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Paper Citation Record · LEDGER

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

As of 21 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 16 inbound Pith citation observations for arXiv:2501.00602.

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

pith.paper-citation-record.v1
2501.00602 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:52:35.131720Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:58:27.330988Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:37:36.984858Z

Reference resolution

34 of 34 outbound references displayed

  • verified exact1
  • verified fuzzy6
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9fddf450-1f98-4f64-b3cf-be2acc611892 · outbound

This paper cites an unresolved cited work.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Unresolved cited work

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T22:52:35.106006Z digest=sha256:ab0e6cda835464c4ffaf6f94174aae8aa7d54aec21e79ecc5fefb64892b06c95

Observation 349a5767-489b-4f5f-8a53-ba18ee697e2e · outbound

This paper cites Vision Transformer Adapter for Dense Predictions.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Vision Transformer Adapter for Dense Predictions

Reference 3

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:34.973601Z digest=sha256:840510ec8d7b64a11f77513320cf575fb914493addfe0f297136c2e828ae29cb

Observation a6157781-f26c-40af-9752-cb1d0bcae2a4 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

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no resolver link, observed 2026-08-10T22:52:34.985266Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:34.985266Z digest=sha256:8ec9372ac46e503389805e58af3af73a9e57fda2e5aa1c55c4908fe9bfab6920

Observation 9b7afea3-86df-4b5a-9886-6e4d4f6b7f8c · outbound

This paper cites Dynamic 3D Gaussian Fields for Urban Areas.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Dynamic 3D Gaussian Fields for Urban Areas

Reference 6

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no resolver link, observed 2026-08-10T22:52:34.990409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:34.990409Z digest=sha256:8fef9d917d275d2be2e7a4fe82ab970147743d1f06ea7b21b5f4667cf1c53dc5

Observation 50eb7aef-2630-4416-b6ed-ff2dee21fd9e · outbound

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

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes $\textit{S}^3$Gaussian: Self-Supervised Street Gaussians for Autonomous Driving

Reference 8

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no resolver link, observed 2026-08-10T22:52:35.000819Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.000819Z digest=sha256:30c6734685e79920bcea63704d609982a1d1b4d404dd11564d9073c750df8fe1

Observation d068de79-9856-4bc1-9393-f867d7e7aaa4 · outbound

This paper cites CoTracker: It is Better to Track Together.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes CoTracker: It is Better to Track Together

Reference 9

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unresolved
no resolver link, observed 2026-08-10T22:52:35.005568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.005568Z digest=sha256:4cb39b00f72aed466a3a67a233719f616fd05c50b15eb93b0092edd27fde0a66

Observation 46c1735c-9cbe-420a-ae95-e5cbf19a8c83 · outbound

This paper cites DynMF: Neural Motion Factorization for Real-time Dynamic View Synthesis with 3D Gaussian Splatting.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes DynMF: Neural Motion Factorization for Real-time Dynamic View Synthesis with 3D Gaussian Splatting

Reference 10

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unresolved
no resolver link, observed 2026-08-10T22:52:35.010340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.010340Z digest=sha256:c7aaf8a99d068e7c019486044d40d58cd49a9a9f1bc83513f66dfd529e67e172

Observation 382cac80-91fb-4441-bebf-1d4b82189a70 · outbound

This paper cites MoSca: Dynamic Gaussian Fusion from Casual Videos via 4D Motion Scaffolds.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes MoSca: Dynamic Gaussian Fusion from Casual Videos via 4D Motion Scaffolds

Reference 11

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no resolver link, observed 2026-08-10T22:52:35.016387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.016387Z digest=sha256:c4ab80459502ddf2b2500f3d94099ca47aa28d301b9721e31c95cae9a683ab30

Observation 8298c630-4253-49c3-881f-e3ce32fe1680 · outbound

This paper cites Decoupled weight decay regularization.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Decoupled weight decay regularization

Reference 12

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no resolver link, observed 2026-08-10T22:52:35.021726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.021726Z digest=sha256:57e89454e61f62e1c48e5f0cef1fdcfce4d0f01d181b5c898619cd0d421f1f83

Observation 62ca5b91-0947-4be8-a580-c774fade6c2b · outbound

This paper cites HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.031746Z digest=sha256:5c8188bd45e9eb9a81ef503c82198e2d08209ac0b310b5c8ed2de469944d7bb5

Observation 442bcc6a-330e-4651-9656-f081563eec95 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 15

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source=pdf_text observed=2026-08-10T22:52:35.036788Z digest=sha256:7e6955264876d65fb3e64a7654cc5b08d15ec694b9cc78acbd9c6658d5991441

Observation 212fa050-3949-4693-b572-3ee4ad48a2d5 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 17

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.046474Z digest=sha256:6b528ecdf4582dee5b7edd42b641ea2e6d851d395856e928aec0d477663f7295

Observation f4e24a49-13ad-443c-826b-907dee2b4071 · outbound

This paper cites latentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstruction.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes latentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstruction

Reference 19

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.056010Z digest=sha256:a3008922c99cecfd9414d99f2fc28b099b252d4d47a728d93b8093838b289e5d

Observation 05bb084f-0371-4a1e-93b4-82e4458923d7 · outbound

This paper cites Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.061065Z digest=sha256:6f766b96ea25d985e857b17687f3c034e982630589cd3fb4f20851907d3028d2

Observation 53b4a700-508a-49d2-9353-e2f9ab905b37 · outbound

This paper cites S-NeRF: Neural Radiance Fields for Street Views.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes S-NeRF: Neural Radiance Fields for Street Views

Reference 21

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no resolver link, observed 2026-08-10T22:52:35.065841Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.065841Z digest=sha256:65b08f5633d0b3d77e2b22d162af6bfeda51d73dbfc53fd14e1c02a19f5cd234

Observation 2dc46873-e7c1-44b7-9d28-8c09385aa41c · outbound

This paper cites GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.070316Z digest=sha256:e99f272e8ee1b2b615211df2e827ba90f622ef8b7e242511fcf8a414132c26a4

Observation a76cefac-4fdb-48c3-a583-fea31d82e735 · outbound

This paper cites Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting

Reference 23

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Observation f79b80f9-1f79-4032-abb4-3550464badad · outbound

This paper cites Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting

Reference 24

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source=pdf_text observed=2026-08-10T22:52:35.080747Z digest=sha256:f94c409617f6e0c851b99e80dc61d2e633342a8063414fd0f054f55244e56ed0

Observation ddd95258-af8b-490f-939b-47bc69a52dbc · outbound

This paper cites GS-LRM: Large Reconstruction Model for 3D Gaussian Splatting.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes GS-LRM: Large Reconstruction Model for 3D Gaussian Splatting

Reference 25

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Observation 1ce45b51-2db6-40e9-a112-fc59ccd4b684 · outbound

This paper cites Driv- inggaussian: Composite gaussian splatting for surrounding dynamic autonomous driving scenes.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Driv- inggaussian: Composite gaussian splatting for surrounding dynamic autonomous driving scenes

Reference 27

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raw_fallback, observed 2026-08-10T22:52:35.791453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T22:52:35.095733Z digest=sha256:836f6fbc280122ce1a61f8365589539339a55462f823ba99947e3d3d2ccff73f

Observation e400611c-d0a3-44eb-9d71-89a7da207944 · outbound

This paper cites For scale s, we compute s = min (exp(s′ − 2.3), 0.5), following Zhang et al.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes For scale s, we compute s = min (exp(s′ − 2.3), 0.5), following Zhang et al

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-10T22:52:35.774566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T22:52:35.101348Z digest=sha256:15bab9584acf05dd33eeba1c005c422161182bdc14fa912e7143465caacf5550

Observation 7eb3bca8-1691-4735-9028-6acb656fa79d · outbound

This paper cites Gradient checkpointing is enabled by default to reduce memory usage.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Gradient checkpointing is enabled by default to reduce memory usage

Reference 30

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raw_fallback, observed 2026-08-10T22:52:35.740718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T22:52:35.110606Z digest=sha256:9bcec0ef9916a7e02a11b47f3bfc4a941e4674ac4c101a72cf0dfcc01da2fa4a

Observation f1564a3a-01d3-45a4-92ba-ca2e60f8c9a2 · outbound

This paper cites However, LGM is originally trained on an object-centric synthetic dataset, which has a significant domain gap compared to our problem.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes However, LGM is originally trained on an object-centric synthetic dataset, which has a significant domain gap compared to our problem

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T22:52:35.120726Z digest=sha256:73cfd80490da21dae9c9b0c989a0882fdf5d0ba6e30e905a3f8fdf463303919e

Observation 80be3b4e-ae30-4d39-8e05-514c3a9a22c2 · outbound

This paper cites These scenes are divided into 700, 150, and 150 scenes for training, validation, and testing, respectively.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes These scenes are divided into 700, 150, and 150 scenes for training, validation, and testing, respectively

Reference 33

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raw_fallback, observed 2026-08-10T22:52:35.708643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 439fadcd-a56c-496b-a41b-84816f879905 · outbound

This paper cites Models are trained on the training set and evaluated on the validation set with unchanged hyperparameters.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Models are trained on the training set and evaluated on the validation set with unchanged hyperparameters

Reference 288

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verified fuzzy
raw_fallback, observed 2026-08-10T22:52:35.691533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T22:52:35.131720Z digest=sha256:7ee862fe94f5779626ea3f98d9893e449311eecb0235172df797a2b51d6723a3

Observation ae55abcb-dab0-4898-a02d-0287a009f4cd · outbound

This paper cites We setλlpips to 0.05, λsky to 0.1, and λreg to 5e-3 in all experiments.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes We setλlpips to 0.05, λsky to 0.1, and λreg to 5e-3 in all experiments

Reference 2014

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verified fuzzy
raw_fallback, observed 2026-08-10T22:52:35.724605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T22:52:35.115762Z digest=sha256:364cdbcce5a1ef48eac3bbb0ed037aa247302b6f06d3f34ac602e2b2ab52c1fa

Observation 221e7637-0faf-4881-abc4-aed3ddd16e94 · outbound

This paper cites DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features

Reference 2017

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metadata mismatch
local_arxiv, observed 2026-08-10T22:52:35.436038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T22:52:35.051106Z digest=sha256:101e1d6517db660de99a29abe587ba9851caa2029c23b9cd859c7a8d7d345e7d

Observation 9e18b390-ea0c-4cd3-bb87-e2d98eef103c · outbound

This paper cites Stereo Magnification: Learning View Synthesis using Multiplane Images.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Stereo Magnification: Learning View Synthesis using Multiplane Images

Reference 2018

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no resolver link, observed 2026-08-10T22:52:35.090618Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.090618Z digest=sha256:767d30bbeb93be3dac587caa297d9607d940d57da209ac2326f8cdb9218d3353

Observation f4a5df2d-1758-4347-b88b-6dc56869869f · outbound

This paper cites Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis

Reference 2019

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no resolver link, observed 2026-08-10T22:52:35.026747Z

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source=pdf_text observed=2026-08-10T22:52:35.026747Z digest=sha256:d9eed7184c2aaff188067ba789c9b58e0d946a43a7a5e46c0ce87504b70d60c5

Observation d088dfdc-95bb-4d86-b17e-570ad8ec1f6e · outbound

This paper cites Flash3D: Feed-Forward Generalisable 3D Scene Reconstruction from a Single Image.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Flash3D: Feed-Forward Generalisable 3D Scene Reconstruction from a Single Image

Reference 2020

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unresolved
no resolver link, observed 2026-08-10T22:52:35.041501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:35.041501Z digest=sha256:5d155795c02c1663b47634e1cf9fa453905baf2feeaa61a592942712afaa5c42

Observation 4f8f66a8-ff82-46de-adbe-3f0b1f69dbaa · outbound

This paper cites GaussianFlow: Splatting Gaussian Dynamics for 4D Content Creation.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes GaussianFlow: Splatting Gaussian Dynamics for 4D Content Creation

Reference 2021

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no resolver link, observed 2026-08-10T22:52:34.995443Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:34.995443Z digest=sha256:597775b5bb5cc652451cbb86c7dcec21218e028f3ff898c5b5284fda308bcaca

Observation e4ad19b5-ca7d-4673-8555-48ece5f4329d · outbound

This paper cites OmniRe: Omni Urban Scene Reconstruction.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes OmniRe: Omni Urban Scene Reconstruction

Reference 2022

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unresolved
no resolver link, observed 2026-08-10T22:52:34.978980Z

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source=pdf_text observed=2026-08-10T22:52:34.978980Z digest=sha256:4a8626f279d5db40d63495dade293d81740f874ec7d0b5b4246718bc177ad8d5

Observation 72bead73-b15f-4360-8ec7-33c096c7584a · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes ShapeNet: An Information-Rich 3D Model Repository

Reference 2023

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unresolved
no resolver link, observed 2026-08-10T22:52:34.961951Z

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source=pdf_text observed=2026-08-10T22:52:34.961951Z digest=sha256:2901b6428ac43321928123b5a91945ed0f2edcc7d5ccf285e881bea9c7158141

Observation 5de9b2e4-4943-4e64-8f78-ffe1799174fc · outbound

This paper cites Periodic Vibration Gaussian: Dynamic Urban Scene Reconstruction and Real-time Rendering.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Periodic Vibration Gaussian: Dynamic Urban Scene Reconstruction and Real-time Rendering

Reference 2024

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Pith citing papers

Observation ed0abced-609e-40cf-a27a-4c63540f2131 · inbound

E3D-Bench: A Benchmark for End-to-End 3D Geometric Foundation Models cites this paper.

E3D-Bench: A Benchmark for End-to-End 3D Geometric Foundation Models STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 79

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:36:09.882241Z digest=sha256:3f013bbdb46bd0517754a524ba7dc743afa229f402fb8600bb70d15b559fd8c0

Observation bf50373f-aaae-48c8-abc5-00066cc65857 · inbound

LSD-3D: Large-Scale 3D Driving Scene Generation with Geometry Grounding cites this paper.

LSD-3D: Large-Scale 3D Driving Scene Generation with Geometry Grounding STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 120

Resolution
unresolved
no resolver link, observed 2026-08-15T16:58:27.330988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:58:27.330988Z digest=sha256:d1c7fdfe7ba749ee95cb4faf51c3d731cf1775d2b4ce89c3a1587f18aac14358

Observation 2138d723-26a9-4643-a181-ebfe841b2440 · inbound

SimScale: Learning to Drive via Real-World Simulation at Scale cites this paper.

SimScale: Learning to Drive via Real-World Simulation at Scale STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 80

Resolution
verified exact
arxiv_id, observed 2026-05-17T04:34:01.833811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-17T04:33:03.629533Z digest=sha256:c33b6383d67d1dd98d09aea941b0cc7f109a2a507b98d3adcc95fd74a09c680b

Observation af34c8b4-b4ab-4428-bcc5-46fa56b61035 · inbound

Flux4D: Flow-based Unsupervised 4D Reconstruction cites this paper.

Flux4D: Flow-based Unsupervised 4D Reconstruction STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-17T02:01:25.713676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-17T01:59:16.251640Z digest=sha256:dfc1b378f8601b5c69bc6c57abf5b8a9b507d1d371b0d7fb8943d38eddc22e18

Observation 4307bcd8-2281-4233-92a0-41ccddbab1e1 · inbound

GaussianDWM: 3D Gaussian Driving World Model for Unified Scene Understanding and Multi-Modal Generation cites this paper.

GaussianDWM: 3D Gaussian Driving World Model for Unified Scene Understanding and Multi-Modal Generation STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-21T17:10:25.126719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-21T17:06:34.398973Z digest=sha256:c6a6f39fdfdc12b559ec13e7e839e5eeb377bd1deb007d455352974fa60ece8c

Observation 73085746-509e-443d-8514-647ad90cd47a · inbound

TokenGS: Decoupling 3D Gaussian Prediction from Pixels with Learnable Tokens cites this paper.

TokenGS: Decoupling 3D Gaussian Prediction from Pixels with Learnable Tokens STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:20:11.254521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T11:11:45.176020Z digest=sha256:00988c1349bac021465ad0c9af90f7202e734074e09ef3b2519d2086f462056e

Observation 69e3c750-4eb3-413a-8d9c-2981f7ead35b · inbound

EnerGS: Energy-Based Gaussian Splatting with Partial Geometric Priors cites this paper.

EnerGS: Energy-Based Gaussian Splatting with Partial Geometric Priors STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:46:24.483270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-07T13:59:39.519865Z digest=sha256:27faa51086277423310c726928ce2ffe88fb841c914432c8a1e791c9a8e33448

Observation 81ae7ef3-d7b8-415b-9299-a434e7a283ab · inbound

Ground4D: Spatially-Grounded Feedforward 4D Reconstruction for Unstructured Off-Road Scenes cites this paper.

Ground4D: Spatially-Grounded Feedforward 4D Reconstruction for Unstructured Off-Road Scenes STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:10:42.771591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-08T18:48:03.544248Z digest=sha256:486389d4013b97043d565befdb9adeab5e69d7b095c8d40aa276d790b7a1a733

Observation 8c2e6e2e-6c9c-4b99-99a0-c1530df33163 · inbound

ConFixGS: Learning to Fix Feedforward 3D Gaussian Splatting with Confidence-Aware Diffusion Priors in Driving Scenes cites this paper.

ConFixGS: Learning to Fix Feedforward 3D Gaussian Splatting with Confidence-Aware Diffusion Priors in Driving Scenes STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:16:25.875195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-12T03:35:41.359735Z digest=sha256:38604d44a253aacc3301c917e4b026758708d9b718159d67cd977108a27858e4

Observation f2cabcf6-c84f-4764-b6f5-fe076e1714c3 · inbound

PointForward: Feedforward Driving Reconstruction through Point-Aligned Representations cites this paper.

PointForward: Feedforward Driving Reconstruction through Point-Aligned Representations STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:27:02.697607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-13T01:22:05.111224Z digest=sha256:5c55a18fd2da1559ee5ea37b8490c472140cf20cc6b4f841c80166570d147830

Observation 735ab5fb-e522-44ca-ba7f-a92e4656cb75 · inbound

Xiaomi Auto World Model: A Joint World Model Integrating Reconstruction and Generation for Autonomous Driving cites this paper.

Xiaomi Auto World Model: A Joint World Model Integrating Reconstruction and Generation for Autonomous Driving STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-20T11:53:15.070222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-20T11:49:10.612194Z digest=sha256:eacd9959a730c3665667143769e628b58b74831abcc2d6f45e38dd71ea22646d

Observation 5ff45c24-9e05-4d38-8604-c3a9713abc1e · inbound

Xiaomi Auto World Model: A Joint World Model Integrating Reconstruction and Generation for Autonomous Driving cites this paper.

Xiaomi Auto World Model: A Joint World Model Integrating Reconstruction and Generation for Autonomous Driving STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-30T18:55:00.566392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T18:49:12.203495Z digest=sha256:a93e3a7f4107078e3de28f7c378e8aecb67da8c22494d5fd00c26dc3369237c1

Observation 1223e76e-4e60-48e6-b709-59e438826d85 · inbound

Envision4D: Envisioning Visual Futures via Feed-forward 4D Gaussian Splatting for Autonomous Driving cites this paper.

Envision4D: Envisioning Visual Futures via Feed-forward 4D Gaussian Splatting for Autonomous Driving STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-03T04:37:36.986572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T13:48:15.379724Z digest=sha256:f4cd4a1a315f56aab9c575255096a9175b83886869f3b17eaa97976b8692c002

Observation bd74ccf0-3471-47d2-88fb-479ac0270bd3 · inbound

L2D2-GS: Learning to Densify for Feedforward Dynamic Gaussian Scene Reconstruction cites this paper.

L2D2-GS: Learning to Densify for Feedforward Dynamic Gaussian Scene Reconstruction STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-06-30T07:14:20.771529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T07:12:54.953225Z digest=sha256:c3bf49cfdae805509404dfb034034ced385f48472cd3654d252c852ab5f3992c

Observation 0e7392b4-db60-4147-9efb-70f1975db9ca · inbound

FFAvatar: Feed-Forward 4D Head Avatar Reconstruction from Sparse Portrait Images cites this paper.

FFAvatar: Feed-Forward 4D Head Avatar Reconstruction from Sparse Portrait Images STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 67

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T06:34:19.028730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T06:29:52.152957Z digest=sha256:d3f72d3e6eec773de91166a7c43e060ee583c1fb3d2fd84ecb5b2d3c2acc0d23

Observation e15081ea-eb00-4e37-9054-f876035a9f42 · inbound

FFAvatar: Feed-Forward 4D Head Avatar Reconstruction from Sparse Portrait Images cites this paper.

FFAvatar: Feed-Forward 4D Head Avatar Reconstruction from Sparse Portrait Images STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes

Reference 67

Resolution
unresolved
no resolver link, observed 2026-07-15T10:23:19.970515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T10:23:19.970515Z digest=sha256:451732c5bd36923c8e95eb2205dde708a273673a52c2b3caf62035eff3b5575c