Paper Citation Record · LEDGER

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence

As of 7 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2508.00299.

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

pith.paper-citation-record.v1
2508.00299 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:16:25.195091Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

42 of 42 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f1709da7-3301-4bd1-9047-90e206426fb2 · outbound

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

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence nuscenes: A multi- modal dataset for autonomous driving

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:26.185487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 344670a6-f5c9-433e-b2d2-1274f5d0436c · outbound

This paper cites Realtime multi-person 2d pose estimation using part affinity fields.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Realtime multi-person 2d pose estimation using part affinity fields

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:26.164549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2d753344-c695-471f-a7e5-00e479dbfade · outbound

This paper cites MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusion.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusion

Reference 3

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Source-reported events for the cited work

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Observation 3b5b99bc-8835-4833-955b-e8aa173fa971 · outbound

This paper cites Structure and content-guided video synthesis with diffusion models.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Structure and content-guided video synthesis with diffusion models

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:26.137906Z

Source-reported events for the cited work

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Observation e04cbcc0-5027-43ca-b8dc-f6f4fa088e25 · outbound

This paper cites MagicDrive3D: Controllable 3D Generation for Any-View Rendering in Street Scenes.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence MagicDrive3D: Controllable 3D Generation for Any-View Rendering in Street Scenes

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:24.928194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0b0984a-ad08-4229-97c8-ea0ac9aa733f · outbound

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

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:24.935021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 646d4b11-bdc7-44b7-92ab-4b3199161c35 · outbound

This paper cites 8 Densepose: Dense human pose estimation in the wild.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence 8 Densepose: Dense human pose estimation in the wild

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:26.109398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9c1c7d5b-4774-4b90-9fd9-d732087ce681 · outbound

This paper cites AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c446e23-4e59-48f8-9921-2e145ef193f8 · outbound

This paper cites Animate anyone: Consistent and controllable image- to-video synthesis for character animation.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Animate anyone: Consistent and controllable image- to-video synthesis for character animation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:26.086274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0c54ec4b-1903-412c-a5c1-c33ef59082f3 · outbound

This paper cites Composer: creative and controllable im- age synthesis with composable conditions.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Composer: creative and controllable im- age synthesis with composable conditions

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:26.061135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7f3ebcc3-659e-4b6d-8079-f3139bf4e40c · outbound

This paper cites Text2performer: Text- driven human video generation.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Text2performer: Text- driven human video generation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:26.026724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c05a73ef-79e9-4afe-b590-977e1d27adf9 · outbound

This paper cites Dreampose: Fashion image-to-video synthesis via stable diffusion.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Dreampose: Fashion image-to-video synthesis via stable diffusion

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:26.000347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d265aa3a-7c9f-443e-bc05-d5566f713e7d · outbound

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

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence 3d gaussian splatting for real-time radiance field rendering

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:24.985880Z

Source-reported events for the cited work

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Observation c68de3f0-fb6f-45ef-a711-eccf83756222 · outbound

This paper cites Text2video-zero: Text- to-image diffusion models are zero-shot video generators.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Text2video-zero: Text- to-image diffusion models are zero-shot video generators

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:25.962621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c43b8eca-1d7c-4971-9c64-66c158d3560c · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.003240Z

Source-reported events for the cited work

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Observation 15f9c03f-ab2a-4c2c-ae1d-1ac1c14c2c01 · outbound

This paper cites Smpl: a skinned multi- person linear model.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Smpl: a skinned multi- person linear model

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:25.939959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4a51c89b-3c3c-4abe-912a-984fc405fb81 · outbound

This paper cites Follow your pose: Pose- guided text-to-video generation using pose-free videos.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Follow your pose: Pose- guided text-to-video generation using pose-free videos

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.015386Z

Source-reported events for the cited work

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Observation 9f3c09a6-a6c0-4a6b-800d-c5d6c0ec6e26 · outbound

This paper cites T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.021308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f916f8f5-d6ec-4e8a-b33d-e1c2f0da9113 · outbound

This paper cites Recondreamer: Crafting world models for driving scene reconstruction via online restora- tion.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Recondreamer: Crafting world models for driving scene reconstruction via online restora- tion

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:25.867244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 33b947be-c410-403d-837c-2cdb30db6f0f · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.034289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6d1d0ac-9b70-40a4-991e-452020146a0f · outbound

This paper cites Fatezero: Fus- ing attentions for zero-shot text-based video editing.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Fatezero: Fus- ing attentions for zero-shot text-based video editing

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.040307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ed40cfc-7d3f-4c3b-b90b-28feca6f9edb · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Learning transferable visual models from natural language supervi- sion

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.046103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7629ee3c-368d-4faa-9ed2-17d8b213c0bb · outbound

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

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence High-resolution image synthesis with latent diffusion models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.053151Z

Source-reported events for the cited work

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Observation 293dd31f-36d3-4237-bb29-df108da3dcd8 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Photorealistic text-to-image diffusion models with deep language understanding

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.060499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79e179b4-eba7-4aab-b0c2-e0f7eafe47ac · outbound

This paper cites Make-A-Video: Text-to-Video Generation without Text-Video Data.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Make-A-Video: Text-to-Video Generation without Text-Video Data

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.068937Z

Source-reported events for the cited work

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Observation 1c489a80-86e5-4ab7-ac51-649b990bb574 · outbound

This paper cites Object- stitch: Object compositing with diffusion model.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Object- stitch: Object compositing with diffusion model

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.077011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6529f11c-d287-4fac-953b-5ba1e316d623 · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Wan: Open and Advanced Large-Scale Video Generative Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.086406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 278b15de-6716-47bc-9cec-64043197d453 · outbound

This paper cites Disco: Disentangled control for realistic human dance generation.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Disco: Disentangled control for realistic human dance generation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:25.754803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4a87a7df-35ec-44e2-aade-c41a4a05309e · outbound

This paper cites UniAnimate: Taming Unified Video Diffusion Models for Consistent Human Image Animation.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence UniAnimate: Taming Unified Video Diffusion Models for Consistent Human Image Animation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.100015Z

Source-reported events for the cited work

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Observation 7c0d608a-10e5-46ef-bb4f-cd2c987a75c7 · outbound

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

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Drivedreamer: Towards real-world- drive world models for autonomous driving

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:25.729069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ba92fa14-71e3-428c-b3de-32b6294b2deb · outbound

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

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Panacea: Panoramic and controllable video generation for autonomous driving

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:25.703052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dc2bce14-12f2-4c6e-92cf-7911afe5a1cc · outbound

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

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:25.675918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 94803cd8-7bf2-4624-9192-3ae2a51a657e · outbound

This paper cites Magicanimate: Temporally consistent human im- age animation using diffusion model.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Magicanimate: Temporally consistent human im- age animation using diffusion model

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:25.655331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 96b44558-ee8b-4255-a4c8-8a9aadabf8c6 · outbound

This paper cites Effec- tive whole-body pose estimation with two-stages distillation.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Effec- tive whole-body pose estimation with two-stages distillation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:25.633887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5e7b4c7b-6062-441a-a41a-df15c7f93c68 · outbound

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

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.143215Z

Source-reported events for the cited work

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Observation 0d1e3167-947e-4909-94d5-33eb166a5415 · outbound

This paper cites IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.151569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbd7a803-d5ef-44d0-8883-ed06cf4491b6 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Adding conditional control to text-to-image diffusion models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.160399Z

Source-reported events for the cited work

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Observation b41ac559-04a8-4c33-b39c-e14d02517e70 · outbound

This paper cites MimicMotion: High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence MimicMotion: High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.167688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81c170be-a10b-40bd-b804-9404866298e7 · outbound

This paper cites Drivedreamer4d: World models are effective data machines for 4d driving scene rep- resentation.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Drivedreamer4d: World models are effective data machines for 4d driving scene rep- resentation

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:25.602121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5e484dbd-cf9a-43d9-a7ef-b36e74bcbdc8 · outbound

This paper cites Drivedreamer-2: Llm-enhanced world models for diverse driving video generation.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Drivedreamer-2: Llm-enhanced world models for diverse driving video generation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:25.581456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1441e9cf-66fc-4c77-bae3-035f902a7308 · outbound

This paper cites Open-Sora: Democratizing Efficient Video Production for All.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Open-Sora: Democratizing Efficient Video Production for All

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:25.189045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 302a763e-381b-46db-917f-d4535f5dba29 · outbound

This paper cites Champ: Controllable and consistent human image an- imation with 3d parametric guidance.

Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence Champ: Controllable and consistent human image an- imation with 3d parametric guidance

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:16:25.559561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.