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Paper Citation Record · LEDGER

ODG: Occupancy Prediction Using Dual Gaussians

As of 9 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 2 inbound Pith citation observations for arXiv:2506.09417.

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

pith.paper-citation-record.v1
2506.09417 v2

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:53:44.121646Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T12:06:52.443736Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T12:34:39.615921Z

Reference resolution

61 of 61 outbound references displayed

  • verified exact0
  • verified fuzzy23
  • unresolved38
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 40f49503-43ee-4647-bf56-2c327dfb88fe · outbound

This paper cites Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields.

ODG: Occupancy Prediction Using Dual Gaussians Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields

Reference 1

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Observation 940f9916-7694-4673-a434-03b27a6d2cdd · outbound

This paper cites Mip-nerf 360: Unbounded anti-aliased neural radiance fields.

ODG: Occupancy Prediction Using Dual Gaussians Mip-nerf 360: Unbounded anti-aliased neural radiance fields

Reference 2

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Observation 7f41f373-46dc-4614-8403-c4c82dcb351c · outbound

This paper cites Semantickitti: A dataset for semantic scene understanding of lidar sequences.

ODG: Occupancy Prediction Using Dual Gaussians Semantickitti: A dataset for semantic scene understanding of lidar sequences

Reference 3

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Observation 355eb153-b3cd-44df-98bf-65b4384dee3d · outbound

This paper cites GaussianFlowOcc: Sparse and Weakly Supervised Occupancy Estimation using Gaussian Splatting and Temporal Flow.

ODG: Occupancy Prediction Using Dual Gaussians GaussianFlowOcc: Sparse and Weakly Supervised Occupancy Estimation using Gaussian Splatting and Temporal Flow

Reference 4

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Observation 9b606fd6-5449-407f-97dd-d2e0fc8cda6a · outbound

This paper cites Occflownet: Towards self-supervised occupancy estimation via differentiable rendering and occupancy flow.IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025.

ODG: Occupancy Prediction Using Dual Gaussians Occflownet: Towards self-supervised occupancy estimation via differentiable rendering and occupancy flow.IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025

Reference 5

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 29e0a8a4-086d-4725-9cf2-d9dd902bfc99 · outbound

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

ODG: Occupancy Prediction Using Dual Gaussians nuscenes: A multimodal dataset for autonomous driving

Reference 6

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Observation 9faab6c3-6c54-476c-a4b4-2553cbdad1a3 · outbound

This paper cites Monoscene: Monocular 3d semantic scene completion.

ODG: Occupancy Prediction Using Dual Gaussians Monoscene: Monocular 3d semantic scene completion

Reference 7

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Observation 6f16b0fc-e5d8-4318-afec-82263143758c · outbound

This paper cites Scenerf: Self-supervised monocular 3d scene reconstruction with radiance fields.

ODG: Occupancy Prediction Using Dual Gaussians Scenerf: Self-supervised monocular 3d scene reconstruction with radiance fields

Reference 8

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 6b2765e7-dc2c-429b-946e-6de9477aba0f · outbound

This paper cites End-to-end object detection with transformers.

ODG: Occupancy Prediction Using Dual Gaussians End-to-end object detection with transformers

Reference 9

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Observation be5870ef-3737-4f6e-9c23-2b292c316b0c · outbound

This paper cites GaussRender: Learning 3D Occupancy with Gaussian Rendering.

ODG: Occupancy Prediction Using Dual Gaussians GaussRender: Learning 3D Occupancy with Gaussian Rendering

Reference 10

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source=pdf_text observed=2026-08-07T04:53:38.536644Z digest=sha256:ef9c09ca7d740b9fedc67aaa4cdf86cecd4cbf929cc32cf9c1443517f36b5ce0

Observation 6fb7004e-64f1-44d7-bcc5-87a7e8281181 · outbound

This paper cites pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction.

ODG: Occupancy Prediction Using Dual Gaussians pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction

Reference 11

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Observation 7414bb0d-1c8f-4cd7-8808-5b30dc7e1e75 · outbound

This paper cites Mvsplat: Efficient 3d gaussian splatting from sparse multi-view images.

ODG: Occupancy Prediction Using Dual Gaussians Mvsplat: Efficient 3d gaussian splatting from sparse multi-view images

Reference 12

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Observation 8bc0fb9b-13e9-46a4-a585-189fff2d4c44 · outbound

This paper cites Openscene: The largest up-to-date 3d occupancy prediction benchmark in autonomous driving.https://github.com/OpenDriveLab/OpenScene, 2023.

ODG: Occupancy Prediction Using Dual Gaussians Openscene: The largest up-to-date 3d occupancy prediction benchmark in autonomous driving.https://github.com/OpenDriveLab/OpenScene, 2023

Reference 13

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 9f33712c-d3fc-4b63-a190-b4630d6769d3 · outbound

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

ODG: Occupancy Prediction Using Dual Gaussians An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 14

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Observation d06db756-d4a1-45b4-a938-42f2de2caaec · outbound

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

ODG: Occupancy Prediction Using Dual Gaussians A point set generation network for 3d object reconstruction from a single image

Reference 15

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Observation b216b5ab-f7c2-40a1-a1e8-e11db831fcd0 · outbound

This paper cites Vision meets robotics: The kitti dataset.The International Journal of Robotics Research, 32(11):1231–1237, 2013.

ODG: Occupancy Prediction Using Dual Gaussians Vision meets robotics: The kitti dataset.The International Journal of Robotics Research, 32(11):1231–1237, 2013

Reference 16

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Observation 314a1d35-62fd-4a52-b59a-f7bf211d701d · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

ODG: Occupancy Prediction Using Dual Gaussians Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 17

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Observation 37afc8e8-8deb-49c9-a32c-c771c6a84703 · outbound

This paper cites Sugar: Surface-aligned gaussian splatting for efficient 3d mesh reconstruction and high-quality mesh rendering.

ODG: Occupancy Prediction Using Dual Gaussians Sugar: Surface-aligned gaussian splatting for efficient 3d mesh reconstruction and high-quality mesh rendering

Reference 18

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Observation ef8d9a6e-8d5c-4429-a927-ed3a188d4648 · outbound

This paper cites Deep residual learning for image recognition.

ODG: Occupancy Prediction Using Dual Gaussians Deep residual learning for image recognition

Reference 19

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Observation 1b5af1ff-3896-441c-bf3f-a6d274163a5c · outbound

This paper cites Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation.

ODG: Occupancy Prediction Using Dual Gaussians Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation

Reference 20

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source=pdf_text observed=2026-08-07T04:53:39.547997Z digest=sha256:360b12268432fd7b6ed8b394995eb305fba25733bf56ad0d82ef1ee1bc6e8137

Observation 53245a00-da48-4cdb-b8ca-43472f1195d4 · outbound

This paper cites Planning-oriented autonomous driving.

ODG: Occupancy Prediction Using Dual Gaussians Planning-oriented autonomous driving

Reference 21

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Observation aa625d6d-b6ab-4dd7-ad38-41414b88c5a8 · outbound

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

ODG: Occupancy Prediction Using Dual Gaussians BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View

Reference 22

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Observation 9d01a344-2ad7-42c4-b4a8-10eb0c9b814b · outbound

This paper cites Selfocc: Self-supervised vision- based 3d occupancy prediction.

ODG: Occupancy Prediction Using Dual Gaussians Selfocc: Self-supervised vision- based 3d occupancy prediction

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:39.907750Z digest=sha256:6c77ff3a5e3ca524bbdbb7f380aaf200f0ed513327b71e5a21841295b1a0d242

Observation ad8c2593-1285-4ad6-8248-209dcd639267 · outbound

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

ODG: Occupancy Prediction Using Dual Gaussians Tri-perspective view for vision-based 3d semantic occupancy prediction

Reference 24

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Observation f0158d3b-b068-4bf3-8f4b-3dedb2480a12 · outbound

This paper cites Gaussianformer: Scene as gaussians for vision-based 3d semantic occupancy prediction.

ODG: Occupancy Prediction Using Dual Gaussians Gaussianformer: Scene as gaussians for vision-based 3d semantic occupancy prediction

Reference 25

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source=pdf_text observed=2026-08-07T04:53:40.067009Z digest=sha256:83b488c7cc19a0fde3a1dcc8ce987dbafd5ca906ca80a30c02c39b2533f7fe2a

Observation 07a55506-22da-41dd-9b4c-1e2002b15299 · outbound

This paper cites Gausstr: Foundation model-aligned gaussian transformer for self-supervised 3d spatial understanding.The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.

ODG: Occupancy Prediction Using Dual Gaussians Gausstr: Foundation model-aligned gaussian transformer for self-supervised 3d spatial understanding.The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025

Reference 26

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 720e896c-6c19-43b2-857d-2f79a90505af · outbound

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

ODG: Occupancy Prediction Using Dual Gaussians 3d gaussian splatting for real-time radiance field rendering.ACM Trans

Reference 27

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Observation d5fe0c2b-a835-4cf7-9234-5612d9556817 · outbound

This paper cites A hierarchical 3d gaussian representation for real-time rendering of very large datasets.ACM Transactions on Graphics (TOG), 43(4):1–15, 2024.

ODG: Occupancy Prediction Using Dual Gaussians A hierarchical 3d gaussian representation for real-time rendering of very large datasets.ACM Transactions on Graphics (TOG), 43(4):1–15, 2024

Reference 28

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source=pdf_text observed=2026-08-07T04:53:40.386304Z digest=sha256:c3a898c2da31b28f9ffe2c37b2956c93baa1774d2c00abdc53ef6c6120c71462

Observation 890b2283-9d12-4844-bf6b-96008764917a · outbound

This paper cites The hungarian method for the assignment problem.Naval research logistics quarterly, 2(1-2):83–97, 1955.

ODG: Occupancy Prediction Using Dual Gaussians The hungarian method for the assignment problem.Naval research logistics quarterly, 2(1-2):83–97, 1955

Reference 29

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source=pdf_text observed=2026-08-07T04:53:40.467445Z digest=sha256:b29cbb0fa9cf76ff2ce2db6e4b3bc0750495257bbed18fa97384e168bb30df67

Observation 0b2a4c9e-8a04-4c1c-8d56-fdcfa14f7121 · outbound

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

ODG: Occupancy Prediction Using Dual Gaussians Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal trans- formers

Reference 30

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:40.609015Z digest=sha256:51f8f4dccf17702b7fb4ac1f0ac52c265e44ef47bf89c53e4edd9968070ab70e

Observation ed35f4ce-d489-4ebf-9627-0c1fef16695b · outbound

This paper cites Focal loss for dense object detection.

ODG: Occupancy Prediction Using Dual Gaussians Focal loss for dense object detection

Reference 31

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source=pdf_text observed=2026-08-07T04:53:40.734056Z digest=sha256:9d0a5fc99457a4850abaecc8c723048de78226c68582cfe5d9c3518d2609f57e

Observation 7c0c6943-9885-4c54-ab2e-7cf52723a020 · outbound

This paper cites Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusion.

ODG: Occupancy Prediction Using Dual Gaussians Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusion

Reference 32

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source=pdf_text observed=2026-08-07T04:53:40.820967Z digest=sha256:767adced8eaa0067d3f5d5f3dd3bdfe7bab082e59d0c6a94f6f4615676a6dc64

Observation 434a7c82-4ecc-4eb1-a7c5-c9c34acf0cfd · outbound

This paper cites Sparsebev: High-performance sparse 3d object detection from multi-camera videos.

ODG: Occupancy Prediction Using Dual Gaussians Sparsebev: High-performance sparse 3d object detection from multi-camera videos

Reference 33

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source=pdf_text observed=2026-08-07T04:53:40.929017Z digest=sha256:9cd592e7dd184981ffb0340aaf6a2999907b6784ea5b3cd920cb56ad7e5ef9b3

Observation 1ebde421-4b8b-4f52-b78e-72058f061eb9 · outbound

This paper cites Fully sparse 3d panoptic occupancy prediction.

ODG: Occupancy Prediction Using Dual Gaussians Fully sparse 3d panoptic occupancy prediction

Reference 34

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:41.056983Z digest=sha256:e140c1b046258bcceff17704c0db8ea694f8d6366634e95a1c6c7c8d6132201a

Observation 58328bde-1f0b-4685-91bf-0937ea5da8a4 · outbound

This paper cites Let occ flow: Self-supervised 3d occupancy flow prediction.The Conference on Robot Learning (CoRL), 2024.

ODG: Occupancy Prediction Using Dual Gaussians Let occ flow: Self-supervised 3d occupancy flow prediction.The Conference on Robot Learning (CoRL), 2024

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:41.205040Z digest=sha256:b083fa485357ce6c430c9203bd16c02267ae885cc6598be8b5a55fbb80476637

Observation 58ebac23-2f61-49da-b947-6992daaf3f4f · outbound

This paper cites PETR: Position Embedding Transformation for Multi-View 3D Object Detection.

ODG: Occupancy Prediction Using Dual Gaussians PETR: Position Embedding Transformation for Multi-View 3D Object Detection

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:41.305810Z digest=sha256:6de7678fc668d9ad9ad2a27fe0f702b3ba05cee4591e23b620bcc8c1f4e2bd86

Observation 5a781dc0-1ecd-4dcb-8bde-2020c864b680 · outbound

This paper cites Decoupled Weight Decay Regularization.

ODG: Occupancy Prediction Using Dual Gaussians Decoupled Weight Decay Regularization

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:41.382194Z digest=sha256:59d8a198ec7ea15b4b15a033559b54d098d08c8f2225d4a9c612277eed00e929

Observation 5de3c552-ddb6-47ce-960e-a1e12e9c8c7d · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

ODG: Occupancy Prediction Using Dual Gaussians SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:41.540020Z digest=sha256:832a50aef8a083acf39f0d34e991e14177781e241c08585c56ff2406aa8fcdfa

Observation 4f8a3622-d5e4-45fb-b7ec-699e47a22db4 · outbound

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

ODG: Occupancy Prediction Using Dual Gaussians Nerf: Representing scenes as neural radiance fields for view synthesis.Communications of the ACM, 65(1):99–106, 2021

Reference 39

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no resolver link, observed 2026-08-07T04:53:41.623182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:41.623182Z digest=sha256:8486f1360743580a2cd7fb61e0f581bc8f36104522fead2e9c8ba361794a62f2

Observation 2ef283e6-799b-45eb-a37c-447d2a92ec70 · outbound

This paper cites Renderocc: Vision-centric 3d occupancy prediction with 2d rendering supervision.

ODG: Occupancy Prediction Using Dual Gaussians Renderocc: Vision-centric 3d occupancy prediction with 2d rendering supervision

Reference 40

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no resolver link, observed 2026-08-07T04:53:41.766920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:41.766920Z digest=sha256:f9725e59fcb297cceffa6df1869f8dc3c2620f37e72ec12778010bf51a1efb34

Observation d7d22171-541c-4004-bd6f-c6e83a80a7f1 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

ODG: Occupancy Prediction Using Dual Gaussians PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 41

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no resolver link, observed 2026-08-07T04:53:41.879815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:41.879815Z digest=sha256:63cad02bffcd8617a819b7a30824edf32fd3a161aab9c107f6eb38d9c1a9bb02

Observation 190c0891-f2ce-4fcb-ac52-446a3bbb0334 · outbound

This paper cites H3o: Hyper-efficient 3d occupancy prediction with heterogeneous supervision.IEEE International Conference on Robotics and Automation (ICRA), 2025.

ODG: Occupancy Prediction Using Dual Gaussians H3o: Hyper-efficient 3d occupancy prediction with heterogeneous supervision.IEEE International Conference on Robotics and Automation (ICRA), 2025

Reference 42

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raw_fallback, observed 2026-08-07T04:53:47.011788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:42.015046Z digest=sha256:5e30b1f9d5185b07cd27ddce1adb3584571e8ff6270fb25cfdc9543815accfee

Observation 667ac1c7-7100-4c7a-979d-df0b13d3d374 · outbound

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

ODG: Occupancy Prediction Using Dual Gaussians Scalability in perception for autonomous driving: Waymo open dataset

Reference 43

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no resolver link, observed 2026-08-07T04:53:42.145133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:42.145133Z digest=sha256:f2551f40b8bb884cacd4212b30bbae998004f714b8107c70138d60ebcdcd4902

Observation ade976a1-b3af-4d30-ab58-47fd7bbae8a3 · outbound

This paper cites Splatter image: Ultra-fast single-view 3d reconstruction.

ODG: Occupancy Prediction Using Dual Gaussians Splatter image: Ultra-fast single-view 3d reconstruction

Reference 44

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no resolver link, observed 2026-08-07T04:53:42.290793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:42.290793Z digest=sha256:3acad460c97375620765e4362653c7cdcf41e5c5a9d19b6032b45ad8b4fb1948

Observation 6c9db310-5e94-42e1-bb6c-b0b30c8a02dd · outbound

This paper cites Sparseocc: Rethinking sparse latent representation for vision-based semantic occupancy prediction.

ODG: Occupancy Prediction Using Dual Gaussians Sparseocc: Rethinking sparse latent representation for vision-based semantic occupancy prediction

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-07T04:53:46.729836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:42.405851Z digest=sha256:d7fbd74ed4bf1615d5376a135bf848a303ccd2bbd825adbbeb1089eebc34642c

Observation 2ed5738c-787c-4e17-ad70-73d89e1abc96 · outbound

This paper cites State of the art on neural rendering.

ODG: Occupancy Prediction Using Dual Gaussians State of the art on neural rendering

Reference 46

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verified fuzzy
raw_fallback, observed 2026-08-07T04:53:46.522041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:42.542054Z digest=sha256:224a070736dc56d2ca5e1ebf08e12fc6721faeb8f40607dd9e7d2baf6adc892b

Observation f971108d-dd14-40d0-95ff-1e98e659a06d · outbound

This paper cites Advances in neural rendering.

ODG: Occupancy Prediction Using Dual Gaussians Advances in neural rendering

Reference 47

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verified fuzzy
raw_fallback, observed 2026-08-07T04:53:46.279371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:42.676765Z digest=sha256:16c347214434f01d6314eb655e1a3eccf5d0bf9fcd7654abc88c4585f388b029

Observation a3d09ab0-cac2-4a21-92d6-fd87ef1c7788 · outbound

This paper cites Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving.Advances in Neural Information Processing Systems, 36, 2024.

ODG: Occupancy Prediction Using Dual Gaussians Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving.Advances in Neural Information Processing Systems, 36, 2024

Reference 48

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verified fuzzy
raw_fallback, observed 2026-08-07T04:53:46.002796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:42.807907Z digest=sha256:30988dff1d3814f9b5368ac0a7984fa00448c38c0c05ab67f82244a186ed8858

Observation 8026400c-4d88-40e2-a94e-e5f55b92e524 · outbound

This paper cites Scene as occupancy.

ODG: Occupancy Prediction Using Dual Gaussians Scene as occupancy

Reference 49

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no resolver link, observed 2026-08-07T04:53:42.892689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:42.892689Z digest=sha256:b79cb5d1aa3ae0eb260dc293b1ed785915a9a056584e5ec0dc0cffa0759a86c1

Observation 79182d03-7bd7-46d5-b773-9c2628cf4ba8 · outbound

This paper cites Attention is all you need.Advances in Neural Information Processing Systems, 2017.

ODG: Occupancy Prediction Using Dual Gaussians Attention is all you need.Advances in Neural Information Processing Systems, 2017

Reference 50

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:42.960531Z digest=sha256:4d981177981cb0604079c5d95236a03583a2acd88d22cb79e2844f7f6dbc8592

Observation 479c191b-1fd9-4011-aaa8-66027786ff0a · outbound

This paper cites Opus: Occupancy prediction using a sparse set.

ODG: Occupancy Prediction Using Dual Gaussians Opus: Occupancy prediction using a sparse set

Reference 51

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raw_fallback, observed 2026-08-07T04:53:45.762702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:43.077901Z digest=sha256:90d313c84eda87398f7479a2860396bb26dda4a64523b93ef0351ed292198665

Observation c9c4d971-a1b2-4614-871d-56e7eddca642 · outbound

This paper cites Exploring object-centric temporal modeling for efficient multi-view 3d object detection.

ODG: Occupancy Prediction Using Dual Gaussians Exploring object-centric temporal modeling for efficient multi-view 3d object detection

Reference 52

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:43.197794Z digest=sha256:ee5867d05dcb05c63c9a75dd14757ecc5666f04c559c8ccbb217f440d3908d4d

Observation d494615b-1bd8-4d88-b789-61508e5c5bff · outbound

This paper cites Openoccupancy: A large scale benchmark for surrounding semantic occupancy perception.

ODG: Occupancy Prediction Using Dual Gaussians Openoccupancy: A large scale benchmark for surrounding semantic occupancy perception

Reference 53

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verified fuzzy
raw_fallback, observed 2026-08-07T04:53:45.528523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:43.276283Z digest=sha256:a17c32f2de4fc4a4cbe5769fb0456396256dd19b3ae9a3c562349c2f077682f2

Observation 649f8c24-b674-4450-85d9-76a168fea20c · outbound

This paper cites Detr3d: 3d object detection from multi-view images via 3d-to-2d queries.

ODG: Occupancy Prediction Using Dual Gaussians Detr3d: 3d object detection from multi-view images via 3d-to-2d queries

Reference 54

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raw_fallback, observed 2026-08-07T04:53:45.348924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:43.369905Z digest=sha256:b9f48feda9c8e30bb1a9698fc7c4e8058c988a51328cff3e961397d5c5e1d9a2

Observation f0f2dddd-e115-4a9e-9421-912df3bc9216 · outbound

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

ODG: Occupancy Prediction Using Dual Gaussians Surroundocc: Multi- camera 3d occupancy prediction for autonomous driving

Reference 55

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verified fuzzy
raw_fallback, observed 2026-08-07T04:53:45.061078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:43.487089Z digest=sha256:5b5db61120343ed5452e530a217f476e8bd0f5d21607502a826de56237e87212

Observation 80adbab7-082d-46af-990e-63bdf8f0b45a · outbound

This paper cites Metric3d: Towards zero-shot metric 3d prediction from a single image.

ODG: Occupancy Prediction Using Dual Gaussians Metric3d: Towards zero-shot metric 3d prediction from a single image

Reference 56

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:43.619357Z digest=sha256:b4ba63845196fe1d5976a2c6e33663fb964bc64963ed8c5df97d2c23b121402a

Observation ca8ea031-70d4-4d49-b50c-3b25b36b3d25 · outbound

This paper cites Mip-splatting: Alias-free 3d gaussian splatting.

ODG: Occupancy Prediction Using Dual Gaussians Mip-splatting: Alias-free 3d gaussian splatting

Reference 57

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no resolver link, observed 2026-08-07T04:53:43.699130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:43.699130Z digest=sha256:0c5dea49173c2d2e9dfb3a497f7a7ef0927238e5d911f53ad096fb4dc636c7be

Observation bc33690d-ccc6-4a00-8d4d-5c018793a298 · outbound

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

ODG: Occupancy Prediction Using Dual Gaussians FlashOcc: Fast and Memory-Efficient Occupancy Prediction via Channel-to-Height Plugin

Reference 58

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no resolver link, observed 2026-08-07T04:53:43.815551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:43.815551Z digest=sha256:2cfa92a992443c39ff2e3621e8c13a77713fde224c481e090f927c3bd842f54a

Observation 27e5d3b4-0276-438e-aa4b-979e79a7ea6c · outbound

This paper cites OccNeRF: Advancing 3D Occupancy Prediction in LiDAR-Free Environments.

ODG: Occupancy Prediction Using Dual Gaussians OccNeRF: Advancing 3D Occupancy Prediction in LiDAR-Free Environments

Reference 59

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no resolver link, observed 2026-08-07T04:53:43.916087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:53:43.916087Z digest=sha256:cc050293a7f73896dc6fd899cebd9b55da4588b753af980beb85c2fb22c56d47

Observation 270c4a0d-e229-4863-ad96-d33e27201f4f · outbound

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

ODG: Occupancy Prediction Using Dual Gaussians Occformer: Dual-path transformer for vision-based 3d semantic occupancy prediction

Reference 60

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raw_fallback, observed 2026-08-07T04:53:44.779223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:44.017381Z digest=sha256:860f90e50414eee6761d24df9ae2dc3dc11c960608689def6af37f48d9fd3b9b

Observation 12c50799-29e4-4cde-a6c8-12db7c7b52de · outbound

This paper cites nucraft: Crafting high resolution 3d semantic occupancy for unified 3d scene understanding.

ODG: Occupancy Prediction Using Dual Gaussians nucraft: Crafting high resolution 3d semantic occupancy for unified 3d scene understanding

Reference 61

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raw_fallback, observed 2026-08-07T04:53:44.560926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:53:44.121646Z digest=sha256:2a5c64ff0ec3f9f6fc4dfa449c95d7cad5e1b75a721e9d91cabb0339cf4705de

Pith citing papers

Observation 5309996e-3c97-4aed-a8a4-2e08de97a627 · inbound

RCGDet3D: Rethinking 4D Radar-Camera Fusion-based 3D Object Detection with Enhanced Radar Feature Encoding cites this paper.

RCGDet3D: Rethinking 4D Radar-Camera Fusion-based 3D Object Detection with Enhanced Radar Feature Encoding ODG: Occupancy Prediction Using Dual Gaussians

Reference 22

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arxiv_id, observed 2026-05-21T05:09:38.462540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T05:08:21.293905Z digest=sha256:c04c8fb2a43bd90f1ca50015234dec51796bd7ba668c510f93dfcf1b7db56a49

Observation 4177b57d-b3ab-4e32-a8d3-16e0315b73f1 · inbound

VEOcc: Voxel-Centric Online Semantic Occupancy Prediction For Embodied Scene Understanding cites this paper.

VEOcc: Voxel-Centric Online Semantic Occupancy Prediction For Embodied Scene Understanding ODG: Occupancy Prediction Using Dual Gaussians

Reference 30

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verified exact
arxiv_id, observed 2026-06-30T12:34:39.617858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T12:06:52.443736Z digest=sha256:4c4f9d4407cab62ca47c227ec90fa99d5d7863991a6232e8b32bdefab7c671b1