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Paper Citation Record · LEDGER

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective

As of 10 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 2 inbound Pith citation observations for arXiv:2507.16254.

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

pith.paper-citation-record.v1
2507.16254 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:18:09.953391Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T23:08:04.399168Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T12:51:23.704420Z

Reference resolution

55 of 55 outbound references displayed

  • verified exact0
  • verified fuzzy33
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 537e75a0-2328-4897-84ce-9c3e98c1b9fb · outbound

This paper cites Slicing aided hyper inference and fine-tuning for small object detection.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Slicing aided hyper inference and fine-tuning for small object detection

Reference 1

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation f535f060-2a96-4d5e-9c19-02ad4f0d3629 · outbound

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

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Synthetic Data from Diffusion Models Improves ImageNet Classification

Reference 2

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Observation 59a4a931-899a-417a-b185-fc4ebe49e880 · outbound

This paper cites Rain removal in traffic surveillance: Does it matter? IEEE Transactions on Intelligent Transportation Systems, 20(8):2802–2819, 2018.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Rain removal in traffic surveillance: Does it matter? IEEE Transactions on Intelligent Transportation Systems, 20(8):2802–2819, 2018

Reference 3

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Observation ebcddd61-bebb-42d8-a13b-afae15e2122a · outbound

This paper cites End-to- end object detection with transformers.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective End-to- end object detection with transformers

Reference 4

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Observation a4a78754-8091-4075-8924-d3d0154af839 · outbound

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

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation

Reference 5

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source=pdf_text observed=2026-08-06T15:18:06.011451Z digest=sha256:6be4eacd6cd31e2c50582d3d1cc4673c25f0ffd23fd93cf2d0c05bde7cfb9e4e

Observation af7351d6-2307-45ad-94a2-195c8401c7ad · outbound

This paper cites Region-Aware Text-to-Image Generation via Hard Binding and Soft Refinement.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Region-Aware Text-to-Image Generation via Hard Binding and Soft Refinement

Reference 6

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source=pdf_text observed=2026-08-06T15:18:06.126143Z digest=sha256:acd67bb96a4550cf2fb225617fe995b34c09c2367cc0626cd18598f2678faa0d

Observation 6f59fb92-15be-47e2-b95f-06d757c6048e · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Imagenet: A large-scale hierarchical image database

Reference 7

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source=pdf_text observed=2026-08-06T15:18:06.197508Z digest=sha256:c83f680d8fb3a5407832bfdffc3d25c7d09714a688c4c720a86629b6f66ba746

Observation e6ff9746-8277-4418-a4f8-936b7b25daab · outbound

This paper cites The unmanned aerial vehicle benchmark: Object detection and tracking.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective The unmanned aerial vehicle benchmark: Object detection and tracking

Reference 8

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 8fc5bf0c-8312-443e-a2b1-b4b7ff291c9f · outbound

This paper cites Visdrone-det2019: The vision meets drone ob- ject detection in image challenge results.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Visdrone-det2019: The vision meets drone ob- ject detection in image challenge results

Reference 9

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source=pdf_text observed=2026-08-06T15:18:06.360211Z digest=sha256:11c8bb1d87dacdd9cd8ad1fe180107742cb04cdd325f81f723735f96c70315e3

Observation ff9d5e05-f26a-4319-9c3f-b5cc0aac3605 · outbound

This paper cites Robust data augmen- tation and ensemble method for object detection in fisheye camera images.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Robust data augmen- tation and ensemble method for object detection in fisheye camera images

Reference 10

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Observation 85e1a9f5-259e-4620-a866-e018f1dde307 · outbound

This paper cites Sim- ple copy-paste is a strong data augmentation method for in- stance segmentation.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Sim- ple copy-paste is a strong data augmentation method for in- stance segmentation

Reference 11

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Observation 4e16fd1e-0511-4e10-bff1-07e3d00632d8 · outbound

This paper cites Fast r-cnn.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Fast r-cnn

Reference 12

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Observation 57c9084a-968b-4962-a2c0-cc1a6956dab3 · outbound

This paper cites Fisheye8k: A benchmark and dataset for fisheye camera object detection.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Fisheye8k: A benchmark and dataset for fisheye camera object detection

Reference 13

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation b573f621-05f3-47c2-ace2-655eb5a8c9d2 · outbound

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

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Is synthetic data from generative models ready for image recognition?

Reference 14

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Observation e7b27fb1-bbfe-44f5-8acf-dc1e9c9bd347 · outbound

This paper cites Ultralytics yolo11, 2024.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Ultralytics yolo11, 2024

Reference 15

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Observation ad84ed8a-1f6a-403b-98d2-3fc5508fbba4 · outbound

This paper cites Ultralytics YOLO, 2023.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Ultralytics YOLO, 2023

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation b26970de-b06c-412d-87e9-b85d0f34b7cd · outbound

This paper cites an unresolved cited work.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Unresolved cited work

Reference 17

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source=pdf_text observed=2026-08-06T15:18:07.014472Z digest=sha256:eff36532bbbe558adfe4287253ac66ee588d863850b473080a0fee346ad59343

Observation 00a0eca7-bffc-4f83-9027-8ac55168daa4 · outbound

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

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Gligen: Open-set grounded text-to-image generation

Reference 18

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Observation 01c62fb8-f815-43dc-b588-2f7764e61c69 · outbound

This paper cites Microsoft coco: Common objects in context.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Microsoft coco: Common objects in context

Reference 19

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Observation 14b94772-dd7f-4ce4-8ce3-7dcf8dc95bfd · outbound

This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Grounding dino: Marrying dino with grounded pre-training for open-set object detection

Reference 20

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation b8c2b4b0-c829-4aad-9a72-905cf6d7ddea · outbound

This paper cites RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer

Reference 21

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source=pdf_text observed=2026-08-06T15:18:07.424734Z digest=sha256:89ca18bf6863622a4ddcb4f135881329b54cb67fc8ad4de5ca360d8751c2c988

Observation 28c68384-db9a-4a10-b9bb-44e3d6f5343e · outbound

This paper cites Dataset diffusion: Diffusion-based synthetic data generation for pixel-level semantic segmentation.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Dataset diffusion: Diffusion-based synthetic data generation for pixel-level semantic segmentation

Reference 22

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Observation 1f21dabc-18c9-48d7-ab4f-e2c58dc4792c · outbound

This paper cites Gpt-4.1, 2024.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Gpt-4.1, 2024

Reference 23

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation d16382af-f5e7-4ce1-8e62-f46860cdb39b · outbound

This paper cites D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement

Reference 24

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source=pdf_text observed=2026-08-06T15:18:07.613301Z digest=sha256:796d0821cba3a0f35c1da1a1df3f5d2baf88ce3e5051a1f11c5808e13d432981

Observation 4aa5875b-ff0d-45e0-a510-4e24e30261e9 · outbound

This paper cites Improving object detection to fisheye cameras with open-vocabulary pseudo- label approach.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Improving object detection to fisheye cameras with open-vocabulary pseudo- label approach

Reference 25

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Observation f0225bd9-0900-4854-b047-b0d3be055549 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective SAM 2: Segment Anything in Images and Videos

Reference 26

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source=pdf_text observed=2026-08-06T15:18:07.723930Z digest=sha256:7bc34f9b78f090ee106dbc4a7bb90f9b5c05aa9b79f19eab203fee6f9bf516a4

Observation b8edeec9-423d-4374-a861-d38ef2b1eadc · outbound

This paper cites You only look once: Unified, real-time object de- tection.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective You only look once: Unified, real-time object de- tection

Reference 27

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source=pdf_text observed=2026-08-06T15:18:07.834930Z digest=sha256:d5978538f4d3c390cbe23dc5709577c48a97e7cd51421c5300176113805c4d1a

Observation 660aaf07-0eeb-4749-b7d6-da4c99a289f2 · outbound

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

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective High-resolution image synthesis with latent diffusion models

Reference 28

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source=pdf_text observed=2026-08-06T15:18:07.907164Z digest=sha256:55ae2929f0f65850b8d485d5346c6972f7f658999ef06b1443055defde841319

Observation c4fdacbf-ea5f-488b-ac12-2e3297172e2c · outbound

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

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Photorealistic text-to-image diffusion models with deep language understanding

Reference 29

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source=pdf_text observed=2026-08-06T15:18:07.981866Z digest=sha256:f2d8bfa72ede6dbdc5c3ad9db61e9ea20cdb50d6ff160a59c96c4ed1e1cc2e4d

Observation 2c277bb3-e219-449a-acc6-d27d77e534f5 · outbound

This paper cites Better aggregation in test-time augmentation.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Better aggregation in test-time augmentation

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:08.040350Z digest=sha256:edeadbdada89b9103894bc9c47b92a24b7e6bb6ed7e08ab98420dab72b9dfa57

Observation fccfa956-1bb1-49ef-9247-d8ed62e85f5d · outbound

This paper cites Road object detection robust to distorted objects at the edge regions of images.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Road object detection robust to distorted objects at the edge regions of images

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:08.113911Z digest=sha256:68384133ecae7cf42198b5a521559ec05720c73068851cc53b7e8e900481c8ea

Observation 7d7dfbea-a64a-462b-b9b1-72b140b0ce52 · outbound

This paper cites Weighted boxes fusion: Ensembling boxes from different ob- ject detection models.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Weighted boxes fusion: Ensembling boxes from different ob- ject detection models

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:08.209045Z digest=sha256:a10b8f22d6d56d68d804de1f188ce3e805c54b6b34eab17d96948eab27e4d17f

Observation 35f4cfdd-b09b-4a57-8a4f-20fcdd8795eb · outbound

This paper cites Aerogen: Enhancing remote sensing object detection with diffusion-driven data generation.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Aerogen: Enhancing remote sensing object detection with diffusion-driven data generation

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:08.284224Z digest=sha256:98135d462fd851ab704e35026389cf30517840c32fc62322931cf20e2c7675bf

Observation d8a1dd72-72c1-48d2-8a29-602f1d79669f · outbound

This paper cites You Only Learn One Representation: Unified Network for Multiple Tasks.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective You Only Learn One Representation: Unified Network for Multiple Tasks

Reference 34

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source=pdf_text observed=2026-08-06T15:18:08.334547Z digest=sha256:09b07e89ecd3dd8b6f98ee48598f180c7ee06b8e55116e11ccec9a9a276efcfb

Observation 1a4df800-cd62-49a7-a03f-75a861ede26b · outbound

This paper cites Yolov9: Learning what you want to learn using pro- grammable gradient information.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Yolov9: Learning what you want to learn using pro- grammable gradient information

Reference 35

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raw_fallback, observed 2026-08-06T15:18:12.926381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:08.421986Z digest=sha256:8624605eb9af2c282ccee956b3031974a5de150c8ad6e54a23f2037086fe15b2

Observation 6a70b3b2-80bb-4090-aa3f-2442ad1a128f · outbound

This paper cites Exploiting diffusion prior for real-world image super-resolution.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Exploiting diffusion prior for real-world image super-resolution

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:12.914277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:08.490876Z digest=sha256:0ba7c640538d16284c6c83141b4c3dcbd50760ff1bf0a808e55e094dc99fd81f

Observation f49da897-9b69-4c74-ab85-4c040a3f4b2b · outbound

This paper cites The 8th ai city challenge.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective The 8th ai city challenge

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:12.900576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:08.572641Z digest=sha256:c00e8ca42931303140631f215bc68a2641a8e2aff297381e77dd233a1afbeae6

Observation ce214b7f-1be4-4e11-8e77-34fdd0df7fa4 · outbound

This paper cites Internimage: Exploring large-scale vi- sion foundation models with deformable convolutions.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Internimage: Exploring large-scale vi- sion foundation models with deformable convolutions

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:12.886201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:08.667761Z digest=sha256:0edb277252f1c6505801049739cfbe965e7bac272cbe224471450314f0a0abba

Observation 1ab8d84b-c06f-451f-8ebc-df68bd6ef2d5 · outbound

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

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Instancediffusion: Instance- level control for image generation

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:12.796665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:08.737525Z digest=sha256:3aea7aa520ecce0ea72eabfd7729e1efe8b3d5da88be636b73d5da09cfb80ff7

Observation ffdd9fc2-e243-420b-9f0d-fbf3b45fe45d · outbound

This paper cites Ua-detrac: A new benchmark and protocol for multi-object detection and tracking.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Ua-detrac: A new benchmark and protocol for multi-object detection and tracking

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:12.618534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:08.766143Z digest=sha256:ac0fdb7f65753a558ef8492404da6d827b153a26e9e72bfcd0484776bb8b8776

Observation 3da5c2f4-4b30-460d-a9fe-102d33fa3ecc · outbound

This paper cites Datasetdm: Synthesizing data with perception annota- tions using diffusion models.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Datasetdm: Synthesizing data with perception annota- tions using diffusion models

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:12.363046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:08.836472Z digest=sha256:b8d60a6c08ca437d1ab59426ae55ff24044bbbdd15a6f074fc8bb8158c991c97

Observation fe60728a-c428-44e1-bc94-7a586988e323 · outbound

This paper cites Diffumask: Synthesizing images with pixel-level annotations for semantic segmentation using dif- fusion models.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Diffumask: Synthesizing images with pixel-level annotations for semantic segmentation using dif- fusion models

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:12.079805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:08.908271Z digest=sha256:b2d46f8feaf41bc901334fca785c9faebbf4e9073d4f49e61b6dc80e09bdc0e5

Observation 707bf371-b52e-4be0-ba8c-455f7740bb77 · outbound

This paper cites A Comprehensive Overview of Fish-Eye Camera Distortion Correction Methods.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective A Comprehensive Overview of Fish-Eye Camera Distortion Correction Methods

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T15:18:08.980744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:08.980744Z digest=sha256:e7c2251898aa4eb92cc051483ebf71ec538fa0714e1f2319be06640a968a1d06

Observation 27d0308d-20da-463a-bf27-178b0bd5fc05 · outbound

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

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Reco: Region-controlled text-to-image genera- tion

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T15:18:09.053555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:09.053555Z digest=sha256:6eaa4f7bbf45096073018273aacd331d6fc5ec5a8cdcff715dc986af6365605c

Observation 5216b767-0fc6-458d-8f8a-e789fc79b3e1 · outbound

This paper cites Navigating text- to-image customization: From lycoris fine-tuning to model evaluation.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Navigating text- to-image customization: From lycoris fine-tuning to model evaluation

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:11.816844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:09.120145Z digest=sha256:d50336176ca196af451753b1a8b2f23802aaba990faafac2a37c0ff941b85c1d

Observation 61b92aae-a01b-415e-9237-6a1b07474364 · outbound

This paper cites Detrs beat yolos on real-time object detection.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Detrs beat yolos on real-time object detection

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:11.620746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:09.215941Z digest=sha256:9b0ab5bce245e8d6cd5f4df0b34a80e5f21af2bb9bbf1667dd3eb09f25a11d56

Observation c1f9b954-ffca-4828-9fdf-4e5211b2c077 · outbound

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

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Migc: Multi-instance generation controller for text-to-image synthesis

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:11.383702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:09.282993Z digest=sha256:55aa028300f25ab8eceb45253c36c0f1a05c28e4ed8ef3063076fc17113fe252

Observation f6aa84b8-ba90-42cc-9005-615f5c732c5b · outbound

This paper cites DreamRenderer: Taming Multi-Instance Attribute Control in Large-Scale Text-to-Image Models.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective DreamRenderer: Taming Multi-Instance Attribute Control in Large-Scale Text-to-Image Models

Reference 48

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unresolved
no resolver link, observed 2026-08-06T15:18:09.380382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:09.380382Z digest=sha256:70a9d1f72a5f1b26f54b35060f9d28d25f6faeedf41ef1d62c71dabde56f2b2f

Observation da3fab33-2813-4342-ae49-66c65a8daba1 · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 49

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no resolver link, observed 2026-08-06T15:18:09.464197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:09.464197Z digest=sha256:703717d604ae17f7a16f56bcc404e1cfcc4922ef3edf7767126d288aa9f6b860

Observation 032d00b4-e604-4a66-962d-dd9c01c88002 · outbound

This paper cites Unpaired image-to-image translation using cycle- consistent adversarial networks.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Unpaired image-to-image translation using cycle- consistent adversarial networks

Reference 50

Resolution
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no resolver link, observed 2026-08-06T15:18:09.555859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:09.555859Z digest=sha256:2fc28162049f9e9835f5ed690be0bfb020ba6eb7e51e0873d7ac69f286023c6e

Observation c9293b07-cd62-48ce-a00d-d1677b660f61 · outbound

This paper cites Detrs with col- laborative hybrid assignments training.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Detrs with col- laborative hybrid assignments training

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:11.106860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:09.633565Z digest=sha256:9a0bb64fd5f0cb81abb463a613e359dd0ce3b80225e724dc3d8017352eec65c1

Observation 6356e0e7-175a-444b-b0a8-a0b578e1410f · outbound

This paper cites We specifically guided the model to ensure that the base captions included the key objects targeted in the fisheye dataset.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective We specifically guided the model to ensure that the base captions included the key objects targeted in the fisheye dataset

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:10.903573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:09.720173Z digest=sha256:7e1468a2138d325024ebbe9351653b2bfa20566047ca9e2784a59722a6fb8c3d

Observation e32549b8-0dc4-48e8-a184-ec54f38541cb · outbound

This paper cites These prompts were given to GPT-4.1-mini to rewrite base captions that are originally extracted from real data so that they better describe the types of images we aimed to generate.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective These prompts were given to GPT-4.1-mini to rewrite base captions that are originally extracted from real data so that they better describe the types of images we aimed to generate

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:10.609893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:09.796638Z digest=sha256:05bf31174cfe7bdfbc522dd188c81b99ca4e73f87fc36c837db095960d847413

Observation 5303c14f-72d7-40e5-bd1d-9dba32b20169 · outbound

This paper cites Figure 1 presents five representative examples, where each column compares images generated from the base pre-trained model (top) and our fine-tuned model (bottom).

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Figure 1 presents five representative examples, where each column compares images generated from the base pre-trained model (top) and our fine-tuned model (bottom)

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:10.363959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:09.896027Z digest=sha256:ed83da38582edbbc52c442650fc01bfd245fe7a8ab4d39aec7db6cb09fe7778d

Observation 5c08337d-66e3-4560-8e46-2af66237a990 · outbound

This paper cites Figure 2 shows that as the synthetic data improves, both false positives and false negatives are gradually reduced, indicating more accurate and confident detection.

Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective Figure 2 shows that as the synthetic data improves, both false positives and false negatives are gradually reduced, indicating more accurate and confident detection

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:10.212238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:18:09.953391Z digest=sha256:df39c4f84e77caed9f0faac2d2e7869c6ecb59f6ca4da53675784e2fb2cae056

Pith citing papers

Observation 606f1cdf-6290-4dd4-a389-3f2079f70259 · inbound

Towards Continual Expansion of Data Coverage: Automatic Text-guided Edge-case Synthesis cites this paper.

Towards Continual Expansion of Data Coverage: Automatic Text-guided Edge-case Synthesis Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-18T12:51:23.706838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T12:46:25.942761Z digest=sha256:aae61c9420b30031276d2c23228737d32783f1efc68caa45c321bcaeae1213ec

Observation bdda10fb-9454-445a-b9df-6991706834a1 · inbound

Physics-aware Masked Diffusion-based Flood Simulation for Urban Fisheye Disaster Detection cites this paper.

Physics-aware Masked Diffusion-based Flood Simulation for Urban Fisheye Disaster Detection Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-01T23:08:04.399168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T23:08:04.399168Z digest=sha256:367146cec2e409ac16f0db1389a9c856c753bf5d7042b210331d70735b591aa4