f2f29cd3 · outbound

This paper cites Neurbf: A neural fields representation with adaptive radial basis functions.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Neurbf: A neural fields representation with adaptive radial basis functions

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.658426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2ca27911-a6bf-4765-920f-a11763981200 · outbound

This paper cites Mobilenerf: Exploiting the polygon rasterization pipeline for efficient neural field rendering on mobile architectures.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Mobilenerf: Exploiting the polygon rasterization pipeline for efficient neural field rendering on mobile architectures

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.645074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b26ada13-c2f0-4a16-bb8b-9aec4e1f8981 · outbound

This paper cites Carla: An open urban driving simulator.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Carla: An open urban driving simulator

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.651287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4783fc41-0cd2-43fc-9e23-dbcac921a865 · outbound

This paper cites A point set generation network for 3d object reconstruction from a single image.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting A point set generation network for 3d object reconstruction from a single image

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.620616Z

Source-reported events for the cited work

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Observation 40f01c06-d0ff-4309-9d28-493a6363397e · outbound

This paper cites Fast dynamic radiance fields with time-aware neural voxels.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Fast dynamic radiance fields with time-aware neural voxels

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.603227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation acdf7e4e-8c98-4474-9d26-abeb1681f097 · outbound

This paper cites Plenoxels: Radiance fields without neural networks.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Plenoxels: Radiance fields without neural networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.576847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 942ab780-561d-48b9-bcf4-5389f637a214 · outbound

This paper cites K-planes: Explicit radiance fields in space, time, and appearance.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting K-planes: Explicit radiance fields in space, time, and appearance

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.563986Z

Source-reported events for the cited work

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Observation 66d01842-965d-4e1e-9fc2-95fe473c87fb · outbound

This paper cites Relightable 3d gaussian: Real-time point cloud relighting with brdf decomposition and ray tracing.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Relightable 3d gaussian: Real-time point cloud relighting with brdf decomposition and ray tracing

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.550400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 599ebb24-a247-43fe-be50-749cd89e5caa · outbound

This paper cites Learning to simulate realistic lidars.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Learning to simulate realistic lidars

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.535717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 83e752ef-3b09-460b-b445-9f05aff073f3 · outbound

This paper cites Baking neural radiance fields for real-time view synthesis.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Baking neural radiance fields for real-time view synthesis

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.519559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6800b636-8cd9-4615-bedf-091fef268d4c · outbound

This paper cites Tri-miprf: Tri-mip representation for efficient anti-aliasing neural radiance fields.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Tri-miprf: Tri-mip representation for efficient anti-aliasing neural radiance fields

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.503306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b462100c-4924-4784-be3f-8545bb1e4b77 · outbound

This paper cites 2d gaussian splatting for geometrically accurate radiance fields.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting 2d gaussian splatting for geometrically accurate radiance fields

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.482494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 79f35050-af8d-4f6b-a9e4-58b8fe0ded17 · outbound

This paper cites Neural kernel surface reconstruction.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Neural kernel surface reconstruction

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.467692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7455d125-f905-4e3a-bbb4-ce5c88d770ae · outbound

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

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting 3d gaussian splatting for real-time radiance field rendering

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.451009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 11d1ce0e-93e3-4e5e-bd21-55a4506434ba · outbound

This paper cites Design and use paradigms for gazebo, an open-source multi-robot simulator.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Design and use paradigms for gazebo, an open-source multi-robot simulator

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.712470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4da9b7f1-2d72-476f-8007-fc5a28c4d829 · outbound

This paper cites Pcgen: Point cloud generator for lidar simulation.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Pcgen: Point cloud generator for lidar simulation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.427339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 02413598-abb9-4934-8f92-45d93c84a8f6 · outbound

This paper cites Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.412584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fd644127-320f-4a6e-afc0-fd2be69d439a · outbound

This paper cites Neural sparse voxel fields.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Neural sparse voxel fields

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.395564Z

Source-reported events for the cited work

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Observation 8fb579fa-6630-4de4-85a4-8a5db12e6706 · outbound

This paper cites Lidarsim: Realistic lidar simulation by leveraging the real world.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Lidarsim: Realistic lidar simulation by leveraging the real world

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.379433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation da7a8982-dcab-419d-9427-1ba3b3e2e6dc · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Nerf: Representing scenes as neural radiance fields for view synthesis

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.735493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13cf723d-0dff-4cee-9619-e37ca1c648bd · outbound

This paper cites Instant neural graphics primitives with a multiresolution hash encoding.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Instant neural graphics primitives with a multiresolution hash encoding

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.354866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 28cbcf2b-4652-41c7-bbbd-976025c925f6 · outbound

This paper cites D-nerf: Neural radiance fields for dynamic scenes.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting D-nerf: Neural radiance fields for dynamic scenes

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.745381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97212a7c-9188-4318-a141-e7ffa0355857 · outbound

This paper cites Kilonerf: Speeding up neural radiance fields with thousands of tiny mlps.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Kilonerf: Speeding up neural radiance fields with thousands of tiny mlps

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.331645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2706309e-a5e8-44ad-ace2-0f734a00c5b5 · outbound

This paper cites Merf: Memory-efficient radiance fields for real-time view synthesis in unbounded scenes.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Merf: Memory-efficient radiance fields for real-time view synthesis in unbounded scenes

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.318723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c5407095-bd1c-482f-bc53-7d3c00d2810a · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting U-net: Convolutional networks for biomedical image segmentation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.764469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d39762e7-4134-48b0-9b2d-d53a4e105dd1 · outbound

This paper cites Airsim: High-fidelity visual and physical simulation for autonomous vehicles.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Airsim: High-fidelity visual and physical simulation for autonomous vehicles

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.769738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0df0f09d-9674-4665-829d-b67c4db9929e · outbound

This paper cites Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.288181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c20755be-e055-411c-9210-6b2ca6416ac6 · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Scalability in perception for autonomous driving: Waymo open dataset

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.781052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2bfeedb-410e-4590-9823-8a48bebd77cb · outbound

This paper cites Lidar-nerf: Novel lidar view synthesis via neural radiance fields.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Lidar-nerf: Novel lidar view synthesis via neural radiance fields

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.265930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4a4519f7-7e3b-4252-a41c-fdf9d7a65d36 · outbound

This paper cites Alignmif: Geometry-aligned multimodal implicit field for lidar-camera joint synthesis.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Alignmif: Geometry-aligned multimodal implicit field for lidar-camera joint synthesis

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.250439Z

Source-reported events for the cited work

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Observation db6d9903-361e-4b78-b306-20a251db920e · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Image quality assessment: from error visibility to structural similarity

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.803158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9a5e003-977e-4063-b1d9-56b8f4f08625 · outbound

This paper cites Dynamic lidar re-simulation using compositional neural fields.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Dynamic lidar re-simulation using compositional neural fields

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.228538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b2f415c6-8db2-40ae-827b-180438c8116f · outbound

This paper cites Physgaussian: Physics-integrated 3d gaussians for generative dynamics.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Physgaussian: Physics-integrated 3d gaussians for generative dynamics

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.216184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 27ce9fa4-21a9-4dcf-847f-c84805cefa44 · outbound

This paper cites S-nerf: Neural radiance fields for street views.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting S-nerf: Neural radiance fields for street views

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.204195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ae53df08-0af9-4b65-95ed-f4e8d622a0a9 · outbound

This paper cites Geonlf: Geometry guided pose-free neural lidar fields.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Geonlf: Geometry guided pose-free neural lidar fields

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.190868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 37fb7a6d-24fc-4e80-9dab-d6abf8955078 · outbound

This paper cites Street gaussians for modeling dynamic urban scenes.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Street gaussians for modeling dynamic urban scenes

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.841962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 843444ff-4908-436a-8bd3-f42c990198bf · outbound

This paper cites Emernerf: Emergent spatial-temporal scene decomposition via self-supervision.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Emernerf: Emergent spatial-temporal scene decomposition via self-supervision

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.165309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9511d75e-0657-4eb7-a3d8-c305716bfd26 · outbound

This paper cites Real-time photorealistic dynamic scene representation and rendering with 4d gaussian splatting.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Real-time photorealistic dynamic scene representation and rendering with 4d gaussian splatting

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.147269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f03e5925-76b7-4a94-a1a9-8091fe1e9834 · outbound

This paper cites Srinivasan, Richard Szeliski, Jonathan T.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Srinivasan, Richard Szeliski, Jonathan T

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.133003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 48b9f62a-d93c-48ab-8d29-7bc1988e2fc3 · outbound

This paper cites PlenOctrees for real-time rendering of neural radiance fields.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting PlenOctrees for real-time rendering of neural radiance fields

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.115431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c328b626-9aad-4301-ad4e-5e6f6825b44f · outbound

This paper cites Nerf-lidar: Generating realistic lidar point clouds with neural radiance fields.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Nerf-lidar: Generating realistic lidar point clouds with neural radiance fields

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.094832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation abf2a99d-d1a1-4b30-b32e-eb8c64a33ff1 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting The unreasonable effectiveness of deep features as a perceptual metric

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.869244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95825ac6-9ff9-4ebf-8d65-8fe359705117 · outbound

This paper cites Lidar4d: Dynamic neural fields for novel space-time view lidar synthesis.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Lidar4d: Dynamic neural fields for novel space-time view lidar synthesis

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.067669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ef884511-e280-4ab5-b897-c04dd3b4899b · outbound

This paper cites Drivable 3d gaussian avatars.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Drivable 3d gaussian avatars

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:50:54.043607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f0a765b5-e04e-4ced-859e-aeffa5d38af9 · outbound

This paper cites @esa (Ref.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting @esa (Ref

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.882228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b707dcc6-6b0b-45e6-82bb-33e6d2503f8a · outbound

This paper cites an unresolved cited work.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Unresolved cited work

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:53.889108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f618dd7d-b6a3-457e-be5e-f721e79fe41d · outbound

This paper cites an unresolved cited work.

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting Unresolved cited work

Reference 54

Resolution: malformed identifier; no resolver link, observed 2026-08-10T16:50:53.896372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation a8b313ac-364a-49ee-8c4e-6494c2733e25 · inbound

OmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generation cites this paper.

OmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generation GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:22:50.668352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bf84ff5e-eac6-43b9-ad38-1372a00246a1 · inbound

Neural LiDAR Bundle Adjustment cites this paper.

Neural LiDAR Bundle Adjustment GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-11T21:13:20.089629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.