Paper Citation Record · LEDGER

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog

As of 11 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2607.22698.

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

pith.paper-citation-record.v1
2607.22698 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T20:21:09.592144Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

verified exact0
verified fuzzy0
unresolved30
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 06b88464-eea2-4b18-b474-184e7cbf2ade · outbound

This paper cites CARLA-2DBBox: Vehicle 2D bounding box annotation module for the CARLA simulator.https://mukhlasadib.github.io/CARLA-2DBBox/,.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog CARLA-2DBBox: Vehicle 2D bounding box annotation module for the CARLA simulator.https://mukhlasadib.github.io/CARLA-2DBBox/,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:05.460342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8768b751-8389-4a34-bfb8-618cffb9d68d · outbound

This paper cites TransFusion: Robust LiDAR-camera fusion for 3D object detection with transformers.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog TransFusion: Robust LiDAR-camera fusion for 3D object detection with transformers

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:05.888579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22e76e5f-c023-4292-bed8-cf9cf29a3c9b · outbound

This paper cites Seeing through fog without seeing fog: Deep multimodal sensor fusion in unseen adverse weather.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Seeing through fog without seeing fog: Deep multimodal sensor fusion in unseen adverse weather

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:06.061457Z

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Observation de443e72-ee7b-4cfd-9ba3-bdd67c19bc1b · outbound

This paper cites Yoon, Yuchen Wu, Andrew Z.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Yoon, Yuchen Wu, Andrew Z

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:06.224702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8176d20-6e54-44c8-946d-b4d977860fd2 · outbound

This paper cites Virtual KITTI 2.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Virtual KITTI 2

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:06.396068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba449bdd-d37b-41a0-8ad0-5b6d4126e977 · outbound

This paper cites Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:06.458612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49c0f6e6-e79a-4879-8898-a45a43ffbb9a · outbound

This paper cites KITTI-CARLA: a KITTI-like dataset generated by CARLA Simulator.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog KITTI-CARLA: a KITTI-like dataset generated by CARLA Simulator

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:06.562413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c549fe6d-b55b-4f32-b126-9b9145d582d7 · outbound

This paper cites CARLA: An open urban driving simulator.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog CARLA: An open urban driving simulator

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:06.676935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0927ea6b-f859-47a7-8dde-aa86d37c7081 · outbound

This paper cites SCOPE: A Synthetic Multi-Modal Dataset for Collective Perception Including Physical-Correct Weather Conditions.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog SCOPE: A Synthetic Multi-Modal Dataset for Collective Perception Including Physical-Correct Weather Conditions

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:06.819467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4691633-c63c-4052-ae19-09d118a23bf6 · outbound

This paper cites Are we ready for autonomous driv- ing? the KITTI vision benchmark suite.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Are we ready for autonomous driv- ing? the KITTI vision benchmark suite

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:07.009055Z

Source-reported events for the cited work

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Observation 9fc9eb81-b1d9-4644-8709-1ff66c78ba75 · outbound

This paper cites Fog simula- tion on real LiDAR point clouds for 3D object detection in adverse weather.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Fog simula- tion on real LiDAR point clouds for 3D object detection in adverse weather

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:07.161718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c4c7a5c-4887-4d78-b1d9-9216782fe701 · outbound

This paper cites Single image haze removal using dark chan- nel prior.IEEE Trans.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Single image haze removal using dark chan- nel prior.IEEE Trans

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:07.311817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2933e735-c075-43a0-bb8f-f5f046c18165 · outbound

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

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:07.442118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09a039ee-3b23-4f23-bd40-3df202442b1d · outbound

This paper cites YOLO by Ultralytics (YOLOv8).

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog YOLO by Ultralytics (YOLOv8)

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:07.549102Z

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Unavailable: canonical work link unavailable.

Observation 939aaa5b-09ad-439a-87eb-4d3fd37952e4 · outbound

This paper cites Adver-City: Open-Source Multi-Modal Dataset for Collaborative Perception Under Adverse Weather Conditions.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Adver-City: Open-Source Multi-Modal Dataset for Collaborative Perception Under Adverse Weather Conditions

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:07.700228Z

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Observation cb9fed75-3ca5-4429-ae8d-e81e87149c22 · outbound

This paper cites AOD-Net: All- in-one dehazing network.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog AOD-Net: All- in-one dehazing network

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:07.809445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe1f11de-7cba-462e-92be-48193546d461 · outbound

This paper cites Swin Transformer: Hierarchical vision transformer using shifted win- dows.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Swin Transformer: Hierarchical vision transformer using shifted win- dows

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:07.991870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aca096e5-f802-4d07-8f7a-ef1b63f5be8e · outbound

This paper cites Rus, and Song Han.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Rus, and Song Han

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:08.148465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 512b5cd6-0696-43d4-8c16-3079da125df5 · outbound

This paper cites Lift, Splat, Shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3D.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Lift, Splat, Shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3D

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:08.247068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba25b38d-ab0d-4afd-89a2-e4a471bbe785 · outbound

This paper cites Canadian adverse driving conditions dataset.International Journal of Robotics Research (IJRR), 40(4–5):681–690, 2021.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Canadian adverse driving conditions dataset.International Journal of Robotics Research (IJRR), 40(4–5):681–690, 2021

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:08.402379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d173a925-c727-4d33-b137-0ff710de3939 · outbound

This paper cites Model adaptation with synthetic and real data for semantic dense foggy scene understanding.Interna- tional Journal of Computer Vision (IJCV), 2018.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Model adaptation with synthetic and real data for semantic dense foggy scene understanding.Interna- tional Journal of Computer Vision (IJCV), 2018

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:08.547498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb38cbaa-87d6-4f2e-8bd3-688dfe97b5e3 · outbound

This paper cites Semantic foggy scene under- standing with synthetic data.International Journal of Computer Vision (IJCV), 126 (9):973–992, 2018.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Semantic foggy scene under- standing with synthetic data.International Journal of Computer Vision (IJCV), 126 (9):973–992, 2018

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:08.677374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 029f8b44-7b04-44b3-8eb1-0c3e13714139 · outbound

This paper cites ACDC: The adverse condi- tions dataset with correspondences for semantic driving scene understanding.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog ACDC: The adverse condi- tions dataset with correspondences for semantic driving scene understanding

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:08.835676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c13c5d52-4fe8-406d-b1e1-ef28fb9aae4f · outbound

This paper cites Vision transformers for single image dehazing.IEEE Trans.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Vision transformers for single image dehazing.IEEE Trans

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:08.942578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b28c3e0-6cbb-4b6c-8c56-56180c578a5b · outbound

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

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Scalability in perception for autonomous driving: Waymo open dataset

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:09.055490Z

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Unavailable: canonical work link unavailable.

Observation b2f52368-6446-4b83-a817-ce373b6c7c92 · outbound

This paper cites SHIFT: A synthetic driving dataset for continuous multi-task domain adaptation.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog SHIFT: A synthetic driving dataset for continuous multi-task domain adaptation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:09.204835Z

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Unavailable: canonical work link unavailable.

Observation 119bcfc5-96fa-417e-8e44-4e95a1e20f7f · outbound

This paper cites AOD-net by PyTorch.https://github.com/weberwcwei/ AODnet-by-pytorch, 2018.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog AOD-net by PyTorch.https://github.com/weberwcwei/ AODnet-by-pytorch, 2018

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:09.331493Z

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Observation 74396052-086f-4dc2-904a-2fb75e52b558 · outbound

This paper cites SynFog: A Photo-realistic Synthetic Fog Dataset based on End-to-end Imaging Simulation for Advancing Real-World Defogging in Autonomous Driving.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog SynFog: A Photo-realistic Synthetic Fog Dataset based on End-to-end Imaging Simulation for Advancing Real-World Defogging in Autonomous Driving

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:09.439590Z

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Unavailable: canonical work link unavailable.

Observation afa10964-6130-40f4-ae1e-61487855a061 · outbound

This paper cites supplementary § Dn.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog supplementary § Dn

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:09.592144Z

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Observation 948418ee-37a3-4512-ac3d-418f2681fac5 · outbound

This paper cites FogDrive uses a locally modified version that lets four cameras of different orientation share a single semantic LiDAR for the visibility test.

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog FogDrive uses a locally modified version that lets four cameras of different orientation share a single semantic LiDAR for the visibility test

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-01T20:21:05.645492Z

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Pith citing papers

No inbound Pith citation observations are available.