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Paper Citation Record · LEDGER

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview

As of 31 July 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2604.13244.

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

pith.paper-citation-record.v1
2604.13244 v1

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T16:18:34.717325Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-31T06:34:12.847434+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

60 of 60 outbound references displayed

  • verified exact10
  • verified fuzzy44
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 360f1eff-0468-47c4-a4c2-e4d5b663d304 · outbound

This paper cites an unresolved cited work.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Unresolved cited work

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 5531b4bb-757e-4175-8710-e8c376c4e77d · outbound

This paper cites WaSR–A Water Segmenta- tion and Refinement Maritime Obstacle Detection Network.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview WaSR–A Water Segmenta- tion and Refinement Maritime Obstacle Detection Network

Reference 2

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No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 30d44515-0566-4985-81d0-a71e9303d108 · outbound

This paper cites The mastr1325 dataset for training deep usv obstacle detection models.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview The mastr1325 dataset for training deep usv obstacle detection models

Reference 3

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No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 583d2b9a-1b40-4063-915e-a0f4f03c7e1d · outbound

This paper cites Mixed Pseudo Labels for Semi-Supervised Object Detection.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Mixed Pseudo Labels for Semi-Supervised Object Detection

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 12a7566f-99df-4517-a178-5e70d1ab3c91 · outbound

This paper cites Schwing, Alexan- der Kirillov, and Rohit Girdhar.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Schwing, Alexan- der Kirillov, and Rohit Girdhar

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 8787c5d2-95bf-45d9-a926-c0dd9c76b478 · outbound

This paper cites MMSegmenta- tion: Openmmlab semantic segmentation toolbox and benchmark.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview MMSegmenta- tion: Openmmlab semantic segmentation toolbox and benchmark

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 8c265319-a64b-4f5a-b96f-b80c9b610573 · outbound

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

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Imagenet: A large-scale hierarchical image database

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation f5dd9ba6-1acc-494c-a8d7-3750a827028c · outbound

This paper cites Rsuigm: Realistic synthetic underwater image gener- ation with image formation model.ACM Trans.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Rsuigm: Realistic synthetic underwater image gener- ation with image formation model.ACM Trans

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation ee535050-09e3-48f7-9501-17ef73ce1c1d · outbound

This paper cites Detection of bodies in maritime rescue operations using unmanned aerial vehicles with multispectral cameras.Journal of Field Robotics, 36(4):782–796.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Detection of bodies in maritime rescue operations using unmanned aerial vehicles with multispectral cameras.Journal of Field Robotics, 36(4):782–796

Reference 9

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No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation b5bc590b-40c3-440e-805c-17330af7c764 · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview YOLOX: Exceeding YOLO Series in 2021

Reference 10

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arxiv_id, observed 2026-05-13T10:31:31.716715Z

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No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 89289bd8-4c2d-4bfc-b066-e5aaa40c2e3a · outbound

This paper cites Cubuk, Quoc V.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Cubuk, Quoc V

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 720a96e3-f11e-4823-a874-bc9beba894f1 · outbound

This paper cites Maritime collision avoidance dataset germany, english channel, and the netherlands.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Maritime collision avoidance dataset germany, english channel, and the netherlands

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 8a88149f-e6a9-4bbe-a210-a01ce30add26 · outbound

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

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Lvis: A dataset for large vocabulary instance segmentation

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 99d97188-c6d0-4178-b656-3f78d059d856 · outbound

This paper cites an unresolved cited work.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Unresolved cited work

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 89d5853c-e025-4e21-9224-59782f266e40 · outbound

This paper cites arXiv preprint arXiv:2509.20787 (2025).

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview arXiv preprint arXiv:2509.20787 (2025)

Reference 15

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arxiv_id, observed 2026-05-11T09:01:00.701227Z

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No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 29c8e8cb-a429-43ff-87a8-4020c97890ed · outbound

This paper cites Ultralytics YOLO, Jan.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Ultralytics YOLO, Jan

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 192f5cf0-17b4-479b-8172-8a53544b4ec6 · outbound

This paper cites Vessel detection and classification from spaceborne optical images: A literature survey.Remote sensing of environment, 207:1–26.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Vessel detection and classification from spaceborne optical images: A literature survey.Remote sensing of environment, 207:1–26

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation d46e22aa-0aba-4349-ba72-c9378263fefa · outbound

This paper cites Your vit is secretly an image segmentation model.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Your vit is secretly an image segmentation model

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation de2833a6-37a3-4fcd-823c-f71557e2d981 · outbound

This paper cites Real-time radar–vision association via monocular distance estimation.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Real-time radar–vision association via monocular distance estimation

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 39e5f3d7-a3d0-4db0-9ebf-1792a0b09a7e · outbound

This paper cites an unresolved cited work.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Unresolved cited work

Reference 20

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No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation db44f2f4-5380-41d9-9f19-130ab558f817 · outbound

This paper cites Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles

Reference 21

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Observation 72135f86-e46b-4786-a531-e0eb9ba23cc0 · outbound

This paper cites Approx- imate supervised object distance estimation on unmanned surface vehicles.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Approx- imate supervised object distance estimation on unmanned surface vehicles

Reference 22

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raw_fallback, observed 2026-05-17T15:59:57.153634Z

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No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 4487f3c1-e52f-4fa1-8cf9-90264e369d8d · outbound

This paper cites 2nd workshop on maritime computer vision (macvi) 2024: Challenge results.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview 2nd workshop on maritime computer vision (macvi) 2024: Challenge results

Reference 23

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No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 3672c30e-8e9a-4655-be4f-8893480b43a2 · outbound

This paper cites 3rd workshop on maritime computer vision (macvi) 2025: Challenge results.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview 3rd workshop on maritime computer vision (macvi) 2025: Challenge results

Reference 24

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raw_fallback, observed 2026-05-17T15:59:57.131582Z

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No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 07b4bdc1-ba9d-4310-86ce-478b6fa17591 · outbound

This paper cites Panoptic segmentation.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Panoptic segmentation

Reference 25

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raw_fallback, observed 2026-05-17T15:59:57.134620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 854ee2ce-01ab-41b5-bfa2-22f3e3222ced · outbound

This paper cites Real-time fusion of visual and chart data for enhanced maritime vision.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Real-time fusion of visual and chart data for enhanced maritime vision

Reference 26

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raw_fallback, observed 2026-05-17T15:59:57.141428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 274ab78f-9437-4a1c-800a-9c2cc98ef09b · outbound

This paper cites A novel performance evaluation methodology for single-target trackers.IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11):2137– 2155.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview A novel performance evaluation methodology for single-target trackers.IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11):2137– 2155

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 130f549b-2d4d-4569-b8d1-354be88bb11b · outbound

This paper cites ROSEBUD: A deep fluvial segmentation dataset for monocular vision-based river navigation and ob- stacle avoidance.Sensors, 22(13):4681.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview ROSEBUD: A deep fluvial segmentation dataset for monocular vision-based river navigation and ob- stacle avoidance.Sensors, 22(13):4681

Reference 28

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raw_fallback, observed 2026-05-17T15:59:57.121416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation e14d5c98-53ad-4e52-89b4-5d3aa6ea11ae · outbound

This paper cites Ni, and Heung-Yeung Shum.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Ni, and Heung-Yeung Shum

Reference 29

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raw_fallback, observed 2026-05-17T15:59:57.128129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation c073a960-bde1-4a7d-a933-df015d084c41 · outbound

This paper cites Exploring plain vision transformer backbones for object de- tection.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Exploring plain vision transformer backbones for object de- tection

Reference 30

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raw_fallback, observed 2026-05-17T15:59:57.138383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:14b4e1e895ca55fff4fef6616b19dd142a955ecdffd2cd005ebae25d7d63399f

Observation 456453ad-319f-468c-82c7-8a329264bd41 · outbound

This paper cites MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation

Reference 31

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arxiv_id, observed 2026-05-11T09:01:00.704945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 9ff5c172-0dc3-4f84-a809-dbab6d9de30d · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Swin transformer: Hierarchical vision transformer using shifted windows

Reference 32

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raw_fallback, observed 2026-05-17T15:59:57.167006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

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Observation 96c48ea1-ac33-4020-9959-af6cbb65bccc · outbound

This paper cites A convnet for the 2020s.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview A convnet for the 2020s

Reference 33

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raw_fallback, observed 2026-05-17T15:59:57.108112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:d5843788e124f01c8cbf057eebed9d1d9be8ba0bbd005304c12b32cd31e8484d

Observation 1b4def2e-0788-4a51-ae5d-7139fa9d417e · outbound

This paper cites Decoupled Weight Decay Regularization.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Decoupled Weight Decay Regularization

Reference 34

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local_arxiv, observed 2026-05-11T09:01:00.683897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:8892e52ecccf8e1d79ec2fbcf4e12d4f95906d1a652f977538eb2bff9b280056

Observation 8f312a2a-3d60-4e18-be49-1aa238670821 · outbound

This paper cites Decoupled weight de- cay regularization.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Decoupled weight de- cay regularization

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.111737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:6e607ae5005562f82567d541150ceb2a61ee90db93a6c18f6f79bbe59e8f47a5

Observation 3c8344f1-d3dc-4bed-8c26-c15691b23a1e · outbound

This paper cites an unresolved cited work.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-05-17T15:59:57.114805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:bd976614b11d56b950cc29e05088eb938feec5f765541ddd296ffbe0cd76acd3

Observation 481f64e4-cf5d-4555-a95d-8be06279746e · outbound

This paper cites RTMDet: An Empirical Study of Designing Real-Time Object Detectors.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview RTMDet: An Empirical Study of Designing Real-Time Object Detectors

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:01:00.675049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:bba1e1988f6a11b2f765d1fc7bc9c920fecf505966adfa9b25fab8e819c80a53

Observation 48d10cb1-bfca-4b2d-b13b-2a7041e2abcc · outbound

This paper cites Dustnet++: Deep learning-based visual regression for dust density estimation.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Dustnet++: Deep learning-based visual regression for dust density estimation

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.095213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:7cb64a698b649af05b0baaecb4a5ef334a704c8c2ef2d33ff1e4c58f94e03325

Observation 624beba0-9690-4db9-9312-f43a293614be · outbound

This paper cites Dustnet: Attention to dust.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Dustnet: Attention to dust

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.101821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:35c27ad6031c656b2879f13b9800692adf2e96e1449c707f5181fa754d37af7b

Observation 7bb78f4c-b44b-4add-96ab-6b576522f9ee · outbound

This paper cites MULTIAQUA: A multimodal maritime dataset and robust training strategies for multimodal semantic segmentation.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview MULTIAQUA: A multimodal maritime dataset and robust training strategies for multimodal semantic segmentation

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.105299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:1ac09b989734795cbb16082ac982fd252666928d3fcd2b61da589a3f08339db7

Observation 789edec6-c2ed-4694-abb4-922ba046c586 · outbound

This paper cites Dinov2: Learning robust visual features without supervision.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Dinov2: Learning robust visual features without supervision

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.085943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:bae7f602f6377f694a1e887b706bd809963766e9ff205b733bf2a47fd6affc53

Observation 428a0946-f4b8-4822-bac2-d50940a068dc · outbound

This paper cites Are object detection assessment criteria ready for maritime computer vision?IEEE Transactions on Intelligent Trans- portation Systems, 21(12):5295–5304.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Are object detection assessment criteria ready for maritime computer vision?IEEE Transactions on Intelligent Trans- portation Systems, 21(12):5295–5304

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.076331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:4a905b4df560c01c104205350ebc3d5576b58b07acd1eeb4cf671826625db485

Observation b94e5f86-0599-4a79-932b-d86a9cfb435e · outbound

This paper cites Puigcerver, C.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Puigcerver, C

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.079591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:191733930dd14dd5cd630c82399714b2b44bac4b445d348ea09b8d18f846791a

Observation ed8322c3-2495-4ebe-a9a4-30b1d9e25d9c · outbound

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

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview SAM 2: Segment Anything in Images and Videos

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-05-11T09:01:00.653573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:2d4fb3552755debf60df74a29856fb39cf80dd7f9f67ca6025e1ba24c2ff27bd

Observation a3e5ab55-180b-4b23-a54b-ca17041d427c · outbound

This paper cites ImageNet-21K Pretraining for the Masses.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview ImageNet-21K Pretraining for the Masses

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:01:00.658333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:a69b847f6d493d515cae108aeb4cf96642d0d8b4bf278594fa69c4953f2d261d

Observation e8c4a6b4-e389-4670-afaa-f9282639bd05 · outbound

This paper cites Rf-detr: Neural architecture search for real-time detection transformers.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Rf-detr: Neural architecture search for real-time detection transformers

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.082910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:5c8df7ddf60495f91c7256420c914e862ed21670cd40980cc7454dc0bf37081a

Observation df3e3d90-f501-428e-b823-74f7b033d9a3 · outbound

This paper cites DINOv3.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview DINOv3

Reference 47

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T09:01:00.678633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:d69500d89acf9501991c67177384f9ee685d1dcbe2bad13e336a2f89244a763f

Observation 2e53f635-08cd-4926-9764-cebe4f485f1e · outbound

This paper cites Weighted boxes fusion: Ensembling boxes from different object detection models.Image and Vision Computing, 107:104117.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Weighted boxes fusion: Ensembling boxes from different object detection models.Image and Vision Computing, 107:104117

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.092141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:098301017258b24b8b0fe72b0fa9b87b91f769cbd1675ed89da8aa09153af297

Observation 0e04078d-059f-4b92-a870-f4f189ae933f · outbound

This paper cites Seadronessee: A maritime benchmark for detecting humans in open water.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Seadronessee: A maritime benchmark for detecting humans in open water

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.125018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:a915a323b853a7815fb3baf6a8bc528db48b3010c11edc6f72695a91154e870c

Observation d8a25a38-5eca-4967-9af0-a417f72d498f · outbound

This paper cites Rsos- net: Real-time surface obstacle segmentation network for uncrewed waterborne vehicles.IEEE Transactions on Intelli- gent Transportation Systems, 27(1):1052–1065.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Rsos- net: Real-time surface obstacle segmentation network for uncrewed waterborne vehicles.IEEE Transactions on Intelli- gent Transportation Systems, 27(1):1052–1065

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.069891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:2db4e1d4ddbf75def883071e2589441c6c663e7cbeee9d45d55a023eb9514c92

Observation c833a26f-902d-41af-ac5d-6a1f2aef4d3e · outbound

This paper cites Bhattacharyya.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Bhattacharyya

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.072883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:10bbdf319d4d742e25c75495a9f64e2956db84f87685df9b34e234dca343b09c

Observation 16c79566-6ac4-4f2a-b6e3-820b3243db28 · outbound

This paper cites an unresolved cited work.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-05-17T15:59:57.088859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:d6b6140216bccc1fb7dfccad88736f8f69a59768937bdb4667623e4757578f0d

Observation 0773c5e3-499c-4562-b8a8-b6832cd27fc9 · outbound

This paper cites Waterscenes: A multi-task 4d radar-camera fusion dataset and benchmarks for autonomous driving on water surfaces.IEEE Transactions on Intelligent Transportation Systems.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Waterscenes: A multi-task 4d radar-camera fusion dataset and benchmarks for autonomous driving on water surfaces.IEEE Transactions on Intelligent Transportation Systems

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.098975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:86b8d4ff97c6d020ed055b7df9dc669839cc9c403470f4fe0376e8c0332700ea

Observation 68fd937e-7fde-4974-ba2e-8dd4b9baf23f · outbound

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

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Dino: Detr with improved denoising anchor boxes for end-to-end object detection

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.170526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:8f00a7f5b4cb1cecb94c065df3192a6535a3b2a82e8e938590d0d4ac4bfc5408

Observation 3bc32312-e868-47f6-bda2-42c27ad20131 · outbound

This paper cites Dense distinct query for end-to-end object detection.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Dense distinct query for end-to-end object detection

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.060096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:228488e1430f2c0de8433be2f56512e5402bfc6fd7159079ebfcb59f5f2a6119

Observation e7c3f6e2-2a98-4324-80ff-940032232bcc · outbound

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

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Detrs with col- laborative hybrid assignments training

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.063552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:ab8d08ef61c0bbaedf775c4843d8522c97c83abaacdf1627a57fee91111a1b5f

Observation 9c25cf43-914c-4daa-a3b5-8fafff2f0057 · outbound

This paper cites Contrast limited adaptive histogram equal- ization.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Contrast limited adaptive histogram equal- ization

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.066551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:e5a5468ec9d14a1a8b884bb35d1bd20290c89857e243739b0dc7f8cea143b953

Observation ddc29c85-e74a-465e-ba88-574f699da2c2 · outbound

This paper cites Learning maritime obstacle detection from weak annotations by scaffolding.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Learning maritime obstacle detection from weak annotations by scaffolding

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.056781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:9e63e7803ba6c642e36f7390e13ffbd0d048c8d8835857ad22fff6d0b7f871c5

Observation 9dc75e94-6d3c-4804-b1d8-c3a5e43df311 · outbound

This paper cites PanSR: An Object-Centric Mask Transformer for Panoptic Segmentation.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview PanSR: An Object-Centric Mask Transformer for Panoptic Segmentation

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:01:00.666247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:3f2d3edd2e8c702100a9641cf8eca9de9d846995ee98ef0cc1b6848106affa18

Observation 7a95ffa1-b99b-484f-a8ab-8f80261ae3e3 · outbound

This paper cites LaRS: A diverse panoptic maritime obstacle detection dataset and benchmark.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview LaRS: A diverse panoptic maritime obstacle detection dataset and benchmark

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-05-17T15:59:57.053185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-10T16:18:34.717325Z digest=sha256:2e22dfa2a80ae24658dfc7e643b1ef4d01e0ee39d2d301f8ff66e9e5407de016

Pith citing papers

No inbound Pith citation observations are available.