Paper Citation Record · LEDGER

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization

As of 9 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2507.12420.

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

pith.paper-citation-record.v1
2507.12420 v2

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:56:56.783905Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

39 of 39 outbound references displayed

verified exact0
verified fuzzy33
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b1dab3d-f3a2-4817-8197-5470c8dd6212 · outbound

This paper cites Yolov4: Optimal speed and accuracy of object detection, 2020.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Yolov4: Optimal speed and accuracy of object detection, 2020

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:03.522230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5c14a848-13ac-420a-a73c-31fb01240f1f · outbound

This paper cites A method of object detection with attention mechanism and c2f dcnv2 for complex traffic scenes.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization A method of object detection with attention mechanism and c2f dcnv2 for complex traffic scenes

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:03.353347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fec985e2-1247-46df-8856-75f1849b4ee3 · outbound

This paper cites Visdrone-det2021: The vision meets drone object de- tection challenge results.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Visdrone-det2021: The vision meets drone object de- tection challenge results

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:03.198212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2cd626d9-9ca6-4826-882f-8ace419077a1 · outbound

This paper cites Dynamic correlation learn- ing and regularization for multi-label confidence calibration.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Dynamic correlation learn- ing and regularization for multi-label confidence calibration

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:03.073464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1a4c19d4-6e49-40eb-8b2b-bafa832d3195 · outbound

This paper cites Object detection for autonomous vehicles under adverse weather conditions.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Object detection for autonomous vehicles under adverse weather conditions

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:02.919079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d821a3f1-febb-4194-99c1-54f527d7fdd8 · outbound

This paper cites A virtually as- sisted digital twin enabled object detection in smart indus- trial manufacturing.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization A virtually as- sisted digital twin enabled object detection in smart indus- trial manufacturing

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:02.781499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5af626cb-d3e2-45b2-b9be-95741bd65275 · outbound

This paper cites Dynamic fea- ture and context enhancement network for faster detection of small objects.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Dynamic fea- ture and context enhancement network for faster detection of small objects

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:02.614951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 10a4f02d-f10a-41f3-b463-a8d13244270d · outbound

This paper cites Adaptive feature fusion and task-dynamic alignment for real-time object detection on edge devices.Ex- pert Systems with Applications, 290:128341, 2025.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Adaptive feature fusion and task-dynamic alignment for real-time object detection on edge devices.Ex- pert Systems with Applications, 290:128341, 2025

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:02.437653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 97bae662-74f5-43c5-863e-c81ed3d56cc9 · outbound

This paper cites Everingham, S.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Everingham, S

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:02.300313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ddba1a12-7f02-41df-89ee-cc6929179278 · outbound

This paper cites Lud-yolo: A novel lightweight object detection network for unmanned aerial vehicle.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Lud-yolo: A novel lightweight object detection network for unmanned aerial vehicle

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:02.159177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 78dcf5d0-fe3e-41ff-9118-7c9c440160c6 · outbound

This paper cites Scott, and Weilin Huang.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Scott, and Weilin Huang

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:01.969407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8177f6ff-6596-4bd1-a809-96ec1f37a09e · outbound

This paper cites Rc-detr: Improving detrs in crowded pedestrian detection via rank- based contrastive learning.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Rc-detr: Improving detrs in crowded pedestrian detection via rank- based contrastive learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:01.794930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2e783781-a589-4066-8d09-8a8d2c7eadf5 · outbound

This paper cites Yolox: Exceeding yolo series in 2021, 2021.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Yolox: Exceeding yolo series in 2021, 2021

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:01.630231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 909ea719-cf1b-468a-8456-ea91ed78a2dd · outbound

This paper cites Siou loss: More powerful learning for bounding box regression, 2022.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Siou loss: More powerful learning for bounding box regression, 2022

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:01.456958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9f6ef005-9de1-4cf4-bb8d-9f99b36132a7 · outbound

This paper cites Girshick, J.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Girshick, J

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:01.254378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7450c866-25b8-46f9-9cab-a44ef636501b · outbound

This paper cites Girshick.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Girshick

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:01.052234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6516714a-77de-432f-9088-c3a4e94e76bf · outbound

This paper cites Mfel-yolo for small object detection in uav aerial images.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Mfel-yolo for small object detection in uav aerial images

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:00.766896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3057e4f8-ab82-463f-8f78-23ed7b458d2d · outbound

This paper cites YOLOv5 by Ultralytics, 2020.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization YOLOv5 by Ultralytics, 2020

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:00.516326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 90153728-371f-4db3-8801-03e3e6246993 · outbound

This paper cites Ultralytics yolov8, 2023.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Ultralytics yolov8, 2023

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:57:00.200847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 39490842-9b60-4541-9b97-73b168be8ec8 · outbound

This paper cites Microsoft COCO: Common Objects in Context.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Microsoft COCO: Common Objects in Context

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T16:56:55.304610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d59a353-ef4c-4f74-8f30-8bd28512b60d · outbound

This paper cites Powerful-iou: More straightforward and faster bounding box regression loss with a nonmonotonic focusing mechanism.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Powerful-iou: More straightforward and faster bounding box regression loss with a nonmonotonic focusing mechanism

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:59.907978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 76d2bb95-3507-4098-abc1-d0ed9bfc9fcf · outbound

This paper cites an unresolved cited work.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:56:59.674186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c94b0e51-0621-4fb3-b37e-ddbe37513971 · outbound

This paper cites Yolov3: An incremental improvement, 2018.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Yolov3: An incremental improvement, 2018

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:59.488053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c3100c9b-864c-4d98-9795-15586d6facc4 · outbound

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

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization You only look once: Unified, real-time object de- tection

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:59.330628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3b7aab79-db73-4ce8-8a02-ee78a5299ac1 · outbound

This paper cites Girshick, and Jian Sun.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Girshick, and Jian Sun

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:59.127371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f65e92f6-ca46-40ec-b446-14dcb7928348 · outbound

This paper cites Generalized in- tersection over union: A metric and a loss for bounding box regression.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Generalized in- tersection over union: A metric and a loss for bounding box regression

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T16:56:55.801319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56e3abdb-6e00-49de-8db1-f55173266472 · outbound

This paper cites Diff-mosaic: Augmenting realistic representations in infrared small target detection via diffu- sion prior.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Diff-mosaic: Augmenting realistic representations in infrared small target detection via diffu- sion prior

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:58.894007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 950b254f-84d8-4faf-9775-c25ccf768857 · outbound

This paper cites Multi- object garbage image detection algorithm based on sp-ssd.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Multi- object garbage image detection algorithm based on sp-ssd

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:58.602541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 42127ed4-4037-436a-95e8-2869fedc430e · outbound

This paper cites Wise-IoU: Bounding Box Regression Loss with Dynamic Focusing Mechanism.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Wise-IoU: Bounding Box Regression Loss with Dynamic Focusing Mechanism

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T16:56:56.046779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b10888a-c208-4011-b96f-83332b30a250 · outbound

This paper cites Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors, 2022.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors, 2022

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:58.393789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ae89fc64-7c12-4a6d-a94f-5b05ca9172cf · outbound

This paper cites Density-guided two-stage small object detection in uav images.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Density-guided two-stage small object detection in uav images

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:58.187969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9437fea5-4dbe-41d7-a829-44fc88833a2e · outbound

This paper cites Unitbox: An advanced object detection net- work.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Unitbox: An advanced object detection net- work

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:57.960066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 22dc2bb4-605f-4455-8087-7b4ea7cccbe7 · outbound

This paper cites Esod-yolov8: Small object detection enhanced with auto- disturbance rejection convolution.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Esod-yolov8: Small object detection enhanced with auto- disturbance rejection convolution

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:57.567100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation aa4abd5c-43db-497b-80b4-4fe8810e041a · outbound

This paper cites Ni, and Heung-Yeung Shum.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Ni, and Heung-Yeung Shum

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:57.507608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cfe1ea56-b790-4c7b-b751-197e41f8fe94 · outbound

This paper cites an unresolved cited work.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:56:57.320800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 193d46bd-9409-4091-b814-8058f0f2f399 · outbound

This paper cites Focal and efficient iou loss for accu- rate bounding box regression.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Focal and efficient iou loss for accu- rate bounding box regression

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:57.186733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 702cba7e-ab9b-471c-8d61-9b05f841aa5b · outbound

This paper cites Distance-iou loss: Faster and bet- ter learning for bounding box regression.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Distance-iou loss: Faster and bet- ter learning for bounding box regression

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:57.058069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9bdc71a4-3a3d-4388-8dfc-f33c9361e328 · outbound

This paper cites Enhancing ge- ometric factors in model learning and inference for object detection and instance segmentation.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Enhancing ge- ometric factors in model learning and inference for object detection and instance segmentation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:56:56.916343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 42f61c49-c44c-4d70-bb23-3e3b24ab6dba · outbound

This paper cites an unresolved cited work.

InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization Unresolved cited work

Reference 2016

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:56:57.788543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.