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Paper Citation Record · LEDGER

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method

As of 20 August 2026, this Paper Citation Record lists 94 of 94 outbound references and 1 inbound Pith citation observation for arXiv:2510.22973.

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

pith.paper-citation-record.v1
2510.22973 v2

Coverage vector

measured 94 of 94 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T08:07:46.273852Z

measured 95 of 95 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T11:43:25.707481Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

94 of 94 outbound references displayed

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  • verified fuzzy0
  • unresolved94
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1a44b6ab-a78e-458b-83dd-b149a7d209d6 · outbound

This paper cites Diffusion probabilistic models for 3d point cloud generation,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Diffusion probabilistic models for 3d point cloud generation,

Reference 1

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source=pdf_text observed=2026-08-04T08:07:35.217560Z digest=sha256:8b8894e53d024842d5adacf58cfc9f7a0da5e20fc8c04b75e8c786c4b819f135

Observation 1da1b2c5-2198-4269-97d2-5a198d02e4c8 · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method High- resolution image synthesis with latent diffusion models,

Reference 2

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Observation 44b843fd-7869-45ca-aeb2-fcbb472c9933 · outbound

This paper cites Conditional diffusion process for inverse halftoning,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Conditional diffusion process for inverse halftoning,

Reference 3

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Observation 686455d0-5405-4a66-ac70-46426afb63df · outbound

This paper cites One at a time: Progressive multi-step volumetric probability learning for reliable 3d scene perception,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method One at a time: Progressive multi-step volumetric probability learning for reliable 3d scene perception,

Reference 4

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Observation df9a4506-c620-4703-9b4c-da63d105821c · outbound

This paper cites DreamDrive: Generative 4D Scene Modeling from Street View Images.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method DreamDrive: Generative 4D Scene Modeling from Street View Images

Reference 5

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Observation 047ffc95-f26d-43d2-b1e2-4186c9e884a1 · outbound

This paper cites UniScene: Unified Occupancy-centric Driving Scene Generation.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method UniScene: Unified Occupancy-centric Driving Scene Generation

Reference 6

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Observation ede2d3b5-e26c-432e-87ed-e8568251f2b4 · outbound

This paper cites Stag-1: Towards Realistic 4D Driving Simulation with Video Generation Model.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Stag-1: Towards Realistic 4D Driving Simulation with Video Generation Model

Reference 7

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Observation 4c76a5c9-f522-4542-b99b-f8b00d8d606d · outbound

This paper cites History-Guided Video Diffusion.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method History-Guided Video Diffusion

Reference 8

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Observation df2e722f-6e66-47c7-82d6-c1660ab8b2d9 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout

Reference 9

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Observation bdeded8d-daa0-4d30-9738-1a01de14c8d4 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Street-view image generation from a bird’s-eye view layout,

Reference 10

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Observation e0030f0c-f156-4aec-8559-2b0b5e8c1816 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Drivedreamer: Towards real-world-driven world models for autonomous driving,

Reference 11

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Observation 3a57def6-7dd7-455a-8d2a-e5ff9eae17f7 · outbound

This paper cites Magicdrive: Street view generation with diverse 3d geometry control,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Magicdrive: Street view generation with diverse 3d geometry control,

Reference 12

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Observation 654375db-41c4-4cf6-9270-fa32a1878811 · outbound

This paper cites Panacea: Panoramic and controllable video generation for autonomous driving,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Panacea: Panoramic and controllable video generation for autonomous driving,

Reference 13

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source=pdf_text observed=2026-08-04T08:07:36.291079Z digest=sha256:25e8c707ac8d35c3e53203eb12a3e96df858c41a96af3f0021710c3392fe9fec

Observation 1fb97571-7d1a-49e1-a3fb-7beaa65abb42 · outbound

This paper cites Lidardm: Generative lidar simulation in a generated world,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Lidardm: Generative lidar simulation in a generated world,

Reference 14

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Observation 6063ff37-6089-46af-999d-d80fbd09a534 · outbound

This paper cites Open- vocabulary object segmentation with diffusion models,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Open- vocabulary object segmentation with diffusion models,

Reference 15

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source=pdf_text observed=2026-08-04T08:07:36.625343Z digest=sha256:6bbe0ec9e91e2f49f9479152bbefcc0c1b430068264084656ebc35d342c712a5

Observation a4e603e4-2d49-467e-9560-99b2ff0c6155 · outbound

This paper cites Datasetdm: Synthesizing data with perception annotations using diffusion models,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Datasetdm: Synthesizing data with perception annotations using diffusion models,

Reference 16

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Observation 08f0c972-47e9-47ba-8893-c7f965ef2866 · outbound

This paper cites Fairdiff: Fair segmentation with point-image diffusion,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Fairdiff: Fair segmentation with point-image diffusion,

Reference 17

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source=pdf_text observed=2026-08-04T08:07:36.976501Z digest=sha256:01dacbacfafc9fec3ab69d1c90b82b99be901cb52ce5c39c697cfa93b2dd4bc5

Observation c2cf5bec-3330-4be4-8828-f8c052630b76 · outbound

This paper cites GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

Reference 18

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Observation f3d67d79-1413-4424-afd8-be1ab031a7da · outbound

This paper cites GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation

Reference 19

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Observation 18b03242-49d6-4487-9025-e1d90cd7e217 · outbound

This paper cites Detdiffusion: Synergizing generative and perceptive models for enhanced data generation and perception,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Detdiffusion: Synergizing generative and perceptive models for enhanced data generation and perception,

Reference 20

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Observation 5e5fefb6-9f4e-49e7-a280-8db299e7e632 · outbound

This paper cites Is synthetic data from generative models ready for image recognition?.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Is synthetic data from generative models ready for image recognition?

Reference 21

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source=pdf_text observed=2026-08-04T08:07:37.618570Z digest=sha256:126fa1e168c4238a6e0dd4b318b30b8a92396bbebb0edd0973859f34c181e6b4

Observation c4fbec0e-56ce-4566-ae57-968ed2c1e102 · outbound

This paper cites The Parrot Dilemma: Human-Labeled vs. LLM-augmented Data in Classification Tasks.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method The Parrot Dilemma: Human-Labeled vs. LLM-augmented Data in Classification Tasks

Reference 22

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Observation 0e436e1a-0906-44fa-9cb5-e4cf7b93bfa8 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method DriveDreamer4D: World Models Are Effective Data Machines for 4D Driving Scene Representation

Reference 23

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Observation 84dd11a4-aae9-48a5-b529-d8b738cb0603 · outbound

This paper cites Panacea: Panoramic and controllable video generation for autonomous driving,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Panacea: Panoramic and controllable video generation for autonomous driving,

Reference 24

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Observation a7ebbf68-3899-4130-b346-79e12e2dfb76 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Openoccupancy: A large scale benchmark for surrounding semantic occupancy perception,

Reference 25

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source=pdf_text observed=2026-08-04T08:07:38.193840Z digest=sha256:72a6aa38789b3ae86be67945e7e9e86f2e47ce4cf0b7734ff6aa1b46fef8b4a0

Observation b4e75ad1-fdcb-4e96-8480-ee5787633319 · outbound

This paper cites Bevfusion: A simple and robust lidar-camera fusion framework,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Bevfusion: A simple and robust lidar-camera fusion framework,

Reference 26

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Observation 21bc0d40-d8a3-476e-af00-5e409d3e1946 · outbound

This paper cites Deepfusion: Lidar-camera deep fusion for multi-modal 3d object detection,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Deepfusion: Lidar-camera deep fusion for multi-modal 3d object detection,

Reference 27

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Observation d8cc7e56-1482-4da0-9008-dec8da78b8e8 · outbound

This paper cites Transfusion: Robust lidar-camera fusion for 3d object detection with transformers,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Transfusion: Robust lidar-camera fusion for 3d object detection with transformers,

Reference 28

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Observation 57d33304-63eb-4f77-8908-3569fc88683d · outbound

This paper cites Camera-lidar integration: Probabilistic sensor fusion for semantic mapping,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Camera-lidar integration: Probabilistic sensor fusion for semantic mapping,

Reference 29

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source=pdf_text observed=2026-08-04T08:07:38.924821Z digest=sha256:1030536432257797eb43c5521942e386a5d2e7210917e4de8aa56af24cb01e42

Observation 956eb75f-0195-4f0c-a5b8-4b813a55cce4 · outbound

This paper cites Learning to generate realistic lidar point cloud,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Learning to generate realistic lidar point cloud,

Reference 30

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Observation 12668a3a-2de9-42b9-8fdf-aac725127231 · outbound

This paper cites Towards realistic scene generation with lidar diffusion models,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Towards realistic scene generation with lidar diffusion models,

Reference 31

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Observation e1726f2c-5450-40df-8150-ce957bad3d72 · outbound

This paper cites DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation

Reference 32

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Observation eb75fdd1-bfd9-4b22-9dad-d28ea56500fc · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving,

Reference 33

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Observation c2d767c4-3e3b-45bb-9c24-1e8430f4ea01 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Surroundocc: Multi-camera 3d occupancy prediction for autonomous driving,

Reference 34

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Observation 000b5467-71d0-41e2-b9f2-a0debc9cbd50 · outbound

This paper cites Scene as occupancy,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Scene as occupancy,

Reference 35

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Observation 42694bb0-b81c-472d-a186-a95bf95f1758 · outbound

This paper cites Planning-oriented autonomous driving,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Planning-oriented autonomous driving,

Reference 36

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source=pdf_text observed=2026-08-04T08:07:39.768811Z digest=sha256:10cd68eee9f65e052e2408e59561db8e81240b2cc5d665b505f3c4c97cbf5d17

Observation 29eb22e2-0d13-4f0f-8157-3d45cf152830 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method nuscenes: A multimodal dataset for autonomous driving,

Reference 37

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Observation 209d4380-4faf-482a-9a07-e0970763afd9 · outbound

This paper cites Nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles,

Reference 38

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Observation 0ad386af-0181-4c4d-bb3a-0d41f697d283 · outbound

This paper cites Neural kernel surface reconstruction,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Neural kernel surface reconstruction,

Reference 39

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Observation 941994d9-7997-4d71-8710-6c4df725f409 · outbound

This paper cites Indoor segmentation and support inference from rgbd images.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Indoor segmentation and support inference from rgbd images

Reference 40

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Observation c89b0cf4-3622-4363-bb1b-7b88286f0290 · outbound

This paper cites Scenenn: A scene meshes dataset with annotations,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Scenenn: A scene meshes dataset with annotations,

Reference 41

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Observation 764fcce5-24e8-4c87-9bc7-69d3056953b0 · outbound

This paper cites SynthCity: A large scale synthetic point cloud.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method SynthCity: A large scale synthetic point cloud

Reference 42

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Observation 825e3faf-d284-45ba-a252-e6127a73632b · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Scannet: Richly-annotated 3d reconstructions of indoor scenes,

Reference 43

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source=pdf_text observed=2026-08-04T08:07:40.405280Z digest=sha256:301bcb46e0b98fcff0b9b68b174b784730481391489a1eed6506353221a377f1

Observation 35e495e4-fc83-4690-9231-656d0596d454 · outbound

This paper cites SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances

Reference 44

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Observation 29e632d6-c5a1-4afe-8a9b-a03a0bbd9484 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Semantickitti: A dataset for semantic scene understanding of lidar sequences,

Reference 45

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Observation a96845ed-f7bb-4bec-b447-50e7e4a876d4 · outbound

This paper cites KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D

Reference 46

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Observation 3bbeafd0-9e7e-41af-9b56-db4891e6c680 · outbound

This paper cites Openscene: The largest up-to-date 3d occupancy prediction benchmark in autonomous driving,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Openscene: The largest up-to-date 3d occupancy prediction benchmark in autonomous driving,

Reference 47

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source=pdf_text observed=2026-08-04T08:07:40.731645Z digest=sha256:872656af7a5252e12ff228ea2c951d483c02f7ae6bcbe53b90917694247e139d

Observation 04980219-8f38-4a21-82f0-97390077dd53 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Monoscene: Monocular 3d semantic scene completion,

Reference 48

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Observation 1b9d5f5b-5f7e-417b-923a-7243b9145782 · outbound

This paper cites Bridging stereo geometry and bev representation with reliable mutual interaction for semantic scene completion,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Bridging stereo geometry and bev representation with reliable mutual interaction for semantic scene completion,

Reference 49

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Observation dc12cc5f-b084-426e-b17a-6325cee1fd02 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Tri-perspective view for vision-based 3d semantic occupancy prediction,

Reference 50

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Observation e526568e-62c1-46f8-b6ab-7497e9aace4c · outbound

This paper cites Hierarchical temporal context learning for camera-based semantic scene completion,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Hierarchical temporal context learning for camera-based semantic scene completion,

Reference 51

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source=pdf_text observed=2026-08-04T08:07:40.954557Z digest=sha256:843f3c08a36fb8608f6d77f825aa0be324a5a9a125a0a61a62cd8efd6c8c4317

Observation b7ecc984-67f8-49d9-b158-7c845372e6b9 · outbound

This paper cites OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving

Reference 52

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Observation 193e0b2c-d21c-46f6-9ef7-731b3578d279 · outbound

This paper cites OccSora: 4D Occupancy Generation Models as World Simulators for Autonomous Driving.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method OccSora: 4D Occupancy Generation Models as World Simulators for Autonomous Driving

Reference 53

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Observation 66679bc7-9ebe-4000-b8e9-08b3a3f654c3 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method FB-OCC: 3D Occupancy Prediction based on Forward-Backward View Transformation

Reference 54

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Observation f2db8f9d-058c-4c4d-b38e-ea9020a76fa6 · outbound

This paper cites Semcity: Semantic scene generation with triplane diffusion,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Semcity: Semantic scene generation with triplane diffusion,

Reference 55

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Observation 65d4fd92-50f8-4abb-a043-0cb0403a19d2 · outbound

This paper cites Pyramid diffusion for fine 3d large scene generation,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Pyramid diffusion for fine 3d large scene generation,

Reference 56

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source=pdf_text observed=2026-08-04T08:07:41.501895Z digest=sha256:a65410d2bdc25b35ebf5779633f90f00acd022368696bd71686136b9e086799d

Observation e5e26516-713e-4d02-8af2-8913ab726b54 · outbound

This paper cites OccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Driving.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method OccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Driving

Reference 57

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source=pdf_text observed=2026-08-04T08:07:41.647718Z digest=sha256:3384dc6c416630b7f7cfa055d9155cb5545ae24cf53801517a8f7df1cd76cde6

Observation a95980d2-4e8a-450b-a7d6-cb0e3118aba7 · outbound

This paper cites Occupancy anticipation for efficient exploration and navigation,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Occupancy anticipation for efficient exploration and navigation,

Reference 58

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source=pdf_text observed=2026-08-04T08:07:41.765035Z digest=sha256:f7f8ba4ad0b48b2c83e68d8936988cb33ab0cec612677470a625c3a0733bd0c5

Observation 641b6a3a-9d2c-45e5-a452-95bbb15c5281 · outbound

This paper cites Structured 3D Latents for Scalable and Versatile 3D Generation.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Structured 3D Latents for Scalable and Versatile 3D Generation

Reference 59

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source=pdf_text observed=2026-08-04T08:07:41.881399Z digest=sha256:1a8705c1dfb83030142200c4d3c7b7c9f0ca6958fd5d497e037777b64d55d7e8

Observation d40ac17e-83e4-4749-9607-795fec037801 · outbound

This paper cites Driving in the occupancy world: Vision-centric 4d occupancy forecasting and planning via world models for autonomous driving,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Driving in the occupancy world: Vision-centric 4d occupancy forecasting and planning via world models for autonomous driving,

Reference 60

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source=pdf_text observed=2026-08-04T08:07:41.956721Z digest=sha256:ce4e76e37dd0290fd15d94ea8f945d546b28f1e2f53d68ca21ce66b3b62648c2

Observation 88ab6857-15d7-4699-8e23-2919f8c6922c · outbound

This paper cites Dynamiccity: Large-scale 4d occupancy generation from dynamic scenes,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Dynamiccity: Large-scale 4d occupancy generation from dynamic scenes,

Reference 61

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source=pdf_text observed=2026-08-04T08:07:42.078666Z digest=sha256:ee9eef571845dc7d325a61e1906f45d1890e2db779146874425d6d59e3228dff

Observation 0e542883-6af4-4a2e-9517-73816b8307e2 · outbound

This paper cites Vista: A generalizable driving world model with high fidelity and versatile controllability,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Vista: A generalizable driving world model with high fidelity and versatile controllability,

Reference 62

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source=pdf_text observed=2026-08-04T08:07:42.181016Z digest=sha256:218c05589d9663d144fa5b896337e52a10bd7021b035b73ed0a4d7ca50ff719a

Observation 92a85507-ef9f-448b-9a79-5cf4501fcd5d · outbound

This paper cites Bridging Stereo Geometry and BEV Representation with Reliable Mutual Interaction for Semantic Scene Completion.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Bridging Stereo Geometry and BEV Representation with Reliable Mutual Interaction for Semantic Scene Completion

Reference 63

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source=pdf_text observed=2026-08-04T08:07:42.326256Z digest=sha256:7f6450e5f1d762bc9cdcbdc92e47681c7ea64e8a9df9889f5140dbce47238877

Observation 640b2777-7630-4a8f-843d-5a4046ded02a · outbound

This paper cites Driving into the future: Multiview visual forecasting and planning with world model for autonomous driving,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Driving into the future: Multiview visual forecasting and planning with world model for autonomous driving,

Reference 64

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source=pdf_text observed=2026-08-04T08:07:42.400677Z digest=sha256:9d02a8f3a0f5e24460e0d23764c59d2a22c187057b6d63d9ea58a470534f8bd6

Observation 4cebcdf9-466e-4767-bab8-c1c624d173eb · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability

Reference 65

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source=pdf_text observed=2026-08-04T08:07:42.472230Z digest=sha256:7196702826ec9343ff441d5baa496641a6782e9181247abcdbc3b7848f5c268b

Observation 8ddd15d2-9241-4de6-9864-be443d402021 · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 66

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source=pdf_text observed=2026-08-04T08:07:42.601539Z digest=sha256:6c4ff4712c0dd2eb1dac0e061dbae12091d079e46d5c1d0d1df40e470ce5dd61

Observation f4e1ecb1-101f-4f05-8eb0-44d143003dbf · outbound

This paper cites WoVoGen: World Volume-aware Diffusion for Controllable Multi-camera Driving Scene Generation.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method WoVoGen: World Volume-aware Diffusion for Controllable Multi-camera Driving Scene Generation

Reference 67

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source=pdf_text observed=2026-08-04T08:07:42.731847Z digest=sha256:6e96f77de81d27ff91246c3269cf8a4e4eeb29c975eb654aab883a0cda3157b8

Observation 6f8de36c-fc32-4fad-b5bd-c1764a082add · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Learning transferable visual models from natural language supervision,

Reference 68

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source=pdf_text observed=2026-08-04T08:07:42.840593Z digest=sha256:da100f7859debf94f3b0f4020a8b7e3b6679afef07439e2d911eed678ce947fc

Observation 6eb35456-d06e-4269-9e7a-2f2ec6f23e91 · outbound

This paper cites MagicDrive-V2: High-Resolution Long Video Generation for Autonomous Driving with Adaptive Control.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method MagicDrive-V2: High-Resolution Long Video Generation for Autonomous Driving with Adaptive Control

Reference 69

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Observation 259c6968-dc14-4073-9873-f7670514892e · outbound

This paper cites Lidar snowfall simulation for robust 3d object detection,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Lidar snowfall simulation for robust 3d object detection,

Reference 70

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source=pdf_text observed=2026-08-04T08:07:43.064928Z digest=sha256:ac546b5aab6e2fcf0e26431cff3ba89e0a09a46a0cb40497092d6160df84574b

Observation 5e515fbd-dd6c-4bfb-86e7-45c9a5a766b5 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Learning compact representations for lidar completion and generation,

Reference 71

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source=pdf_text observed=2026-08-04T08:07:43.170169Z digest=sha256:4b9fca29204496d2578fd19440585331d2af3008e0e3b0b5a4ee460cd20c7ad6

Observation 821f2df5-4345-4fb3-9a81-929c1428ba65 · outbound

This paper cites Nerf-lidar: Generating realistic lidar point clouds with neural radiance fields,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Nerf-lidar: Generating realistic lidar point clouds with neural radiance fields,

Reference 72

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source=pdf_text observed=2026-08-04T08:07:43.335355Z digest=sha256:adc73714aa91a9e643e411ddac48f45740869eaf5d479fa6d00578319d74a5ba

Observation 5e0eed5b-952b-47d9-ad89-2a50584b459f · outbound

This paper cites Gs-lidar: Generating realistic lidar point clouds with panoramic gaussian splatting,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Gs-lidar: Generating realistic lidar point clouds with panoramic gaussian splatting,

Reference 73

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source=pdf_text observed=2026-08-04T08:07:43.455494Z digest=sha256:bf451a1edfe6a42a8e4a9650c9be21000cdf1eccf7690d98bfef492b0c4b20f4

Observation 139eb304-c615-449d-84f5-5e8b46fb3fda · outbound

This paper cites KISS-ICP: In Defense of Point-to-Point ICP – Simple, Accurate, and Robust Registration If Done the Right Way,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method KISS-ICP: In Defense of Point-to-Point ICP – Simple, Accurate, and Robust Registration If Done the Right Way,

Reference 74

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Observation f354693b-41d7-4d34-aa4d-24ec034a9337 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method The lovász-softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks,

Reference 75

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Observation cdb8adfb-2ef3-41bd-a181-07454dc17087 · outbound

This paper cites Latte: Latent Diffusion Transformer for Video Generation.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Latte: Latent Diffusion Transformer for Video Generation

Reference 76

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Observation e260fb90-9ae4-4717-82fe-fa87275dd5ac · outbound

This paper cites Scalable diffusion models with transformers,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Scalable diffusion models with transformers,

Reference 77

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Observation 93ef559a-77ba-4a45-991a-e315b94b23e6 · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 78

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Observation fbe4347f-4299-401f-a2fa-d910dfadb650 · outbound

This paper cites Open-Sora Plan: Open-Source Large Video Generation Model.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Open-Sora Plan: Open-Source Large Video Generation Model

Reference 79

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source=pdf_text observed=2026-08-04T08:07:44.374359Z digest=sha256:01734fe91aeee4be949ae60899f2125d0ed1874250bc0a0c9e94df0b7784fbd2

Observation 3c8be36c-42e4-4f74-ad83-3bea125e26b2 · outbound

This paper cites Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation,

Reference 80

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source=pdf_text observed=2026-08-04T08:07:44.588036Z digest=sha256:1b4e2474bd0191da335980ffd8b0e6d55cca373e33efe1e1b1c76ed83a037b59

Observation cd060e72-b221-4b84-b011-962151bbad20 · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Roformer: Enhanced transformer with rotary position embedding,

Reference 81

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source=pdf_text observed=2026-08-04T08:07:44.722096Z digest=sha256:6455e832b47d1f83d6d29abd33a1daa4151eea3d5bfeb66119d33a4dd47c83c7

Observation e2ef2ba2-4c75-4127-8955-c555093cbb94 · outbound

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

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method 3d gaussian splatting for real-time radiance field rendering

Reference 82

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source=pdf_text observed=2026-08-04T08:07:44.864869Z digest=sha256:1e82f17725f646b0807967da35c2ac5a7ec8441f59fe63d86c804e5ed1eda5c8

Observation 1cb08274-0bd4-441f-a0d1-ea51a0736d46 · outbound

This paper cites Hugs: Holistic urban 3d scene understanding via gaussian splatting,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Hugs: Holistic urban 3d scene understanding via gaussian splatting,

Reference 83

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source=pdf_text observed=2026-08-04T08:07:45.002390Z digest=sha256:4dcba1b14ac15c46e8955d3cb4edf0e9d0bf2fff48bab0b19b1a1e72bff95482

Observation e8989b0b-afce-49e5-823f-7b3f2e872547 · outbound

This paper cites 3dgut: Enabling distorted cameras and secondary rays in gaussian splatting,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method 3dgut: Enabling distorted cameras and secondary rays in gaussian splatting,

Reference 84

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Observation c3280511-88b4-4f04-bbed-1c8a8a104d3e · outbound

This paper cites From points to parts: 3d object detection from point cloud with part-aware and part-aggregation network,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method From points to parts: 3d object detection from point cloud with part-aware and part-aggregation network,

Reference 85

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source=pdf_text observed=2026-08-04T08:07:45.239804Z digest=sha256:35196788cea5d582e9d2754af13519e9ab5fb99c5bfc9b873c477e4696aae076

Observation 8a73f685-b613-4f96-86d5-2caff2e3bab2 · outbound

This paper cites Unisim: A neural closed-loop sensor simulator,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Unisim: A neural closed-loop sensor simulator,

Reference 86

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Observation 056ed30b-5317-4f7e-bf38-ea371b42946e · outbound

This paper cites Zip-nerf: Anti-aliased grid-based neural radiance fields,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Zip-nerf: Anti-aliased grid-based neural radiance fields,

Reference 87

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Observation 7750d637-abec-44cd-8640-517216022fba · outbound

This paper cites NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction

Reference 88

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Observation a0730047-7e12-4baa-bff2-dd9ecd4ef5eb · outbound

This paper cites Digging into self-supervised monocular depth estimation,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Digging into self-supervised monocular depth estimation,

Reference 89

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Observation 4c3455bd-9fc4-4946-82e0-830fc39dca23 · outbound

This paper cites Deep ordinal regression network for monocular depth estimation,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Deep ordinal regression network for monocular depth estimation,

Reference 90

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Observation 766448f4-4199-46f1-80f6-301e98345d59 · outbound

This paper cites Open3D: A Modern Library for 3D Data Processing.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Open3D: A Modern Library for 3D Data Processing

Reference 91

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Observation 5dd7ff0b-45b5-48b2-841a-8807995eba42 · outbound

This paper cites Lmscnet: Lightweight multiscale 3d semantic completion,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Lmscnet: Lightweight multiscale 3d semantic completion,

Reference 92

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source=pdf_text observed=2026-08-04T08:07:46.081344Z digest=sha256:90b84f4944b6c40681376d82723b8b1abbf40fa3a06d82017c53429d502483cf

Observation cb4b1df3-4497-4bc5-965e-660f0bb696f4 · outbound

This paper cites Navsim: Data-driven non- reactive autonomous vehicle simulation and benchmarking,.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method Navsim: Data-driven non- reactive autonomous vehicle simulation and benchmarking,

Reference 93

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Observation b53a8564-7878-49b9-a0b7-4b20ee7db564 · outbound

This paper cites He was a Sr.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method He was a Sr

Reference 2021

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source=pdf_text observed=2026-08-04T08:07:46.273852Z digest=sha256:034c852b438c740b26fb01daa1f48635fb19878476b7c502e89cf1abb2524859

Pith citing papers

Observation 74fe8ae3-bef1-4796-8fee-b74b86d94ef5 · inbound

FPSGen: Flexible Point Cloud Scene Generation with BEV-Supported Transport Flows cites this paper.

FPSGen: Flexible Point Cloud Scene Generation with BEV-Supported Transport Flows Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method

Reference 167

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source=arxiv_source observed=2026-08-01T11:43:25.707481Z digest=sha256:f4eee01ac983d2a8da190ca74c31d16feb8bda96154dfa670a6f2bb32fe8af4d