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Paper Citation Record · LEDGER

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving

As of 9 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2505.23115.

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

pith.paper-citation-record.v1
2505.23115 v2

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:57:16.526609Z

measured 44 of 44 standing notices

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

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 85cd9984-6b2f-4e0e-8e68-92fbbf5b81d7 · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d,

Reference 1

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Observation e880d585-fb32-48bc-ab1a-33fd91f4bff2 · outbound

This paper cites Semantickitti: A dataset for semantic scene un- derstanding of lidar sequences,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Semantickitti: A dataset for semantic scene un- derstanding of lidar sequences,

Reference 2

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Observation 4d0738fc-0eba-4318-8ed7-fa6fd46fc069 · outbound

This paper cites Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving

Reference 3

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Observation 6ada5bf7-7a60-41a9-b199-c41a66d223da · outbound

This paper cites Denoising diffusion probabilistic models,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Denoising diffusion probabilistic models,

Reference 4

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Observation fb20ddc2-42aa-4068-ae06-131ebc5099cf · outbound

This paper cites Denoising Diffusion Implicit Models.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Denoising Diffusion Implicit Models

Reference 5

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Observation bce0e8c3-b2dd-405b-ad8f-4969908458c1 · outbound

This paper cites Argmax flows and multinomial diffusion: Learning categorical distributions,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Argmax flows and multinomial diffusion: Learning categorical distributions,

Reference 6

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Source-reported events for the cited work

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Observation 6e88a2c0-5e52-4da0-817c-ccaa44b1a9d8 · outbound

This paper cites Structured denoising diffusion models in discrete state-spaces,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Structured denoising diffusion models in discrete state-spaces,

Reference 7

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Observation c866eb1f-563c-40a4-a48d-58cdbaaff896 · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving U-net: Convolutional networks for biomedical image segmentation,

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 e3bb08ab-7a89-4cc3-ba17-9f9fde51410e · outbound

This paper cites Cylindrical and asymmetrical 3d convolution networks for lidar segmentation,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Cylindrical and asymmetrical 3d convolution networks for lidar segmentation,

Reference 9

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Observation c8960e6d-7d98-4439-8c33-ff18fdc07a41 · outbound

This paper cites Sigmoid-weighted linear units for neural network function approximation in reinforcement learning,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Sigmoid-weighted linear units for neural network function approximation in reinforcement learning,

Reference 10

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Observation 3c0844c8-99b7-4ad9-9565-8d7c28278ed8 · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers,

Reference 11

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Observation 1a82b77e-5305-42b5-9ea2-225750f268f0 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Deep unsupervised learning using nonequilibrium thermodynamics,

Reference 12

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Observation c7ea90ce-d619-4033-9317-d1917eea9acd · outbound

This paper cites Classifier-Free Diffusion Guidance.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Classifier-Free Diffusion Guidance

Reference 13

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Observation 134e1503-09f7-413a-be79-172cb01b778f · outbound

This paper cites Diffusion models beat gans on image synthesis,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Diffusion models beat gans on image synthesis,

Reference 14

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Observation b22509c5-1b4e-4d62-a89e-214539eb3dfc · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving FB-OCC: 3D Occupancy Prediction based on Forward-Backward View Transformation

Reference 15

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Observation 71d7bbaa-5541-4f0d-a71b-06d2d302e7b9 · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Monoscene: Monocular 3d semantic scene completion,

Reference 16

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Observation 7b8503ba-2d91-4c96-be34-f21e13824e29 · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving RenderOcc: Vision-Centric 3D Occupancy Prediction with 2D Rendering Supervision

Reference 17

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Observation 3b66aa44-3aba-45c6-87fa-f5452552b1d5 · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View

Reference 18

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Observation 01804d58-7249-4536-917a-d3d8d831818c · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentation

Reference 19

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Observation 70ec621d-dd51-40e2-9861-f33ae99725c0 · outbound

This paper cites Denoising Diffusion Semantic Segmentation with Mask Prior Modeling.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Denoising Diffusion Semantic Segmentation with Mask Prior Modeling

Reference 20

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Observation 6a0e4802-bde2-4fd2-8bbb-915e63497cf9 · outbound

This paper cites Planning-oriented autonomous driving,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Planning-oriented autonomous driving,

Reference 21

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Observation 1f8cf418-4b34-445d-893e-af2f6782917b · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Openoccupancy: A large scale benchmark for surrounding semantic occupancy perception,

Reference 22

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Observation eb52ef87-f049-46ff-909d-9b89471dbe14 · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Occformer: Dual-path transformer for vision-based 3d semantic occupancy prediction,

Reference 23

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Observation dd25a889-d8c9-4f57-a680-d7236abd23f1 · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Surroundocc: Multi-camera 3d occupancy prediction for autonomous driving,

Reference 24

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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 d01033f5-3d87-4404-8131-1495621982e6 · outbound

This paper cites PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction

Reference 25

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source=pdf_text observed=2026-08-07T12:57:15.310716Z digest=sha256:ce48158132aababfec86f75bc6fed1922ce719e2c7651c85019bbdc7f25623f5

Observation c47f20b9-f6d2-440c-9517-12e2d4a7d317 · outbound

This paper cites A Simple Framework for 3D Occupancy Estimation in Autonomous Driving.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving A Simple Framework for 3D Occupancy Estimation in Autonomous Driving

Reference 26

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local_arxiv, observed 2026-08-07T12:57:17.106328Z

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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 91fbd28b-420e-4664-899e-77151cc50311 · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Scenerf: Self-supervised monocular 3d scene reconstruction with radiance fields,

Reference 27

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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.

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Observation a2866093-235a-4a8a-8d10-5c8dd007bd51 · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Tri-perspective view for vision-based 3d semantic occupancy prediction,

Reference 28

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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.

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Observation c6d5dcf1-ef57-4ae9-96e4-4cdf14b21f51 · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving V oxformer: Sparse voxel transformer for camera- based 3d semantic scene completion,

Reference 29

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Observation 2d966b51-377d-4def-85af-995acfbe6305 · outbound

This paper cites Scene as occupancy,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Scene as occupancy,

Reference 30

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raw_fallback, observed 2026-08-07T12:57:18.260406Z

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.

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Observation 95ef765e-f68c-4de2-99c2-a85e9f7b380a · outbound

This paper cites Mapprior: Bird’s-eye view map layout estimation with generative models,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Mapprior: Bird’s-eye view map layout estimation with generative models,

Reference 31

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raw_fallback, observed 2026-08-07T12:57:18.093336Z

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=2026-08-07T12:57:15.757066Z digest=sha256:245c2354ae8b9e53d245908ab39752e5cb90e86ef2affc714a148d66d8e206ae

Observation 11bf4ac3-9b13-495f-b1bb-fdc6ec1236f9 · outbound

This paper cites Joint 2D-3D-Semantic Data for Indoor Scene Understanding.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Joint 2D-3D-Semantic Data for Indoor Scene Understanding

Reference 32

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source=pdf_text observed=2026-08-07T12:57:15.810738Z digest=sha256:5e9de6971619d84779e4fcc64eecf3e1ae74252cf1d7b8bd889d1eee0d49171b

Observation 0e4e15e7-198f-4288-99ff-2f77bf84031b · outbound

This paper cites Scannet: Richly-annotated 3d reconstructions of indoor scenes,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Scannet: Richly-annotated 3d reconstructions of indoor scenes,

Reference 33

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source=pdf_text observed=2026-08-07T12:57:15.864082Z digest=sha256:9a99d859fb7e6296dc1856877f5485ff73058993428438a17a34da36b94da08d

Observation d057a2d6-39d0-4b50-9ac5-6093d044cf99 · outbound

This paper cites Diffusion Probabilistic Models for Scene-Scale 3D Categorical Data.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Diffusion Probabilistic Models for Scene-Scale 3D Categorical Data

Reference 34

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source=pdf_text observed=2026-08-07T12:57:15.925875Z digest=sha256:85aab7b75ac619543032168322b0b7a64d1015e913e6d2dc2c9e186608b3d84f

Observation ac5bbb3a-9b26-4cb4-aac4-a2c0a377c071 · outbound

This paper cites BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:57:16.013834Z digest=sha256:c7114f06e055112b7f5d67078b22fc237724b9b0fab1c71bcdc5a9760f3a1011

Observation f0704e84-42d3-498a-b3a6-24e8f0ff8a20 · outbound

This paper cites Street-view image generation from a bird’s-eye view layout,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Street-view image generation from a bird’s-eye view layout,

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-07T12:57:17.867131Z

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=2026-08-07T12:57:16.053067Z digest=sha256:127755ec39ae27ed873bb1b58834d78bd71953fff3c41ff30ba41593aa1f2f74

Observation e958071e-1e1f-4a32-bf25-856a17061119 · outbound

This paper cites DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T12:57:16.102535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:57:16.102535Z digest=sha256:85e543a16ec7123d6b87af9cb55b4fb8c65fd4fb4ff5139bed8deb68cdc06e69

Observation b3a3cb41-3013-4558-909e-c49fe24881c9 · outbound

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

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving MagicDrive: Street View Generation with Diverse 3D Geometry Control

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T12:57:16.147405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:57:16.147405Z digest=sha256:97b0368130e448a4b97f72ccbfab4d701f0346cff0a2ff29005717a86c219a0c

Observation 9d46f851-31e2-4875-81b1-8dce821004e3 · outbound

This paper cites Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T12:57:16.187608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:57:16.187608Z digest=sha256:09904bbb6fcbf7f8f2025377cff4717a36d655dd2691079497332fe72b4a8113

Observation b4579ff5-1dc5-4860-8c0c-a6df891fb143 · outbound

This paper cites Panacea: Panoramic and Controllable Video Generation for Autonomous Driving.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Panacea: Panoramic and Controllable Video Generation for Autonomous Driving

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T12:57:16.292531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:57:16.292531Z digest=sha256:796f9e134c7ee2d5f7d4ec57b1e69879ffad8799ee814e83c7e24fe46e227682

Observation 739124b4-2c0c-4633-99bf-ecdbb066c323 · outbound

This paper cites Learning compact representations for lidar completion and generation,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Learning compact representations for lidar completion and generation,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:57:17.650134Z

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=2026-08-07T12:57:16.336588Z digest=sha256:a6766f06fac201c0e41653fbf9a9da91ab0e5086c1aa5304fbd7973ebb2b3754

Observation e3fceb30-1ab7-4438-affb-05583bebfc71 · outbound

This paper cites Lopr: Latent occupancy prediction using generative models,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Lopr: Latent occupancy prediction using generative models,

Reference 42

Resolution
verified exact
raw_fallback, observed 2026-08-07T12:57:16.904820Z

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=2026-08-07T12:57:16.370459Z digest=sha256:0fb59f86dc09627de1001570be4adf1a094a032eadfcb90d1eaf2c7309621709

Observation a88b7042-bca5-4e5c-87a3-a14d02c23fd3 · outbound

This paper cites DiffBEV: Conditional Diffusion Model for Bird's Eye View Perception.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving DiffBEV: Conditional Diffusion Model for Bird's Eye View Perception

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:57:16.715046Z

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=2026-08-07T12:57:16.427600Z digest=sha256:521db14c456a4ef894353640f26264b7b5eba5ecb469fc0a094b202c7de4f75e

Observation d81047c6-0c30-40aa-b81e-af387c906cd1 · outbound

This paper cites Occgen: Generative multi-modal 3d occupancy prediction for autonomous driving,.

Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving Occgen: Generative multi-modal 3d occupancy prediction for autonomous driving,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:57:17.444975Z

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=2026-08-07T12:57:16.526609Z digest=sha256:a7393be3b2d8d6e4306d29cc99ec2e948dfcd4f96fb76e085ecc511542cb6ff0

Pith citing papers

No inbound Pith citation observations are available.