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Paper Citation Record · LEDGER

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection

As of 19 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 1 inbound Pith citation observation for arXiv:2504.17076.

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

pith.paper-citation-record.v1
2504.17076 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:55:12.013650Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T16:10:16.251424Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T09:16:00.567003Z

Reference resolution

51 of 51 outbound references displayed

  • verified exact0
  • verified fuzzy36
  • unresolved14
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 834714ed-3ffe-4a5c-b0db-30e4e347ef9c · outbound

This paper cites Synthetic Data from Diffusion Models Improves ImageNet Classification.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Synthetic Data from Diffusion Models Improves ImageNet Classification

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:55:11.807771Z digest=sha256:78962eca8111930b12f32ea2418095e7bb49e96b862a4439ca6f11b0962819f6

Observation 09b2ac63-1a61-4f4e-afec-4226338ce430 · outbound

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

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection nuscenes: A multi- modal dataset for autonomous driving

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8ff3d98f-e982-4673-8236-1e037eec2e60 · outbound

This paper cites Smote: synthetic minority over- sampling technique.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Smote: synthetic minority over- sampling technique

Reference 3

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raw_fallback, observed 2026-08-16T10:55:12.812306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation db2517a9-b452-42d5-b8c9-adde46fdf5fb · outbound

This paper cites PixArt-\Sigma: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection PixArt-\Sigma: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e0d2a4d9-9afd-4498-bc9b-53f061e0769b · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:55:11.826965Z digest=sha256:b526e836d324f7baa677ed3016aff9b8e19d40081dae7ee9913768e93de7141f

Observation 0bfd3999-35b4-40e4-b2af-1c45b70aff9c · outbound

This paper cites Geodiffusion: Text- prompted geometric control for object detection data genera- tion.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Geodiffusion: Text- prompted geometric control for object detection data genera- tion

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:55:11.831504Z digest=sha256:82add0e15caa4a58ab4d34918087a4f31c9ba146373e9e226b66b9b8446abbc4

Observation eeabcf17-d682-4a12-b333-3a02661542ab · outbound

This paper cites MMDetection3D: Open- MMLab next-generation platform for general 3D object detection.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection MMDetection3D: Open- MMLab next-generation platform for general 3D object detection

Reference 7

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raw_fallback, observed 2026-08-16T10:55:12.788957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ec35d84c-3550-4bbe-b213-aa7e795d536a · outbound

This paper cites an unresolved cited work.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Unresolved cited work

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation be5fce6d-5d22-4c8e-bfa4-e8e8d2993625 · outbound

This paper cites Meta-sim2: Unsupervised learning of scene structure for synthetic data generation.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Meta-sim2: Unsupervised learning of scene structure for synthetic data generation

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.844273Z digest=sha256:e3d3b6909ea4b16dff800d9daf945393516e0c1ccfe545ccd6284e8fab7fb916

Observation 60d4acfe-335b-4d78-8d9d-120ae7aac27d · outbound

This paper cites On the importance of visual context for data augmentation in scene understanding.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection On the importance of visual context for data augmentation in scene understanding

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ad8af4c8-f353-42f1-9169-090a6b3d204f · outbound

This paper cites Cut, paste and learn: Surprisingly easy synthesis for instance de- tection.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Cut, paste and learn: Surprisingly easy synthesis for instance de- tection

Reference 11

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raw_fallback, observed 2026-08-16T10:55:12.733118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 073a595d-a67d-4ad0-ab9b-4a54c8218194 · outbound

This paper cites Divergen: Improv- ing instance segmentation by learning wider data distribu- tion with more diverse generative data.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Divergen: Improv- ing instance segmentation by learning wider data distribu- tion with more diverse generative data

Reference 12

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raw_fallback, observed 2026-08-16T10:55:12.719923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.856253Z digest=sha256:0554e159c0b2a39e2730f145f3b75f16effd4440818af20470532ea55b4f68e0

Observation e73a7fe2-cb19-4b19-87a0-f22f24c38cb3 · outbound

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

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection MagicDrive3D: Controllable 3D Generation for Any-View Rendering in Street Scenes

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:55:11.860136Z digest=sha256:307846f75dd94d5c0e578eb07762c444ebbedee0545a78c176460a9d211edf85

Observation 36d9dda1-f1e0-46a7-8703-d0de084c07d9 · outbound

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

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection MagicDrive: Street view generation with diverse 3d geometry control

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-16T10:55:12.705817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.864156Z digest=sha256:84f447ca4596d16cc65af1381df0a35fe80e4bdd0ede92b657772cd10c692af4

Observation bd1655fe-6bef-4a05-a487-723262db3d56 · outbound

This paper cites DALL-E for Detection: Language-driven Compositional Image Synthesis for Object Detection.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection DALL-E for Detection: Language-driven Compositional Image Synthesis for Object Detection

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:55:11.867980Z digest=sha256:e7b63a3024d3f6a94011107be36a528c8160831c27da886914dbc13a7c2f062f

Observation a820c8ca-b34b-4f8f-8305-ea5198f63203 · outbound

This paper cites Layout- transformer: Layout generation and completion with self- attention.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Layout- transformer: Layout generation and completion with self- attention

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:55:11.872083Z digest=sha256:c8eec17012636dfa7f4e4139b5045e75a7fe5c07fbe0630eb362e228743e8f9d

Observation ec2c00db-5fb0-4507-a552-0926c815d520 · outbound

This paper cites Adasyn: Adaptive synthetic sampling approach for imbal- anced learning.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Adasyn: Adaptive synthetic sampling approach for imbal- anced learning

Reference 17

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raw_fallback, observed 2026-08-16T10:55:12.683406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.875997Z digest=sha256:98d2cdbcddfe52ed7449f71c4ab452228e5ca48caf0deae9b37a2c3058722e90

Observation d614aeb1-7adf-4f18-8cab-e573790f41d0 · outbound

This paper cites Mask r-cnn.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Mask r-cnn

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.879814Z digest=sha256:751b6b573f1d98d0f874fdcb01a7233516b3a5568aca8ef731b7063ded3670e9

Observation 154a666b-64a2-4eba-bd41-c9e2f118943c · outbound

This paper cites Is synthetic data from generative models ready for image recognition? In International Conference on Learning Representations, 2023.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Is synthetic data from generative models ready for image recognition? In International Conference on Learning Representations, 2023

Reference 19

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raw_fallback, observed 2026-08-16T10:55:12.657273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 088beef5-df2a-41b3-8513-392f018d40ca · outbound

This paper cites Denoising dif- fusion probabilistic models.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Denoising dif- fusion probabilistic models

Reference 20

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raw_fallback, observed 2026-08-16T10:55:12.642992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 2c12b9ff-f40c-4812-be97-2b1f3c96d72e · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Lora: Low-rank adaptation of large language models

Reference 21

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raw_fallback, observed 2026-08-16T10:55:12.628763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.891457Z digest=sha256:56466205a0d9be4c3f3333ab0a8f87ed56aa592d335dc98afed91f6b030c8036

Observation 28bb93cc-0d8b-4819-847f-b0a8a26bf196 · outbound

This paper cites Layoutdm: Discrete diffusion model for controllable layout generation.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Layoutdm: Discrete diffusion model for controllable layout generation

Reference 22

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raw_fallback, observed 2026-08-16T10:55:12.614156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.895369Z digest=sha256:500292d5f6e38bd4b767ab8850a4f5d83e6fe0aa0a61d9dbe11f13ce88efb554

Observation 5e5082a3-5f0e-4cec-a32d-b946f4c70bf2 · outbound

This paper cites Layoutvae: Stochastic scene layout gen- eration from a label set.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Layoutvae: Stochastic scene layout gen- eration from a label set

Reference 23

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raw_fallback, observed 2026-08-16T10:55:12.600347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 43e060c4-0782-4068-ba24-321146a095b9 · outbound

This paper cites Meta-sim: Learning to generate synthetic datasets.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Meta-sim: Learning to generate synthetic datasets

Reference 24

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raw_fallback, observed 2026-08-16T10:55:12.587377Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.903004Z digest=sha256:27b78e647db5fd0e706ec431de49dcfc20eccdf33174da5460394f35e12162ea

Observation 696e3e70-186e-43cf-a7eb-66e33a0311de · outbound

This paper cites Segment any- 9 thing.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Segment any- 9 thing

Reference 25

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raw_fallback, observed 2026-08-16T10:55:12.573542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 411831c3-eb49-4734-a5c4-d87f97fc565f · outbound

This paper cites Blt: Bidirectional layout transformer for controllable layout generation.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Blt: Bidirectional layout transformer for controllable layout generation

Reference 26

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raw_fallback, observed 2026-08-16T10:55:12.560682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.911160Z digest=sha256:c59c39f525fc9960b54518c545416f04ba558af0fb5e4f21ebab8342bced1ba2

Observation dd282509-1eae-40c7-8ce7-5541f904a724 · outbound

This paper cites Dataset Enhancement with Instance-Level Augmentations.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Dataset Enhancement with Instance-Level Augmentations

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:55:11.915339Z digest=sha256:017a9d59256f342f8ca0da10ab04a3f38332142ba9c8c99effd9661c603a3390

Observation c796f23e-1b47-40c9-8a40-d838d123ec42 · outbound

This paper cites an unresolved cited work.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Unresolved cited work

Reference 28

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no resolver link, observed 2026-08-16T10:55:11.919947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:55:11.919947Z digest=sha256:03460a88ec04b70bd9fcafa10906cd0ee2d6a00646a855fdf1f805c1af08e1d1

Observation 6528bff4-88d2-4686-ad78-5083db726f20 · outbound

This paper cites Context-aware synthesis and placement of object instances.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Context-aware synthesis and placement of object instances

Reference 29

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raw_fallback, observed 2026-08-16T10:55:12.539572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.924017Z digest=sha256:a31d7e9bd0c163f6c7d696c295b779ce14452d2b68b7371b3f0389c6eb34562e

Observation 564e4eb7-34b1-44ec-bec8-63f8e5dbfc57 · outbound

This paper cites A simple background augmentation method for object detection with diffusion model.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection A simple background augmentation method for object detection with diffusion model

Reference 30

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raw_fallback, observed 2026-08-16T10:55:12.526978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.927978Z digest=sha256:22c5eb8f3f2c74dd6bc66e2fad9a75d99f6b12d66bdfa620538768fcc3922d1f

Observation 8964f47b-91a6-4203-a4e8-c2e420517b1b · outbound

This paper cites Lawrence Zitnick.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Lawrence Zitnick

Reference 31

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raw_fallback, observed 2026-08-16T10:55:12.514281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.932073Z digest=sha256:67108081af78685c819f9e0dc11a80eb5b9195e1762d2f7ab94e75a0d7c9d200

Observation 8811f19b-27a2-4743-9a95-a2a4a3bd272d · outbound

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

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models

Reference 32

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raw_fallback, observed 2026-08-16T10:55:12.501321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.936423Z digest=sha256:6b4df22cd706d3db70db2b9c128d8029b83de36b7cbf34a0edfb2953d91aa498

Observation 06dc6678-3292-4759-a9a1-2617cdbaccd3 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 33

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raw_fallback, observed 2026-08-16T10:55:12.488606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.940172Z digest=sha256:a5ed837c152485e06b99d912429003545516606ffef6cf8ca43c7d40f5c3b1cc

Observation 7ac9e934-92da-4822-b3bf-07bd9ddd84d4 · outbound

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

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection High-resolution image synthesis with latent diffusion models

Reference 34

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raw_fallback, observed 2026-08-16T10:55:12.475590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.944118Z digest=sha256:ce63216ac71099677de0580d9bbbb7c62bf0f4649fb947b4e8ee3c0995adb829

Observation b5dc13b5-6975-419c-83f6-5bb21b6fbb19 · outbound

This paper cites Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J

Reference 35

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 2f785cb3-a405-4831-a357-90bcce6d996e · outbound

This paper cites Gen2Det: Generate to Detect.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Gen2Det: Generate to Detect

Reference 36

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unresolved
no resolver link, observed 2026-08-16T10:55:11.952265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:55:11.952265Z digest=sha256:ebb65d20b7ff2b6eb90d96fd337eb8e5e28fef744cf6ed2eb7197acab208a60b

Observation 1feca054-1e0e-4963-b562-5247544de54c · outbound

This paper cites Scenegen: Learning to generate realistic traffic scenes.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Scenegen: Learning to generate realistic traffic scenes

Reference 37

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verified fuzzy
raw_fallback, observed 2026-08-16T10:55:12.450163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.956632Z digest=sha256:9f5646144fc370d42255a705b48680f223e751bd79fd19aad6c8f1f87db2d437

Observation c6f3aa12-e448-41c3-916d-d62440d324e3 · outbound

This paper cites DetDiffusion: Synergizing Generative and Perceptive Models for Enhanced Data Generation and Perception.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection DetDiffusion: Synergizing Generative and Perceptive Models for Enhanced Data Generation and Perception

Reference 38

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unresolved
no resolver link, observed 2026-08-16T10:55:11.960581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:55:11.960581Z digest=sha256:d6a6e0d699e0deb74db741ec3a7cfd962708b8929bd8578c7d0f43ec37494763

Observation de64bde8-7a9a-4675-b4f3-7754eee280c4 · outbound

This paper cites Datasetdm: Synthesizing data with perception annotations us- ing diffusion models.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Datasetdm: Synthesizing data with perception annotations us- ing diffusion models

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:55:12.436949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.964865Z digest=sha256:d1dad24fe0a18b605f3d5b43bd2c39cd3e373985ca1dad151ad81167f13820f6

Observation 3e5f490e-e970-4a3f-a739-193ff85911da · outbound

This paper cites Mosaicfusion: Diffusion models as data augmenters for large vocabulary instance segmentation.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Mosaicfusion: Diffusion models as data augmenters for large vocabulary instance segmentation

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:55:12.423754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.969168Z digest=sha256:faef8a1c86b77dcf01dd67dbb69e3920265160116c24495e8c83bd9c34fad635

Observation 6a7cfca4-6b16-4a76-a341-1bed04cf5137 · outbound

This paper cites Layouttransformer: Scene layout gen- eration with conceptual and spatial diversity.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Layouttransformer: Scene layout gen- eration with conceptual and spatial diversity

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:55:12.410685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.973124Z digest=sha256:5ccd796d8f663df2cc84bfc85d9e51ae5b7d82189e01468d33a0dcff9116d2d5

Observation 9d2ef9fb-e672-4ca3-9059-01f99e07333f · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Depth anything: Unleashing the power of large-scale unlabeled data

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:55:12.397398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.977132Z digest=sha256:07de8f1809d8c4ec146ec1f1a9c61a0e3a9f029d48481c26b24fc5ed8515608f

Observation 677f81fc-5f3a-45f6-88ac-2980ba948ef1 · outbound

This paper cites Dense prediction with attentive feature aggregation.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Dense prediction with attentive feature aggregation

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:55:12.384518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.981081Z digest=sha256:aacfb642a861aedbf097edb07e3c79bb590978e9999b4b21f420b525fb8c0bab

Observation 3dc30a53-7d9a-4fe2-8fc7-206a5df9af91 · outbound

This paper cites Bdd100k: A diverse driving dataset for heterogeneous mul- titask learning.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Bdd100k: A diverse driving dataset for heterogeneous mul- titask learning

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:55:12.370153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.985003Z digest=sha256:beafce26a4af68df018d0dd09d384db419247a38aef81150de48ae7f7c0c7411

Observation 938b9909-7040-4329-95e0-e10a6df23318 · outbound

This paper cites Generative lo- cation modeling for spatially aware object insertion.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Generative lo- cation modeling for spatially aware object insertion

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-16T10:55:11.989091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:55:11.989091Z digest=sha256:94382931bbbbd47b885847ec5c29ef05db23faec0b3757b6f2d8455583b8576b

Observation 5e67da9d-a0eb-429d-977a-ca9506177a9a · outbound

This paper cites Learning object placement by inpainting for compositional data augmentation.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Learning object placement by inpainting for compositional data augmentation

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:55:12.356256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.992970Z digest=sha256:7a3699d7dcebc0e2c443dafd41313f4ce254dcf64bb3b018abeb41ccf4801f70

Observation 051a89f9-c902-46f7-9094-774d1a19774a · outbound

This paper cites Adding conditional control to text-to-image diffusion models, 2023.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Adding conditional control to text-to-image diffusion models, 2023

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:55:12.343403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:11.997166Z digest=sha256:7e0b533f4b4eb63c8275895f7534c545cd61ffd0b4010a3c5264e65d3db7144e

Observation 8a7db830-60f5-40b7-9998-0cb5113802a3 · outbound

This paper cites DiffusionEngine: Diffusion Model is Scalable Data Engine for Object Detection.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection DiffusionEngine: Diffusion Model is Scalable Data Engine for Object Detection

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-16T10:55:12.001164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:55:12.001164Z digest=sha256:9c74fe7f98a106e3f3412ed014a7b6eec205df4111b3b6fdb1c47d6ba1e5a967

Observation e759f5ea-afcd-4492-a63f-8a971bfa4f20 · outbound

This paper cites X-paste: Revisiting scalable copy-paste for in- stance segmentation using clip and stablediffusion.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection X-paste: Revisiting scalable copy-paste for in- stance segmentation using clip and stablediffusion

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:55:12.329979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:12.005641Z digest=sha256:e600c281274247acc76551e187d7804c8b8e3a9d0bf7a2530a69101811ad84dd

Observation 2a636721-1700-456f-bc66-3dfbe1cfaea9 · outbound

This paper cites Using syn- thetic data for data augmentation to improve classification accuracy.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection Using syn- thetic data for data augmentation to improve classification accuracy

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T10:55:12.316377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:12.009691Z digest=sha256:6d02c077b3bb1bdbc222acd5a576435c239c7fb8c9fef5147d09fb3c018caf3e

Observation 9c011f0e-6a38-4c6f-8455-6cd9fb60f4e8 · outbound

This paper cites car”, “bus.

Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection car”, “bus

Reference 51

Resolution
malformed identifier
raw_fallback, observed 2026-08-16T10:55:12.302095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T10:55:12.013650Z digest=sha256:9d483c7041998b89fe4c32abb3b199970cc49cc599630562f43086595f98a7dd

Pith citing papers

Observation 3e3f404f-1f4d-4261-9091-e830cebe044a · inbound

HiddenObjects: Scalable Diffusion-Distilled Spatial Priors for Object Placement cites this paper.

HiddenObjects: Scalable Diffusion-Distilled Spatial Priors for Object Placement Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:16:00.570172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T16:10:16.251424Z digest=sha256:612aa442a145e2c3850f407c66d0bc819a4e1ba1b0a1ecfba402fdde8b74359a