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Paper Citation Record · LEDGER

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints

As of 8 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2506.13027.

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

pith.paper-citation-record.v1
2506.13027 v2

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:40:56.762496Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

26 of 26 outbound references displayed

  • verified exact1
  • verified fuzzy17
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c6207705-c378-4137-a48e-f70e998d1fe4 · outbound

This paper cites write newline.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:53.254781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:53.254781Z digest=sha256:d2f88fe489401f930946c1c218de34e40a2d1a7eb11ac62d49356d071d2742b2

Observation 0dd6398b-1705-4bf0-bdee-53709dc124f5 · outbound

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

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints End-to-end object detection with transformers

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:04.640576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:53.320590Z digest=sha256:be2aaa45fdf3a66578b56ed2eebf7a9f261038f18335bc20208c58c505fc91e7

Observation d48ce54d-2adb-4644-910f-b33cfaab2fd0 · outbound

This paper cites LW-DETR: A Transformer Replacement to YOLO for Real-Time Detection.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints LW-DETR: A Transformer Replacement to YOLO for Real-Time Detection

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:53.428144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:53.428144Z digest=sha256:81b4cf292e0fee13b4a91ae13478d75250fc940a26d7479ba8dc958125ff3a4e

Observation 239f6e76-7535-4a49-9f20-700eb379fbcf · outbound

This paper cites Ultralytics yolo11, 2024.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Ultralytics yolo11, 2024

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:53.555823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:53.555823Z digest=sha256:c56da795134ddb16e75cb352ecc649c2a832ccb09867989e7e195ade8683ee07

Observation 351171a6-4e6b-4099-b9be-de0080f80eba · outbound

This paper cites Ultralytics yolov8, 2023.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Ultralytics yolov8, 2023

Reference 5

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unresolved
no resolver link, observed 2026-08-07T00:40:53.726370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:53.726370Z digest=sha256:a2f7dafdf83cecc16c81f575c4e08028bfe23b7e187e42e4cb94c403efe69ff2

Observation f136ebe3-f8b7-445e-9488-74ed53dd3d25 · outbound

This paper cites Dn-detr: Accelerate detr training by introducing query denoising.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Dn-detr: Accelerate detr training by introducing query denoising

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:02.793309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:53.903002Z digest=sha256:f7783cb2e88aba6af1432470bf1f6380fcdaec5d759549072ed98a4681639f1d

Observation fe2bf999-e78d-4aa0-b081-5790fef484ff · outbound

This paper cites Crowdpose: Efficient crowded scenes pose estimation and a new benchmark.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Crowdpose: Efficient crowded scenes pose estimation and a new benchmark

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:00.687304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:54.076126Z digest=sha256:56876fda0f21c6d6bb19f2a04682727b3f5fef3f48c2bb3999d0a90ea13d1968

Observation 9529193e-383f-4ea2-aa46-b44278729952 · outbound

This paper cites Microsoft coco: Common objects in context.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Microsoft coco: Common objects in context

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:41:00.123991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:54.276804Z digest=sha256:bb23cbcb55e1956f078852696aac899c317e8fb5df2912c4cd09bffe793ce747

Observation e9401ec1-b414-4a69-94d0-4632228f7e24 · outbound

This paper cites Group pose: A simple baseline for end-to-end multi-person pose estimation.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Group pose: A simple baseline for end-to-end multi-person pose estimation

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:59.951708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:54.425050Z digest=sha256:262aedbfa9cdbc7ec9527536d6d93ea5540fb3446d73f0304ba762f0fe40872c

Observation ca444f40-cace-45c1-b00e-4fe5949ea157 · outbound

This paper cites RTMO : Towards high-performance one-stage real-time multi-person pose estimation, 2023.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints RTMO : Towards high-performance one-stage real-time multi-person pose estimation, 2023

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-07T00:40:59.765772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:54.572585Z digest=sha256:f3016e06957773e2d5a4dd165be0217ce1c74e9ba0420581c8c5fcb522279986

Observation d0c74356-504c-4e86-a35d-c5a741e5d8a6 · outbound

This paper cites Yolo-pose: Enhancing yolo for multi person pose estimation using object keypoint similarity loss.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Yolo-pose: Enhancing yolo for multi person pose estimation using object keypoint similarity loss

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:59.566551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:54.712726Z digest=sha256:b4b5bd9215c75646cade9e58b3dc431d816c4e0e1d37494340bb4b33d8b8a90c

Observation 86f3100d-7343-4ab7-9198-4710ca632a7b · outbound

This paper cites Fcpose: Fully convolutional multi-person pose estimation with dynamic instance-aware convolutions.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Fcpose: Fully convolutional multi-person pose estimation with dynamic instance-aware convolutions

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:59.404471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:54.842049Z digest=sha256:13bb40faccbcffa0984847ebc11ce7f6bcddf83ca8ea4799f74fd65cbd245304

Observation 5cf0f704-a3e2-49b4-abcc-38a61cf85c94 · outbound

This paper cites Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:40:57.008517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:54.985071Z digest=sha256:1fb598bf115178037336c2770c43abdb62ed0362e361ca2eaf55cd652b7a92d7

Observation e1643edb-bc8a-499e-a69d-95d6eb6867aa · outbound

This paper cites D-fine: Redefine regression task in detrs as fine-grained distribution refinement, 2024.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints D-fine: Redefine regression task in detrs as fine-grained distribution refinement, 2024

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:59.224515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:55.133553Z digest=sha256:5094c28ea1b317ffdf0fe9cd26cfdc77cda23c67eb1f9b7bd5ed70e6b0cb69c1

Observation 4d622f64-29e4-47d9-b0d1-f75bec1f6a9d · outbound

This paper cites an unresolved cited work.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-07T00:40:59.070348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:55.302540Z digest=sha256:488e0db67a524ee0725672a48f698f668224b596a4260bf05d006ecaf24c16cb

Observation f8be9f88-84d9-4ff5-b4bc-be44038a0405 · outbound

This paper cites Objects365: A large-scale, high-quality dataset for object detection.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Objects365: A large-scale, high-quality dataset for object detection

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:58.860532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:55.482482Z digest=sha256:5e4d4be6d270fd6b5bd5c94506141b5c5b342c3ceaaab5ded51bd81a848eb7b5

Observation d6a2cad3-5642-4f14-bdee-083112794648 · outbound

This paper cites Inspose: instance-aware networks for single-stage multi-person pose estimation.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Inspose: instance-aware networks for single-stage multi-person pose estimation

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:58.644530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:55.602919Z digest=sha256:42f038d9c5bcbdb3c7f22149ef03ea6be6619c0c1e9de8cefb828df89a877123

Observation 68255e8c-fded-4022-8ce8-80ee44d4e9f1 · outbound

This paper cites End-to-end multi-person pose estimation with transformers.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints End-to-end multi-person pose estimation with transformers

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:58.504935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:55.734201Z digest=sha256:a6d64858d79c0559426369bfc60b388f38c74c1b5f485c38500145879c0bf6ef

Observation 12b5fc83-c112-4307-b5cb-b03c8106085b · outbound

This paper cites Deim: Detr with improved matching for fast convergence, 2025.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Deim: Detr with improved matching for fast convergence, 2025

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:58.326461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:55.850441Z digest=sha256:e4bfb7c1a51192e24cd2037391cd70b9861aac4aea0a902212d912e3776bf04f

Observation 75016801-4602-4621-a966-913e895bfa27 · outbound

This paper cites DirectPose: Direct End-to-End Multi-Person Pose Estimation.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints DirectPose: Direct End-to-End Multi-Person Pose Estimation

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:56.025574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:56.025574Z digest=sha256:8560e948b1e68e06b459f970e03b2d27676a3843b9265e2dc0f2296bdf5da4a9

Observation 8544916f-3216-4ef0-9a32-39a698d68114 · outbound

This paper cites Contextual instance decoupling for robust multi-person pose estimation.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Contextual instance decoupling for robust multi-person pose estimation

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:58.139920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:56.146421Z digest=sha256:ff27c693ac3c160c5fd529416113c54fe07ab76b414ecebb3fee6bdfbc4b9f22

Observation 328b4cba-869c-4ea2-b16e-3c599488bec4 · outbound

This paper cites Querypose: Sparse multi-person pose regression via spatial-aware part-level query.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Querypose: Sparse multi-person pose regression via spatial-aware part-level query

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:57.887209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:56.275255Z digest=sha256:759bc921e84766d0d51c3265fd913029d18cf93f1a204134e0c97f22bbc3436a

Observation 30ac0f7f-011b-4df1-8af9-5ab2268a9f7b · outbound

This paper cites Explicit box detection unifies end-to-end multi-person pose estimation.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Explicit box detection unifies end-to-end multi-person pose estimation

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:57.529304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:56.405676Z digest=sha256:b9364368c3aceced8dc0b0d65d1773168b7f4cdb0b95b7f945cdf8d1eaed49b9

Observation 9315a06e-12af-44b1-9c1a-9dc61ddf3e7c · outbound

This paper cites Dino: Detr with improved denoising anchor boxes for end-to-end object detection.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Dino: Detr with improved denoising anchor boxes for end-to-end object detection

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:57.202325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:40:56.551294Z digest=sha256:b14253e2722a701187ce1d1efcc5464047c41ef2fc25cab41278eace9700034b

Observation 3b858d94-dbfc-4817-bd0a-a652550ca1d4 · outbound

This paper cites Detrs beat yolos on real-time object detection, 2023.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Detrs beat yolos on real-time object detection, 2023

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:56.697009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:56.697009Z digest=sha256:e1a62d29d96c11fc8b25fd88a25c2cdac336c34b68c8443d1550bf55c1d717ea

Observation 31fede08-80da-4cad-b799-902eadbb15cd · outbound

This paper cites Objects as Points.

DETRPose: Real-Time End-to-End Multi-Person Pose Estimation via Modified Transformer Decoder and Novel Denoising Keypoints Objects as Points

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:56.762496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:56.762496Z digest=sha256:a34988e6106655040082aafd1f3f385a43e3d9b9a1591b9efcafa84634a6aeda

Pith citing papers

No inbound Pith citation observations are available.