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Paper Citation Record · LEDGER

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction

As of 8 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2506.05563.

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

pith.paper-citation-record.v1
2506.05563 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:20:52.351495Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

62 of 62 outbound references displayed

  • verified exact5
  • verified fuzzy28
  • unresolved29
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d93c4a20-1e34-44aa-acdd-41b95c93da8a · outbound

This paper cites Per-Gaussian Embedding-Based Deformation for Deformable 3D Gaussian Splatting.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Per-Gaussian Embedding-Based Deformation for Deformable 3D Gaussian Splatting

Reference 1

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Observation 091d0cfb-87e4-41c9-a4b7-d93c05c3ac12 · outbound

This paper cites The lov´asz-softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction The lov´asz-softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation dc645a00-2483-42d9-ae48-893ab653cda8 · outbound

This paper cites A generalization of algebraic surface draw- ing.ACM transactions on graphics (TOG), 1(3):235–256,.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction A generalization of algebraic surface draw- ing.ACM transactions on graphics (TOG), 1(3):235–256,

Reference 3

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation e1d8ef8b-2ce8-445c-ad73-9aa75a1cea0c · outbound

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

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction nuscenes: A multi- modal dataset for autonomous driving

Reference 4

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raw_fallback, observed 2026-08-07T10:20:53.396040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.074523Z digest=sha256:7fb214411d594eb0590de91d7699854ba04c2638febd4054ef97d002884ea116

Observation 2ea6885c-a2f4-45ac-8cd0-571d1508cb79 · outbound

This paper cites OmniRe: Omni Urban Scene Reconstruction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction OmniRe: Omni Urban Scene Reconstruction

Reference 5

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source=pdf_text observed=2026-08-07T10:20:52.079714Z digest=sha256:c093296918c9d143bc9b3a21bd155e2d9f49db2c1e5aae19be93f53c5d0a4621

Observation 36bf602e-e724-4ac9-8b0b-991fb8c470a8 · outbound

This paper cites DreamScene4D: Dynamic Multi-Object Scene Generation from Monocular Videos.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction DreamScene4D: Dynamic Multi-Object Scene Generation from Monocular Videos

Reference 6

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source=pdf_text observed=2026-08-07T10:20:52.085571Z digest=sha256:b82ecf008a11285258f1c7de1fa793c2147a22475b492a883c5ca4a5563f8be1

Observation 8800d749-cce6-4009-a2cb-cd731cf10408 · outbound

This paper cites 4D-Rotor Gaussian Splatting: Towards Efficient Novel View Synthesis for Dynamic Scenes.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction 4D-Rotor Gaussian Splatting: Towards Efficient Novel View Synthesis for Dynamic Scenes

Reference 7

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source=pdf_text observed=2026-08-07T10:20:52.091191Z digest=sha256:9dddcb7bc303c3abeced7ce81e1fb067761bb93dfbbba6e062fee87e59326ff0

Observation 19ebbff0-4f6d-4011-8eef-1a728040859f · outbound

This paper cites A New Split Algorithm for 3D Gaussian Splatting.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction A New Split Algorithm for 3D Gaussian Splatting

Reference 8

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verified exact
local_arxiv, observed 2026-08-07T10:20:52.922274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ed600e61-57b8-42a3-a8e3-b5e9b046445f · outbound

This paper cites GaussianOcc: Fully Self-supervised and Efficient 3D Occupancy Estimation with Gaussian Splatting.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction GaussianOcc: Fully Self-supervised and Efficient 3D Occupancy Estimation with Gaussian Splatting

Reference 9

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source=pdf_text observed=2026-08-07T10:20:52.102301Z digest=sha256:09a1294637a752576d27f5211df20790daaa158fbe85cbd6a8ee5e1aa5b35d69

Observation 2fed5bb2-d8f9-430c-aa94-70537496d159 · outbound

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

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction GaussianFlow: Splatting Gaussian Dynamics for 4D Content Creation

Reference 10

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source=pdf_text observed=2026-08-07T10:20:52.107253Z digest=sha256:1e64080c0541293e3d9fc83fd13098911d521ab87da5984c9f1ee709459c4119

Observation 3a6dc39b-ec23-471c-b528-e759a702c66f · outbound

This paper cites Motion-aware 3D Gaussian Splatting for Efficient Dynamic Scene Reconstruction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Motion-aware 3D Gaussian Splatting for Efficient Dynamic Scene Reconstruction

Reference 11

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source=pdf_text observed=2026-08-07T10:20:52.112470Z digest=sha256:05a3ee0976d90394a4eb692f41e179fc8c1a97b66294632a7d24b622cfb6f1f6

Observation 4b11170d-9f38-48c9-8e54-8300c4fa15ef · outbound

This paper cites BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View

Reference 12

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source=pdf_text observed=2026-08-07T10:20:52.117554Z digest=sha256:11892b3da37e95a261fa170070ed5e00abffe0ceb4f7034ae3480b0c128e6eda

Observation 0e082408-7fb4-4556-be4c-b233da1d2a3e · outbound

This paper cites SelfOcc: Self-Supervised Vision-Based 3D Occupancy Prediction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction SelfOcc: Self-Supervised Vision-Based 3D Occupancy Prediction

Reference 13

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source=pdf_text observed=2026-08-07T10:20:52.122381Z digest=sha256:9ab09f84e0860419632d3bb85e1dbaa7299a28bd93337752527459500b896d48

Observation 8a0fbcd1-e12b-4561-b4d7-10b07ef851ab · outbound

This paper cites Tri-perspective view for vision-based 3d se- mantic occupancy prediction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Tri-perspective view for vision-based 3d se- mantic occupancy prediction

Reference 14

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source=pdf_text observed=2026-08-07T10:20:52.126878Z digest=sha256:2d65fa64ad730dfb9e37eed83ae4bc5f1c495259d234f6784a8304420e9f493b

Observation 81efdd03-0540-4267-8b3d-79fb18129223 · outbound

This paper cites GaussianFormer: Scene as Gaussians for Vision-Based 3D Semantic Occupancy Prediction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction GaussianFormer: Scene as Gaussians for Vision-Based 3D Semantic Occupancy Prediction

Reference 15

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source=pdf_text observed=2026-08-07T10:20:52.131978Z digest=sha256:85d82b3d72c55bc6d32dfc573aedfecb9942a0c33bccec42e45afeba456b64d7

Observation 0addbf7e-dea2-448f-bc49-572e3b428bf7 · outbound

This paper cites Sc-gs: Sparse-controlled gaussian splatting for editable dynamic scenes.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Sc-gs: Sparse-controlled gaussian splatting for editable dynamic scenes

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b3c332ff-19c8-4447-9ddc-0ca65223ac03 · outbound

This paper cites A compact dynamic 3d gaussian representation for real-time dynamic view synthesis.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction A compact dynamic 3d gaussian representation for real-time dynamic view synthesis

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.141299Z digest=sha256:2da47369c7b983bb56c3f53ce79ae5a2f2378da92c9e4d080dd37aa1f9fb7890

Observation b74281c0-da30-4375-b33e-497a0d84cbd3 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.ACM TOG, 42(4):1–14, 2023.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction 3d gaussian splatting for real-time radiance field rendering.ACM TOG, 42(4):1–14, 2023

Reference 18

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 8b646a5b-57c2-4136-8afd-11fe80434cf1 · outbound

This paper cites DGD: Dynamic 3D Gaussians Distillation.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction DGD: Dynamic 3D Gaussians Distillation

Reference 19

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local_arxiv, observed 2026-08-07T10:20:52.813572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.150339Z digest=sha256:6f227f6765a4ee11e5a73ba4e7b97031bdb588e5f958d57f05d9ccf41e16bad7

Observation 5c3527da-4227-4aac-b687-d117b1efab14 · outbound

This paper cites Fully Explicit Dynamic Gaussian Splatting.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Fully Explicit Dynamic Gaussian Splatting

Reference 20

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verified exact
local_arxiv, observed 2026-08-07T10:20:52.792035Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 0dffbffd-2608-4f05-b883-bcc17fa823e9 · outbound

This paper cites V oxformer: Sparse voxel transformer for camera- based 3d semantic scene completion.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction V oxformer: Sparse voxel transformer for camera- based 3d semantic scene completion

Reference 21

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Observation b46d9f21-2197-4e8b-a7d8-14c09b0dac69 · outbound

This paper cites Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers

Reference 22

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 230c32d2-95e1-4b97-a517-ddc24728e3d8 · outbound

This paper cites 2, 3, 4, 5, 6.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction 2, 3, 4, 5, 6

Reference 23

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.169633Z digest=sha256:b6954254faeaafd34154f78257445b6f563ded63e5d49dcb105e7dd2af06db7b

Observation 3e043df6-c106-4406-bf3a-35c98a9ac64c · outbound

This paper cites FB-OCC: 3D Occupancy Prediction based on Forward-Backward View Transformation.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction FB-OCC: 3D Occupancy Prediction based on Forward-Backward View Transformation

Reference 24

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source=pdf_text observed=2026-08-07T10:20:52.174934Z digest=sha256:3786034d5d8062f92bf633a58995939d76de6a6f3883aa4c194e7ff4a0770977

Observation a45ef4f6-7c77-4be3-a343-59157b63dd41 · outbound

This paper cites Gaussian-flow: 4d reconstruction with dynamic 3d gaus- sian particle.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Gaussian-flow: 4d reconstruction with dynamic 3d gaus- sian particle

Reference 25

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source=pdf_text observed=2026-08-07T10:20:52.179670Z digest=sha256:b63469df4337a465602b15f5c7698b2aea2da6937b3a7db23346f81b74a3aacf

Observation 390b93c2-4b4e-4f57-a4eb-cb4a14e51311 · outbound

This paper cites Fully Sparse 3D Occupancy Prediction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Fully Sparse 3D Occupancy Prediction

Reference 26

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source=pdf_text observed=2026-08-07T10:20:52.183845Z digest=sha256:a65f400a8c190bd4e17008024b7b180e278603283380acf3e5d8eb456c4f96a3

Observation dbf3cf00-087e-4328-acb2-61eb710cdf75 · outbound

This paper cites SurroundSDF: Implicit 3D Scene Understanding Based on Signed Distance Field.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction SurroundSDF: Implicit 3D Scene Understanding Based on Signed Distance Field

Reference 27

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verified exact
local_arxiv, observed 2026-08-07T10:20:52.740512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.188504Z digest=sha256:f0237e87bea2d9197bc9676ef0ce18f2075c5c0ff86fabfe6145eb370ac66d2e

Observation 9e9b880a-4a6c-417e-876c-1603c2ab5817 · outbound

This paper cites MoDGS: Dynamic Gaussian Splatting from Casually-captured Monocular Videos with Depth Priors.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction MoDGS: Dynamic Gaussian Splatting from Casually-captured Monocular Videos with Depth Priors

Reference 28

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source=pdf_text observed=2026-08-07T10:20:52.193434Z digest=sha256:762d8051c4d2770b4e017bc727b47ca181f14b21c48d0b9076539069e886db08

Observation 024169e0-603a-4547-9327-75d43aab5007 · outbound

This paper cites 3D Geometry-aware Deformable Gaussian Splatting for Dynamic View Synthesis.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction 3D Geometry-aware Deformable Gaussian Splatting for Dynamic View Synthesis

Reference 29

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source=pdf_text observed=2026-08-07T10:20:52.198477Z digest=sha256:b53e0488dac23cb8a2a69365d18c5467f3126513d1883378dc999b800fb784c8

Observation 71281112-01c9-4744-8a52-7d911b07d64c · outbound

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

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis

Reference 30

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source=pdf_text observed=2026-08-07T10:20:52.202972Z digest=sha256:013deb149406faf7483aefce5625696a42f1f173075119309055de26936ce144

Observation f2569273-739e-48d6-bc4d-1c0fd076e19f · outbound

This paper cites 3DGSR: Implicit Surface Reconstruction with 3D Gaussian Splatting.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction 3DGSR: Implicit Surface Reconstruction with 3D Gaussian Splatting

Reference 31

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source=pdf_text observed=2026-08-07T10:20:52.207799Z digest=sha256:3e5a7498b85dd2355fbc3e192bf2c7c6c616f1994bf8e5b7a62067b35b3a4ed4

Observation a08b18ef-efd3-4442-83c5-ea3803526a25 · outbound

This paper cites Cam4docc: Benchmark for camera-only 4d occupancy fore- casting in autonomous driving applications.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Cam4docc: Benchmark for camera-only 4d occupancy fore- casting in autonomous driving applications

Reference 32

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raw_fallback, observed 2026-08-07T10:20:53.271963Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ff207c1a-aca2-4346-ac22-4ce5f89c48b1 · outbound

This paper cites Cotr: Compact occupancy transformer for vision-based 3d occupancy prediction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Cotr: Compact occupancy transformer for vision-based 3d occupancy prediction

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.216779Z digest=sha256:95c382a56513faec2a275677908c26eed45469c130837da8a6cd7eab02e5358e

Observation a2bb5499-e2ae-4061-8f56-b46e9f72785f · outbound

This paper cites OccDepth: A Depth-Aware Method for 3D Semantic Scene Completion.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction OccDepth: A Depth-Aware Method for 3D Semantic Scene Completion

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:20:52.221201Z digest=sha256:3fdeb6e2677379c7f5d62638b23078a2ead02799de77a8ea54804846a087baa6

Observation d1519814-3fc4-41a7-be08-e54c99353001 · outbound

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

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106, 2021

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.243404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.225821Z digest=sha256:6c224419517b6420a772f013ea712b6804069bc8d20df7bee5074c9ee3a0d8f6

Observation d6ec70d9-b4c7-4217-9a7c-08311946de84 · outbound

This paper cites RenderOcc: Vision-Centric 3D Occupancy Prediction with 2D Rendering Supervision.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction RenderOcc: Vision-Centric 3D Occupancy Prediction with 2D Rendering Supervision

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T10:20:52.230384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:20:52.230384Z digest=sha256:1160a15a72a50f37636f96126317c12bac37a2deaf19f46cdae22b262fe67984

Observation 2f4055c3-e138-4a02-b19b-3453b1d160bb · outbound

This paper cites Learning occupancy for monocular 3d object detection.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Learning occupancy for monocular 3d object detection

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.228960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.235647Z digest=sha256:7ddf4828207a063437b513f5a1adeb31655a752da746f11bbc09ced58353a826

Observation b5aed746-e8af-4ed5-8309-08f128472a58 · outbound

This paper cites Scene as occupancy.Proceedings of the IEEE/CVF International Conference on Computer Vi- sion, 2023.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Scene as occupancy.Proceedings of the IEEE/CVF International Conference on Computer Vi- sion, 2023

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.214027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.239947Z digest=sha256:17f00e118fdb499018da0d1d0783acfed3fd5fda6df46b5111f1e06508fb0943

Observation b37316c3-9d0e-46b7-b7a2-01940368b0f0 · outbound

This paper cites Col- laborative semantic occupancy prediction with hybrid fea- ture fusion in connected automated vehicles.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Col- laborative semantic occupancy prediction with hybrid fea- ture fusion in connected automated vehicles

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.199887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.244225Z digest=sha256:26b6ac4ade3738a717e7f0b765e605b41cb9f2463dd6fedd88056ebe9b3a3202

Observation 5d37a20d-d221-4eca-9c4a-c74d519a5dfd · outbound

This paper cites DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T10:20:52.248655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:20:52.248655Z digest=sha256:30b0f1fc1c87cc64a52c4b64128d2faf72af9dc75700e57de74f5078a91d0648

Observation 10e39a01-97af-48b5-8f58-3bd7bbf36ecf · outbound

This paper cites Sparseocc: Re- thinking sparse latent representation for vision-based seman- tic occupancy prediction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Sparseocc: Re- thinking sparse latent representation for vision-based seman- tic occupancy prediction

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.184665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.253572Z digest=sha256:fad1604da4e48519676c686e316ae1e507217b3ada52ad5bba1eb9a56c5be839

Observation 4dcc899d-8f82-42fa-a872-d072c6216f93 · outbound

This paper cites Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving.NeurIPS, 36, 2024.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving.NeurIPS, 36, 2024

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.169233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.258721Z digest=sha256:89653e9b4cd979b594cc027dafb049ff4149d4fabf7a8f2f9a82414db798a462

Observation 022f889c-3c8b-479a-a016-f5927188a0f7 · outbound

This paper cites Scene as occupancy.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Scene as occupancy

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.154575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.263044Z digest=sha256:ea852013c9380a477823288ad71887615ebde93147976039bc8cc26d407d6c6b

Observation b6dbb402-7d71-4014-8701-e997057486ad · outbound

This paper cites Pop-3d: Open-vocabulary 3d occupancy prediction from im- ages.Advances in Neural Information Processing Systems, 36, 2024.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Pop-3d: Open-vocabulary 3d occupancy prediction from im- ages.Advances in Neural Information Processing Systems, 36, 2024

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.138586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.267558Z digest=sha256:8b18451d74eb2345d4f999d43f2ba7ee45c1092a3b17dd04391a46f8e1bc51c4

Observation 613aeaf4-ef2f-4477-bde4-6f2a56f98aae · outbound

This paper cites Openoccupancy: A large scale benchmark for sur- rounding semantic occupancy perception.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Openoccupancy: A large scale benchmark for sur- rounding semantic occupancy perception

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.122289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.271887Z digest=sha256:60355e9ec00fc0b64932e139ae263337848a098489413ba8da4af2551602cda0

Observation a0ab2c63-6807-44f5-9791-0affc4803b84 · outbound

This paper cites PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentation.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentation

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T10:20:52.276717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:20:52.276717Z digest=sha256:96b9599a146b31007ef392cad834d98089047db1add89ec6dd533edf9708a1f4

Observation a6eb541b-82b7-443a-a778-a26f86acc187 · outbound

This paper cites Omni-scene: omni- gaussian representation for ego-centric sparse-view scene re- construction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Omni-scene: omni- gaussian representation for ego-centric sparse-view scene re- construction

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.107893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.281742Z digest=sha256:6557ed1bc6fbcd6ec37a3bd0d974fbb7a5cbec0d4abba5335f3b5c2778ff07d4

Observation 137321da-22c0-4dec-8451-d3c3f551db84 · outbound

This paper cites Surroundocc: Multi-camera 3d occu- pancy prediction for autonomous driving.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Surroundocc: Multi-camera 3d occu- pancy prediction for autonomous driving

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.092453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.286162Z digest=sha256:c0dd060e901e57b44e02ce35544df9c3275d289354da0717a47d53cbe8ecb55f

Observation 2617980f-993a-49a2-8c6d-f6aa4dae7c04 · outbound

This paper cites Deep Height Decoupling for Precise Vision-based 3D Occupancy Prediction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Deep Height Decoupling for Precise Vision-based 3D Occupancy Prediction

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T10:20:52.290507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:20:52.290507Z digest=sha256:e9e58b871d6cb26f118baad6c88d9f7cc8cca36244ccae2375a391b74291828a

Observation 4ec4f8e6-b2ea-4970-9adf-450c52cb2196 · outbound

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

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T10:20:52.295071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:20:52.295071Z digest=sha256:c8d3ed88e43e3c1caa45899052a2abdbc05972235f8be9e9ec7b27d16a095ce8

Observation bf1826f1-2516-44df-b820-719e834cc45c · outbound

This paper cites Rignet: Repetitive image guided network for depth completion.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Rignet: Repetitive image guided network for depth completion

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.076143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.300131Z digest=sha256:6295a8a285fa4ce3299f318c45634dfb6fabde154e612499cac677567f383271

Observation 0733840b-b25c-4e59-a272-8705fba624ed · outbound

This paper cites Tri- perspective view decomposition for geometry-aware depth completion.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Tri- perspective view decomposition for geometry-aware depth completion

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.058728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.304912Z digest=sha256:5387fa265b8fcb550ef9cc4a9eba05547e77fab37692b667c93910e03cad8e7f

Observation d4ea34f8-b359-4b77-8044-40276551b403 · outbound

This paper cites Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T10:20:52.309598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:20:52.309598Z digest=sha256:59d02e3a30b4fd64ba4596654d60bbcbcc77efb6c71edb130c0ee4a3d3e1f881

Observation 190d54b0-2116-4e0f-b27e-7f473249ab08 · outbound

This paper cites GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Models.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Models

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T10:20:52.314290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:20:52.314290Z digest=sha256:b8b2433cbf34f94685c2ef1287a4492c5ed955b22bfca0fea57c1b29ea5fc07e

Observation d5f41c24-39f0-49ab-8957-67e929ef010d · outbound

This paper cites FlashOcc: Fast and Memory-Efficient Occupancy Prediction via Channel-to-Height Plugin.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction FlashOcc: Fast and Memory-Efficient Occupancy Prediction via Channel-to-Height Plugin

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T10:20:52.319123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:20:52.319123Z digest=sha256:bc586f91c0f08bc5311f10230f5e4dee280baa4f2d91f4e0a3218f63551645b3

Observation 1d08b255-c55f-4ff5-88e0-1ab3ed6824ef · outbound

This paper cites Occnerf: Self- supervised multi-camera occupancy prediction with neural radiance fields.arXiv e-prints, pages arXiv–2312, 2023.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Occnerf: Self- supervised multi-camera occupancy prediction with neural radiance fields.arXiv e-prints, pages arXiv–2312, 2023

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.043683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.323750Z digest=sha256:9086adba231a7abd90892c0f252320983555edbcc5898ed5da98fd4138df26e5

Observation 121e1236-9912-4d95-bc7d-72c7fbb99892 · outbound

This paper cites EgoGaussian: Dynamic Scene Understanding from Egocentric Video with 3D Gaussian Splatting.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction EgoGaussian: Dynamic Scene Understanding from Egocentric Video with 3D Gaussian Splatting

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T10:20:52.328047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:20:52.328047Z digest=sha256:d70031cf8dc0df6b30ef93935f1b4a36da4e41d11c84f4347aa4564404bed724

Observation 6c5eb209-0b75-4dc1-ab35-554ea0dfb56b · outbound

This paper cites Occformer: Dual-path transformer for vision-based 3d semantic occu- pancy prediction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Occformer: Dual-path transformer for vision-based 3d semantic occu- pancy prediction

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.028467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.333328Z digest=sha256:ecfe653ba7b90dcf21e475a3ca416a21797f6eb896ec6461662c4bbb1698e2f2

Observation 3b2b6472-133a-44bc-a3bc-087ed35c830e · outbound

This paper cites TCLC-GS: Tightly Coupled LiDAR-Camera Gaussian Splatting for Autonomous Driving.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction TCLC-GS: Tightly Coupled LiDAR-Camera Gaussian Splatting for Autonomous Driving

Reference 59

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:20:52.411692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.337657Z digest=sha256:06089be09edb33ba253e32b252dc8eec16ddab85f40cc6f510d5a28733ec26b7

Observation e4311de4-969f-4ef9-9667-e02033b54160 · outbound

This paper cites Lowrankocc: Tensor decomposition and low-rank recovery for vision-based 3d semantic occupancy prediction.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Lowrankocc: Tensor decomposition and low-rank recovery for vision-based 3d semantic occupancy prediction

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:53.010924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.342430Z digest=sha256:74b3a7e58be181274b07fe0bc41d760c7210bb6cc361acab20087382de20c5e9

Observation 715f63e4-9d83-41ab-9ee5-46d16d64e9e7 · outbound

This paper cites Occworld: Learning a 3d occupancy world model for autonomous driving.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction Occworld: Learning a 3d occupancy world model for autonomous driving

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:52.995709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T10:20:52.346790Z digest=sha256:215248d6f9241b9c78e129de61676d9762b67e00b85a7193746e004d01690d59

Observation 9a167dc4-0c9f-4000-8dba-1757c06d8490 · outbound

This paper cites MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian Splatting.

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian Splatting

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T10:20:52.351495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:20:52.351495Z digest=sha256:5bea7734a74770caad868df886f755c2e48da5b05036f10e47cd8b0c831a05e0

Pith citing papers

No inbound Pith citation observations are available.