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Paper Citation Record · LEDGER

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation

As of 15 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2507.23683.

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

pith.paper-citation-record.v1
2507.23683 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:34:07.382158Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

38 of 38 outbound references displayed

  • verified exact0
  • verified fuzzy21
  • unresolved17
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bf26c437-b59d-461b-ad00-731ede0fc2f0 · outbound

This paper cites nuscenes: A multi- modal dataset for autonomous driving.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation nuscenes: A multi- modal dataset for autonomous driving

Reference 1

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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 2026-08-14T06:32:32.682623+00:00.

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Observation 17c6bd73-1bb2-4500-a976-2fa1b849ec0d · outbound

This paper cites End-to-end autonomous driving: Challenges and frontiers.IEEE Transactions on Pat- tern Analysis and Machine Intelligence, 2024.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation End-to-end autonomous driving: Challenges and frontiers.IEEE Transactions on Pat- tern Analysis and Machine Intelligence, 2024

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 44f9517a-0673-4218-81c6-382c63a575d3 · outbound

This paper cites MagicDrive: Street View Generation with Diverse 3D Geometry Control.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation MagicDrive: Street View Generation with Diverse 3D Geometry Control

Reference 3

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no resolver link, observed 2026-08-06T10:34:02.750825Z

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Observation f3dc2fff-6f5d-415e-b217-ccc8f1793fe9 · outbound

This paper cites Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability

Reference 4

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T10:34:02.866016Z digest=sha256:30d31960f6285a8f11eeb6bb5d412d38084c1481caf623071c965ebd50a57e3f

Observation 0d369dbf-5cc4-4ec9-a8f0-33320f1327f1 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.Advances in neural information processing systems, 30, 2017.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Gans trained by a two time-scale update rule converge to a local nash equilib- rium.Advances in neural information processing systems, 30, 2017

Reference 5

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no resolver link, observed 2026-08-06T10:34:03.022783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:03.022783Z digest=sha256:3a832752fbab88b8602e0c4794b3591fd52b9e2cd1055952fb59857480df4a19

Observation b7bd80b3-f275-4308-997f-9c0b0ec629c7 · outbound

This paper cites GAIA-1: A Generative World Model for Autonomous Driving.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation GAIA-1: A Generative World Model for Autonomous Driving

Reference 6

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:03.109780Z digest=sha256:8c6112728dfe1fd554ed06a62f5e1b46f708f98cb5e0665dd8c5f33207027afe

Observation d7e4f95a-933d-4e7f-b77c-c94f1cb55497 · outbound

This paper cites St-p3: End-to-end vision-based au- tonomous driving via spatial-temporal feature learning.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation St-p3: End-to-end vision-based au- tonomous driving via spatial-temporal feature learning

Reference 7

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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 2026-08-14T06:32:32.682623+00:00.

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Observation fc0a0e70-811e-4873-9e32-32e510c127fa · outbound

This paper cites Planning-oriented autonomous driving.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Planning-oriented autonomous driving

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-06T10:34:12.938468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:03.390152Z digest=sha256:3c8198ae1fac14f299f4ff839783b8b043869d035a91b6ed6c9cc54f45fc03b0

Observation 344e2d22-5021-4154-96fd-4d3196bdfc18 · outbound

This paper cites $\textit{S}^3$Gaussian: Self-Supervised Street Gaussians for Autonomous Driving.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation $\textit{S}^3$Gaussian: Self-Supervised Street Gaussians for Autonomous Driving

Reference 9

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:03.538958Z digest=sha256:9750ca676a4547ae4871916ca15ddb6e13d51a100cf54336afcfcdebf0ed39fe

Observation dbe9354d-4453-449b-a3ec-6805ee7aeade · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics, 42 (4), 2023.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation 3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics, 42 (4), 2023

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:03.696508Z digest=sha256:795ad66b794ef1d8479d3c3397c2e2f3cc199b479dbc8a127f3c73b07fcc3c18

Observation a46940ac-d40c-4f1f-adb0-c4cdffaa2a6e · outbound

This paper cites Adam: A Method for Stochastic Optimization.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Adam: A Method for Stochastic Optimization

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:03.829387Z digest=sha256:8cdd6f862bcb2c4dc7711753b65cbf32db7c6074e640e71f55a1152dec16035a

Observation d833571b-4e1b-470f-950c-582c8e85c82d · outbound

This paper cites Dngaussian: Optimizing sparse-view 3d gaussian radiance fields with global-local depth normaliza- tion.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Dngaussian: Optimizing sparse-view 3d gaussian radiance fields with global-local depth normaliza- tion

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:12.467419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:03.984304Z digest=sha256:1eae8b64f628fa681d06972e4169d8628c72aa450607196cd4b3e5f82d9b0b4b

Observation e5ba0fed-ee3f-47e4-9a9b-979eca6c210f · outbound

This paper cites Learning distilled collaboration graph for multi-agent perception.Advances in Neural Infor- mation Processing Systems, 34:29541–29552, 2021.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Learning distilled collaboration graph for multi-agent perception.Advances in Neural Infor- mation Processing Systems, 34:29541–29552, 2021

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:12.264568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:04.140223Z digest=sha256:a12895ea21fbc121988da97d2f1bf093714b5bc14a6b3c85dbf69a06d699b1d7

Observation 00b74dc2-88d0-48db-ada1-6fd904d402b3 · outbound

This paper cites A survey on autonomous driving datasets: Statistics, annotation quality, and a future outlook.IEEE Transactions on Intelligent Vehicles, 2024.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation A survey on autonomous driving datasets: Statistics, annotation quality, and a future outlook.IEEE Transactions on Intelligent Vehicles, 2024

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:04.269717Z digest=sha256:3395d253d91854e15507120053f86bcf5201e2828040615a172e50ccd2ff09be

Observation 4103d6e2-601d-490f-bfca-09ee06693c98 · outbound

This paper cites Deceptive-nerf/3dgs: Diffusion- generated pseudo-observations for high-quality sparse-view reconstruction.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Deceptive-nerf/3dgs: Diffusion- generated pseudo-observations for high-quality sparse-view reconstruction

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:11.989721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:04.372294Z digest=sha256:9723ffdcd836808912bb9e926910c0ccce5dc1f122fd68b73706faee64cc11f7

Observation 537a776d-7375-4b01-a6f2-071c1a074577 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106, 2021.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106, 2021

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:04.526302Z digest=sha256:e72f15874565315cd8845aa58bfe2348e2bc94a50ad0de9759da4122812b217f

Observation 72d3a69b-48b4-453a-9473-b34be04cf5e7 · outbound

This paper cites ReconDreamer: Crafting World Models for Driving Scene Reconstruction via Online Restoration.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation ReconDreamer: Crafting World Models for Driving Scene Reconstruction via Online Restoration

Reference 17

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:04.667244Z digest=sha256:3d574f580c3f672a0d5230366d68f4986ef10bd67793888cbe586820227311e8

Observation 97955872-5234-4575-a245-52d0b1684d92 · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation DreamFusion: Text-to-3D using 2D Diffusion

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:04.784741Z digest=sha256:15c73e7df55d5d71d4c940e264b04dabe3d6a231a5ffeaaddf0b1e770a1fe502

Observation 7dab8224-4c47-4c83-96a5-9bf4520199dc · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation High-resolution image syn- thesis with latent diffusion models

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-06T10:34:11.742434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:04.915349Z digest=sha256:34acd1b6e78f51d6619664004b31c50fea528fe0558e64a8f2944168019d0509

Observation 92c13bdc-4bb8-4aeb-bec9-6e8581f5d0f3 · outbound

This paper cites an unresolved cited work.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Unresolved cited work

Reference 20

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:05.056649Z digest=sha256:5d7bd477ce25fa29cdb7389bcde85de69abac18716a37204bb1f4f3698d4e0bb

Observation f00dd72d-afcc-43a0-97ba-4de8c46289e5 · outbound

This paper cites Scalability in per- ception for autonomous driving: Waymo open dataset.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Scalability in per- ception for autonomous driving: Waymo open dataset

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:11.142180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:05.182191Z digest=sha256:652fcbd6721d8876eecd28f00fd54d188c79bc23c6732078166f4d100f2bcc93

Observation a5c0cd52-121c-41c1-8ac7-8850fb4e680b · outbound

This paper cites Street- view image generation from a bird’s-eye view layout.IEEE Robotics and Automation Letters, 9(4):3578–3585, 2024.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Street- view image generation from a bird’s-eye view layout.IEEE Robotics and Automation Letters, 9(4):3578–3585, 2024

Reference 22

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raw_fallback, observed 2026-08-06T10:34:10.930078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:05.295929Z digest=sha256:38b4259ead5ccbc53c731e4d3f55f6b05a664528ef9b1fc8f1680400feed6850

Observation d222465d-9a14-4fb1-99a2-4d231c490ede · outbound

This paper cites Srinivasan, Jonathan T.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Srinivasan, Jonathan T

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-06T10:34:10.694423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:05.460137Z digest=sha256:263756c5fa9e57bb880696cbe46e85b6d526b0ea667fad7e43d22dc707dbb1ad

Observation fdc647a7-8144-493b-ba8e-d4b4767ab4a4 · outbound

This paper cites Zhang, Francesco Ferroni, and Deva Ramanan.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Zhang, Francesco Ferroni, and Deva Ramanan

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:10.365828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:05.610502Z digest=sha256:1f41b1d5aa6d685deb097ea5dadc8079a5876b2a3f65af0863136e73a0b0f871

Observation a1a46503-5a1c-419b-921d-69e7d498b200 · outbound

This paper cites Drivedreamer: Towards real-world- drive world models for autonomous driving.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Drivedreamer: Towards real-world- drive world models for autonomous driving

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:10.078005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:05.720310Z digest=sha256:f9a50bb6648830de20e7bd1bf996591a14f88e180dc7cfe411db8659e6e602dc

Observation 5b80a981-b1aa-4328-ac20-706aa8dd1265 · outbound

This paper cites Driving into the future: Multiview visual forecasting and planning with world model for au- tonomous driving.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Driving into the future: Multiview visual forecasting and planning with world model for au- tonomous driving

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:09.809098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:05.848692Z digest=sha256:35bf4811a6c7b9977322c7e89c4f189e6262919bbe724cf004a1f9dd3e383099

Observation b05eaa42-fb0d-4b26-8874-4ec3dcc3b0ab · outbound

This paper cites Privacy of autonomous vehicles: Risks, protection methods, and future directions.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Privacy of autonomous vehicles: Risks, protection methods, and future directions

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:09.492654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:05.950754Z digest=sha256:2d7edac0f7f42056d0b765b5765ffa01be867e9550b8e64ecd952fa92fd1917d

Observation 7e1a61c3-604c-457d-85cf-6560521f47b2 · outbound

This paper cites SparseGS: Sparse View Synthesis using 3D Gaussian Splatting.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation SparseGS: Sparse View Synthesis using 3D Gaussian Splatting

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T10:34:06.065695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:06.065695Z digest=sha256:83ba2c6a91e945077f4a0cda8d37d78ede5021b83cd1d92571c0a9a331800574

Observation 3e1d47cf-0a6b-4a39-8fa0-e3b846a54836 · outbound

This paper cites Street gaussians: Modeling dynamic urban scenes with gaussian splatting.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Street gaussians: Modeling dynamic urban scenes with gaussian splatting

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:09.213037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:06.160988Z digest=sha256:b6cdb609c5e3375684d1f403ba0472842096ec9042ef2947cced629f88f5914a

Observation fe265d01-e1c4-476b-9fc2-74471a9c5b6a · outbound

This paper cites StreetCrafter: Street View Synthesis with Controllable Video Diffusion Models.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation StreetCrafter: Street View Synthesis with Controllable Video Diffusion Models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T10:34:06.320554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:06.320554Z digest=sha256:03aa62f8ff62b7811576a29f32b69b59a1cd6326163b5b26e14cbee05e6cf1a9

Observation a3e67915-9bef-4d54-bbd6-93cda1122294 · outbound

This paper cites Generalized predictive model for autonomous driving.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Generalized predictive model for autonomous driving

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:08.922704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:06.473529Z digest=sha256:71c87ccd21d1dfc8d40acd6d018cd1a3d552b0332bb7000575df2bc13d0bcf34

Observation 5cf687fb-9312-4242-89fb-4f80ee96027c · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Depth anything: Unleashing the power of large-scale unlabeled data

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:08.626600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:06.614664Z digest=sha256:6f5e5ddf5dd5e229f29fbb74df673695d1b0ee8d8a8364557027a0a1d4565176

Observation 9e0d9b0d-d6e2-43b4-877e-0117206bcc88 · outbound

This paper cites Depth any- thing v2.Advances in Neural Information Processing Sys- tems, 37:21875–21911, 2024.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Depth any- thing v2.Advances in Neural Information Processing Sys- tems, 37:21875–21911, 2024

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T10:34:06.757207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:06.757207Z digest=sha256:7bffc558c842f237407408242de1e36ad75371730623f09a7b5693e90daf5319

Observation 5f16a775-f704-46d8-b250-f16e588ab5ca · outbound

This paper cites Driving View Synthesis on Free-form Trajectories with Generative Prior.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Driving View Synthesis on Free-form Trajectories with Generative Prior

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T10:34:06.894718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:06.894718Z digest=sha256:0277e2fe9d2fc0170df7516cf9d1e7a7a6c275004734f395d5ba504138bd4b2f

Observation 09faccfe-d537-4246-8c0a-77dd8f0af8b7 · outbound

This paper cites Dair-v2x: A large-scale dataset for vehicle-infrastructure cooperative 3d object detection.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Dair-v2x: A large-scale dataset for vehicle-infrastructure cooperative 3d object detection

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:08.391288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:07.027057Z digest=sha256:60a5368a9cde1a126ee7fd7ddb84d306dbb2ec8a8d0b4f6b327b8df31ffda198

Observation 541bd337-bbdd-464a-a6f0-aeb36453474d · outbound

This paper cites V2x-seq: A large-scale sequential dataset for vehicle-infrastructure cooperative perception and forecast- ing.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation V2x-seq: A large-scale sequential dataset for vehicle-infrastructure cooperative perception and forecast- ing

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:08.122316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:07.154375Z digest=sha256:98fb978d62c1a246dd2eca542678c16f430b94f77b3c37376c061156f2215197

Observation b7a41776-8d75-4bba-a626-eccb28774b1f · outbound

This paper cites DriveDreamer4D: World Models Are Effective Data Machines for 4D Driving Scene Representation.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation DriveDreamer4D: World Models Are Effective Data Machines for 4D Driving Scene Representation

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T10:34:07.266895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:34:07.266895Z digest=sha256:d6260fd30b3e4ff1bd7879ee4bca5865d290c7b4d020dbe7538c487369b297e7

Observation 4aebf429-fd6d-43dc-bedb-f1e5263fc9a4 · outbound

This paper cites Drivinggaussian: Composite gaussian splatting for surrounding dynamic au- tonomous driving scenes.

I2V-GS: Infrastructure-to-Vehicle View Transformation with Gaussian Splatting for Autonomous Driving Data Generation Drivinggaussian: Composite gaussian splatting for surrounding dynamic au- tonomous driving scenes

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:34:07.871646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T10:34:07.382158Z digest=sha256:cab77298f83f58c086c9f7ee8bd5fe977b4181ecb3a7351aaa80977f7369ea62

Pith citing papers

No inbound Pith citation observations are available.