Paper Citation Record · LEDGER

Image Segmentation with transformers: An Overview, Challenges and Future

As of 15 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2501.09372.

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

pith.paper-citation-record.v1
2501.09372 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:10:54.070242Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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 exact5
verified fuzzy5
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation badbce81-722f-4f4b-aa5f-bd739bc9058a · outbound

This paper cites A Review on the Strategies and Techniques of Image Segmentation,.

Image Segmentation with transformers: An Overview, Challenges and Future A Review on the Strategies and Techniques of Image Segmentation,

Reference 1

Resolution: verified exact; doi, observed 2026-08-10T20:10:54.223023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a06a9c92-6ef3-4c81-b596-846eb10eb1bc · outbound

This paper cites Techniques and Challenges of Image Segmentation: A Review,.

Image Segmentation with transformers: An Overview, Challenges and Future Techniques and Challenges of Image Segmentation: A Review,

Reference 2

Resolution: verified exact; doi, observed 2026-08-10T20:10:54.208810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d4c53a0c-25c9-4011-acfb-104c7dd9a198 · outbound

This paper cites Fu lly convolutional networks for semantic segmentation,.

Image Segmentation with transformers: An Overview, Challenges and Future Fu lly convolutional networks for semantic segmentation,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.920089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a236a509-183e-4bcc-ab98-fbdf716a7fb3 · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation.

Image Segmentation with transformers: An Overview, Challenges and Future U-Net: Convolutional Networks for Biomedical Image Segmentation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.924659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5680d631-193b-4f5e-8612-388093a8b93c · outbound

This paper cites Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs.

Image Segmentation with transformers: An Overview, Challenges and Future Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.929456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 474d458f-bc5b-4ca1-9e12-7af1df7b3c35 · outbound

This paper cites Pyramid Scene Parsing Network.

Image Segmentation with transformers: An Overview, Challenges and Future Pyramid Scene Parsing Network

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.933874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cc183ce-3c33-4d8b-afc6-0e6dc43c00b8 · outbound

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

Image Segmentation with transformers: An Overview, Challenges and Future ImageNet: A large -scale hierarchical image database,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.938756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44c81258-cf69-4ac4-92e6-468638d3575b · outbound

This paper cites The Pascal Visual Object Classes (VOC) Challenge,.

Image Segmentation with transformers: An Overview, Challenges and Future The Pascal Visual Object Classes (VOC) Challenge,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.942948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f245bd79-3efe-4ec6-bb65-345af1161fdf · outbound

This paper cites Microsoft COCO: Common Objects in Context,.

Image Segmentation with transformers: An Overview, Challenges and Future Microsoft COCO: Common Objects in Context,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.946963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecb4b7ba-f6ab-48b4-b326-0ce6ca61c33f · outbound

This paper cites The Cityscapes Dataset for Semantic Urban Scene Understanding.

Image Segmentation with transformers: An Overview, Challenges and Future The Cityscapes Dataset for Semantic Urban Scene Understanding

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:54.989871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8f4b089c-a933-4281-affe-9f3d0eae95b9 · outbound

This paper cites The Liver Tu mor Segmentation Benchmark (LiTS),.

Image Segmentation with transformers: An Overview, Challenges and Future The Liver Tu mor Segmentation Benchmark (LiTS),

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.959895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f905edba-ea02-456e-898d-73863b25914e · outbound

This paper cites Multi-Scale Context Aggregation by Dilated Convolutions.

Image Segmentation with transformers: An Overview, Challenges and Future Multi-Scale Context Aggregation by Dilated Convolutions

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.963606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4e377b7-fb99-47ee-9274-18d8cca9528e · outbound

This paper cites Deep Residual Learning for Image Recognition.

Image Segmentation with transformers: An Overview, Challenges and Future Deep Residual Learning for Image Recognition

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:54.978715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3f7f83ce-382f-4fcd-a9a7-74c99d2a055c · outbound

This paper cites Dropout: A Simple Way to Prevent Neural Networks from Overfitting,.

Image Segmentation with transformers: An Overview, Challenges and Future Dropout: A Simple Way to Prevent Neural Networks from Overfitting,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:54.966905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b2a2a535-440a-4125-b8c0-bf8df186ba86 · outbound

This paper cites Attention Is All You Need.

Image Segmentation with transformers: An Overview, Challenges and Future Attention Is All You Need

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.979182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fb38790-b15b-44ab-be6f-98d0fb912d29 · outbound

This paper cites Long Short -Term Memory,.

Image Segmentation with transformers: An Overview, Challenges and Future Long Short -Term Memory,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.982663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e255ac17-1214-4398-90fd-0a54270aaa69 · outbound

This paper cites Non-local Neural Networks.

Image Segmentation with transformers: An Overview, Challenges and Future Non-local Neural Networks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.987337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 711c3fd3-f46d-43b1-b464-737c56da2fb2 · outbound

This paper cites PSANet: Point-wise Spatial Attention Network for Scene Parsing,.

Image Segmentation with transformers: An Overview, Challenges and Future PSANet: Point-wise Spatial Attention Network for Scene Parsing,

Reference 18

Resolution: verified exact; doi, observed 2026-08-10T20:10:54.140017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fdac9936-7f34-4593-9f17-694033421186 · outbound

This paper cites Local Relation Networks for Image Recognition.

Image Segmentation with transformers: An Overview, Challenges and Future Local Relation Networks for Image Recognition

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:54.955118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d2847e4f-009f-4a44-ab50-5caa477521fc · outbound

This paper cites Exploring Self-attention for Image Recognition.

Image Segmentation with transformers: An Overview, Challenges and Future Exploring Self-attention for Image Recognition

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:10:54.529049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9e9b59f9-7c84-4886-816a-bcdc7a544835 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Image Segmentation with transformers: An Overview, Challenges and Future An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.007985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4cef0b4-0429-4d6a-b6f0-61c906830ebe · outbound

This paper cites End-to-End Object Detection with Transformers.

Image Segmentation with transformers: An Overview, Challenges and Future End-to-End Object Detection with Transformers

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.011596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba674ad2-358e-4f2d-850e-c7c33f3839c9 · outbound

This paper cites Scene Parsing through ADE20K Dataset,.

Image Segmentation with transformers: An Overview, Challenges and Future Scene Parsing through ADE20K Dataset,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.015526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8110192-d049-4427-9a5c-4b9eea6d8d77 · outbound

This paper cites The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS),.

Image Segmentation with transformers: An Overview, Challenges and Future The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS),

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.019948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfaadbb7-a43b-4991-a618-03d12cf6834c · outbound

This paper cites CNN or RNN: Review and Experimental Comparison on Image Classification,.

Image Segmentation with transformers: An Overview, Challenges and Future CNN or RNN: Review and Experimental Comparison on Image Classification,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.024166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9061a98-f58f-4886-aa0e-2293349add66 · outbound

This paper cites SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation.

Image Segmentation with transformers: An Overview, Challenges and Future SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.028041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffe9c360-d5b7-473f-87b8-5a1dff89b035 · outbound

This paper cites Densely Connected Convolutional Networks.

Image Segmentation with transformers: An Overview, Challenges and Future Densely Connected Convolutional Networks

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.033403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 382f9a6c-3020-4003-bee7-7bbaffdfac2f · outbound

This paper cites Deep High-Resolution Representation Learning for Visual Recognition.

Image Segmentation with transformers: An Overview, Challenges and Future Deep High-Resolution Representation Learning for Visual Recognition

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:54.940882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c9e71008-fa13-497a-9edc-db5922e30b75 · outbound

This paper cites Segmenter: Transformer for Semantic Segmentation.

Image Segmentation with transformers: An Overview, Challenges and Future Segmenter: Transformer for Semantic Segmentation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.045389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3e2cc5b-8e8c-4d04-979f-fe1da9ce14b4 · outbound

This paper cites Fully Transformer Networks for Semantic Image Segmentation.

Image Segmentation with transformers: An Overview, Challenges and Future Fully Transformer Networks for Semantic Image Segmentation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.049533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a36f9808-a23f-4368-914f-f01d69eca483 · outbound

This paper cites Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions.

Image Segmentation with transformers: An Overview, Challenges and Future Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.053883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2fee5b9-fcfd-40a0-8718-f97f33e2cbd3 · outbound

This paper cites Masked-attention Mask Transformer for Universal Image Segmentation.

Image Segmentation with transformers: An Overview, Challenges and Future Masked-attention Mask Transformer for Universal Image Segmentation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.057923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8c60624-6622-467d-8837-d34acfd8af83 · outbound

This paper cites Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.

Image Segmentation with transformers: An Overview, Challenges and Future Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.061761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f63a732c-cb40-4a5f-b692-d9645347c08d · outbound

This paper cites Swin Transformer: Hierarchical Vision Transformer using Shifted Windows.

Image Segmentation with transformers: An Overview, Challenges and Future Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.066079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90ccc98d-ed52-40e4-b5b1-000bae914df2 · outbound

This paper cites SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers.

Image Segmentation with transformers: An Overview, Challenges and Future SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.070242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f15da264-dfbe-46ce-ac63-2f90edfb6422 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Image Segmentation with transformers: An Overview, Challenges and Future Deep Residual Learning for Image Recognition

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.972028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 987a3519-239e-4886-82ed-3fd775f82d9b · outbound

This paper cites The Cityscapes Dataset for Semantic Urban Scene Understanding.

Image Segmentation with transformers: An Overview, Challenges and Future The Cityscapes Dataset for Semantic Urban Scene Understanding

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:53.955439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 200d981b-8a8d-4986-9c3f-cb80d6d911bd · outbound

This paper cites Local Relation Networks for Image Recognition.

Image Segmentation with transformers: An Overview, Challenges and Future Local Relation Networks for Image Recognition

Reference 2019

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:10:54.545818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 10a7ab64-9a23-40fd-85f8-9dc095a05a8f · outbound

This paper cites Deep High-Resolution Representation Learning for Visual Recognition.

Image Segmentation with transformers: An Overview, Challenges and Future Deep High-Resolution Representation Learning for Visual Recognition

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-10T20:10:54.041403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.