Paper Citation Record · LEDGER

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation

As of 19 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 7 inbound Pith citation observations for arXiv:2411.15497.

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

pith.paper-citation-record.v1
2411.15497 v3

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

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measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:45:56.589082Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T00:48:24.776038Z

Reference resolution

47 of 47 outbound references displayed

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External citation measurements

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Outbound references

Observation d9b95d20-ecd7-41d2-b5ac-eebb313e5822 · outbound

This paper cites Auto Cherry-Picker: Learning from High-quality Generative Data Driven by Language.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Auto Cherry-Picker: Learning from High-quality Generative Data Driven by Language

Reference 1

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Observation cf6ebf13-d54f-494d-acfa-8174ae9a7fdc · outbound

This paper cites Anchor-free oriented proposal generator for object detection.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Anchor-free oriented proposal generator for object detection

Reference 2

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Observation 89e41d5d-7202-4e45-96c4-afda0a465942 · outbound

This paper cites A review of medical image data augmentation techniques for deep learning appli- cations.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation A review of medical image data augmentation techniques for deep learning appli- cations

Reference 3

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Observation 2d8d9c6d-2290-4b04-9028-d28ce228dc0c · outbound

This paper cites Mr im- age denoising and super-resolution using regularized reverse diffusion.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Mr im- age denoising and super-resolution using regularized reverse diffusion

Reference 4

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Observation 18c8b70d-a469-4e7b-b720-b204d5fd43d2 · outbound

This paper cites Style injec- tion in diffusion: A training-free approach for adapting large- scale diffusion models for style transfer.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Style injec- tion in diffusion: A training-free approach for adapting large- scale diffusion models for style transfer

Reference 5

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Observation ccba755e-695c-4cc4-95f1-014d81ea99ee · outbound

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

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Cut, paste and learn: Surprisingly easy synthesis for instance de- tection

Reference 6

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Observation 6f838fa5-55b2-4991-9298-3b1f6a63b252 · outbound

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

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Divergen: Improv- ing instance segmentation by learning wider data distribu- tion with more diverse generative data

Reference 7

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Observation 4c744aed-5a79-432a-91fd-153de23e0d65 · outbound

This paper cites Learned representation-guided diffusion models for large-image generation.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Learned representation-guided diffusion models for large-image generation

Reference 8

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Observation 249f2259-386e-43c9-bc53-6d5f84caf76c · outbound

This paper cites Lvis: A dataset for large vocabulary instance segmentation.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Lvis: A dataset for large vocabulary instance segmentation

Reference 9

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Observation caccb2df-74c8-4bf7-a9f4-dda1f8d2e994 · outbound

This paper cites Deep residual learning for image recognition.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Deep residual learning for image recognition

Reference 10

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Observation 0fb8df8d-7bf6-4f12-81bb-db11b901b8e1 · outbound

This paper cites Denoising dif- fusion probabilistic models.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Denoising dif- fusion probabilistic models

Reference 11

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Observation 0667d237-9efb-4a8f-855e-f72cf9110f04 · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Imagen Video: High Definition Video Generation with Diffusion Models

Reference 12

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Observation 27b7a282-976f-45e3-ba3b-4b53bce281ca · outbound

This paper cites Diffusionsat: A generative foundation model for satellite imagery.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Diffusionsat: A generative foundation model for satellite imagery

Reference 13

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Observation f97a9218-297c-4ef6-9bed-28dd9f3cd328 · outbound

This paper cites Augmentation for small object detection.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Augmentation for small object detection

Reference 14

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Source-reported events for the cited work

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Observation c87980c0-a257-41db-9f3a-8ebcee740fe0 · outbound

This paper cites Object detection in optical remote sensing images: A survey and a new benchmark.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Object detection in optical remote sensing images: A survey and a new benchmark

Reference 15

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Observation 02290cea-d945-4a02-b3bc-cafcc8d213e3 · outbound

This paper cites Gligen: Open-set grounded text-to-image generation.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Gligen: Open-set grounded text-to-image generation

Reference 16

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Source-reported events for the cited work

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Observation 627a5c9e-9e92-4272-aa52-80b0929932e8 · outbound

This paper cites A Simple Background Augmentation Method for Object Detection with Diffusion Model.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation A Simple Background Augmentation Method for Object Detection with Diffusion Model

Reference 17

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Observation ef9b231b-77e9-4822-a3d8-b0610329005f · outbound

This paper cites Image synthesis from layout with locality- aware mask adaption.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Image synthesis from layout with locality- aware mask adaption

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:40.320415Z

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Observation cadf4d22-4e99-4a48-99c8-c3871d6151fe · outbound

This paper cites Re- moteclip: A vision language foundation model for remote sensing.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Re- moteclip: A vision language foundation model for remote sensing

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:40.308240Z

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Observation 8d70d1a4-6180-49ca-965d-8f2ed113eafd · outbound

This paper cites Ssd: Single shot multibox detector.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Ssd: Single shot multibox detector

Reference 20

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Observation 61b80040-eb18-4211-ab9f-530d9c9b57a3 · outbound

This paper cites Ship rotated bounding box space for ship extraction from high-resolution optical satellite images with complex back- grounds.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Ship rotated bounding box space for ship extraction from high-resolution optical satellite images with complex back- grounds

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:40.284196Z

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Observation 7248e6f1-59e2-4add-9f06-3ee35197219e · outbound

This paper cites Decoupled Weight Decay Regularization.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Decoupled Weight Decay Regularization

Reference 22

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Observation 2c91402a-c960-4c3a-b264-5fe21714ebcd · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view syn- thesis.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Nerf: Representing scenes as neural radiance fields for view syn- thesis

Reference 23

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AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Improved denoising diffusion probabilistic models

Reference 24

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Observation 13baf44e-bd34-4183-b4ca-eeadf734870c · outbound

This paper cites HSIGene: A Foundation Model For Hyperspectral Image Generation.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation HSIGene: A Foundation Model For Hyperspectral Image Generation

Reference 25

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Observation f6ea89a3-d969-4004-ad46-170c408eb01d · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 26

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Observation 30085d00-8ef3-4a68-a6dc-b8e211856d83 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Learn- ing transferable visual models from natural language super- vision

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:40.263804Z

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Observation 39d221fc-7efb-419a-bd84-1dac9dd60f56 · outbound

This paper cites Classification accuracy score for conditional generative models.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Classification accuracy score for conditional generative models

Reference 28

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Observation 7bafe379-144c-4532-996c-ff1331f5e676 · outbound

This paper cites Generative ad- versarial text to image synthesis.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Generative ad- versarial text to image synthesis

Reference 29

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Observation a5eae80f-b5fd-4a51-822e-d1bd313d608a · outbound

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

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation High-resolution image synthesis with latent diffusion models

Reference 30

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Observation 642150fc-2e5f-45ec-9d3d-52e70535a4da · outbound

This paper cites Image synthesis from reconfig- urable layout and style.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Image synthesis from reconfig- urable layout and style

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:40.232230Z

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Observation 462627be-4152-4795-9f92-ac77a0f2583e · outbound

This paper cites Crs-diff: Controllable remote sensing image generation with diffusion model.IEEE Transactions on Geoscience and Remote Sensing , 2024.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Crs-diff: Controllable remote sensing image generation with diffusion model.IEEE Transactions on Geoscience and Remote Sensing , 2024

Reference 32

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Observation 51e3e421-63de-4177-a54c-7009f63092a6 · outbound

This paper cites Satsynth: Augmenting image-mask pairs through diffusion models for aerial semantic segmentation.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Satsynth: Augmenting image-mask pairs through diffusion models for aerial semantic segmentation

Reference 33

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Observation c5757467-14f3-4cdb-8410-4733af88d73b · outbound

This paper cites Yolov8: A novel object detection algorithm with enhanced performance and robust- ness.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Yolov8: A novel object detection algorithm with enhanced performance and robust- ness

Reference 34

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Observation ff6ef43a-cc51-4f74-ac8b-c98c5a89af38 · outbound

This paper cites Instancediffusion: Instance- level control for image generation.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Instancediffusion: Instance- level control for image generation

Reference 35

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Observation e3df3eb0-c78d-40ed-b5ef-db7e7c5d785d · outbound

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AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Stylediffusion: Controllable disentangled style transfer via diffusion models

Reference 36

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Observation c0dae777-5d7d-4bb0-9bd5-f96d447d1186 · outbound

This paper cites Oriented r-cnn for object detection.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Oriented r-cnn for object detection

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:40.179634Z

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Observation b9ab3f18-a3fe-4761-951e-cd39ea571554 · outbound

This paper cites Reco: Region-controlled text-to-image genera- tion.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Reco: Region-controlled text-to-image genera- tion

Reference 38

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This paper cites Stack- gan: Text to photo-realistic image synthesis with stacked generative adversarial networks.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Stack- gan: Text to photo-realistic image synthesis with stacked generative adversarial networks

Reference 39

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Source-reported events for the cited work

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Observation 65cb343f-9e07-4e71-a7da-78f6de8cc30f · outbound

This paper cites How well do deep learning-based methods for land cover classification and object detection perform on high resolu- tion remote sensing imagery? Remote Sensing, 12(3):417,.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation How well do deep learning-based methods for land cover classification and object detection perform on high resolu- tion remote sensing imagery? Remote Sensing, 12(3):417,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:40.159089Z

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Observation 0fd43151-c5de-4d48-ba32-df97cabfcf01 · outbound

This paper cites X-paste: Revisiting scalable copy- paste for instance segmentation using clip and stablediffu- sion.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation X-paste: Revisiting scalable copy- paste for instance segmentation using clip and stablediffu- sion

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:40.149224Z

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Observation 54913b2c-29f7-434a-92ec-ee3c369d7ff4 · outbound

This paper cites Layoutdiffusion: Controllable diffu- sion model for layout-to-image generation.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Layoutdiffusion: Controllable diffu- sion model for layout-to-image generation

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:40.139856Z

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Observation 7a9b1695-7ad3-48c9-bd57-c84f91906e62 · outbound

This paper cites Building damage assessment for rapid dis- aster response with a deep object-based semantic change de- tection framework: From natural disasters to man-made dis- asters.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Building damage assessment for rapid dis- aster response with a deep object-based semantic change de- tection framework: From natural disasters to man-made dis- asters

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Observation a46ca8e4-e1cc-4d73-bad0-40c7976b569e · outbound

This paper cites Changen2: Multi-temporal re- mote sensing generative change foundation model.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Changen2: Multi-temporal re- mote sensing generative change foundation model

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Source-reported events for the cited work

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Observation 3c64103b-7a18-45f6-9183-8d243119f4a3 · outbound

This paper cites Migc: Multi-instance generation controller for text-to-image synthesis.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Migc: Multi-instance generation controller for text-to-image synthesis

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:40.121038Z

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Observation 8b44a823-8e22-4812-bd8c-9b4e1dc44fc6 · outbound

This paper cites ODGEN: Domain-specific Object Detection Data Generation with Diffusion Models.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation ODGEN: Domain-specific Object Detection Data Generation with Diffusion Models

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Observation a843afe3-cddc-460d-ab96-7321b0db3f8b · outbound

This paper cites Object detection in 20 years: A survey.Proceed- ings of the IEEE, 111(3):257–276, 2023.

AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation Object detection in 20 years: A survey.Proceed- ings of the IEEE, 111(3):257–276, 2023

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:40.109195Z

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Pith citing papers

Observation c1dc5294-7f8a-4e7a-93e3-a4e9108ec70f · inbound

CC-Diff: Enhancing Contextual Coherence in Remote Sensing Image Synthesis cites this paper.

CC-Diff: Enhancing Contextual Coherence in Remote Sensing Image Synthesis AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation

Reference 41

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Observation 238cfac1-1244-4d88-abc9-7c34c97eec28 · inbound

EarthSynth: Generating Informative Earth Observation with Diffusion Models cites this paper.

EarthSynth: Generating Informative Earth Observation with Diffusion Models AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation

Reference 17

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Observation f4e4fc41-02bc-4e5b-93d5-9785bb849e3f · inbound

FICGen: Frequency-Inspired Contextual Disentanglement for Layout-driven Degraded Image Generation cites this paper.

FICGen: Frequency-Inspired Contextual Disentanglement for Layout-driven Degraded Image Generation AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-05T12:59:26.738411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1222e3b-f608-40cc-becd-2ad9958d8a84 · inbound

SHARP: Spectrum-aware Highly-dynamic Adaptation for Resolution Promotion in Remote Sensing Synthesis cites this paper.

SHARP: Spectrum-aware Highly-dynamic Adaptation for Resolution Promotion in Remote Sensing Synthesis AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-15T00:48:24.778131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cf1bbe57-ca25-45c1-a657-64b3b64c2ce1 · inbound

SHARP: Spectrum-aware Highly-dynamic Adaptation for Resolution Promotion in Remote Sensing Synthesis cites this paper.

SHARP: Spectrum-aware Highly-dynamic Adaptation for Resolution Promotion in Remote Sensing Synthesis AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-14T20:17:28.243545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28146605-edde-44e1-8bb7-a6a618300b6a · inbound

Class-specific diffusion models improve military object detection in a low-data domain cites this paper.

Class-specific diffusion models improve military object detection in a low-data domain AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:15:22.996101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 441c8a01-cda1-498a-9988-ccda0b90b33e · inbound

HarmoniDiff-RS: Training-Free Diffusion Harmonization for Satellite Image Composition cites this paper.

HarmoniDiff-RS: Training-Free Diffusion Harmonization for Satellite Image Composition AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:26:11.421716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.