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Paper Citation Record · LEDGER

Where are the Masks: Instance Segmentation with Image-level Supervision

As of 11 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:1907.01430.

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

pith.paper-citation-record.v1
1907.01430 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-25T11:00:54.626141Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

44 of 44 outbound references displayed

  • verified exact2
  • verified fuzzy41
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8d7710c7-97b4-41d7-9a6f-101e8310b5f2 · outbound

This paper cites Learning pixel-level semantic affinity with image-level supervision for weakly supervised semantic segmentation.

Where are the Masks: Instance Segmentation with Image-level Supervision Learning pixel-level semantic affinity with image-level supervision for weakly supervised semantic segmentation

Reference 1

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Observation 9cc02bd5-1fc2-4e30-8223-acfc2ad4ce30 · outbound

This paper cites Multiscale combinatorial grouping.

Where are the Masks: Instance Segmentation with Image-level Supervision Multiscale combinatorial grouping

Reference 2

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Observation fd51a1c1-8731-4b5e-bfe8-057abd8cf191 · outbound

This paper cites Whatâ ˘A ´Zs the point: Semantic segmentation with point supervision.

Where are the Masks: Instance Segmentation with Image-level Supervision Whatâ ˘A ´Zs the point: Semantic segmentation with point supervision

Reference 3

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Observation c8c8d3e4-6122-4e1e-8c88-f85f4990b5ed · outbound

This paper cites Weakly supervised deep detection networks.

Where are the Masks: Instance Segmentation with Image-level Supervision Weakly supervised deep detection networks

Reference 4

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Observation 066d7a7c-cbab-4dba-87b9-ea2ec8e59edc · outbound

This paper cites YOLACT: Real-time Instance Segmentation.

Where are the Masks: Instance Segmentation with Image-level Supervision YOLACT: Real-time Instance Segmentation

Reference 5

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Observation 43801894-f198-41fe-a179-788b7067b7a6 · outbound

This paper cites Masklab: Instance segmentation by refining object detec- tion with semantic and direction features.

Where are the Masks: Instance Segmentation with Image-level Supervision Masklab: Instance segmentation by refining object detec- tion with semantic and direction features

Reference 6

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:408acfdcfbc49add24ef55643eb8b1801730f3c926f38bb8cff741da7e69af38

Observation eecbcedc-0c90-4247-b25b-63d3f2d13221 · outbound

This paper cites Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs.

Where are the Masks: Instance Segmentation with Image-level Supervision Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs

Reference 7

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source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:049c01e0348399443278cd269a4dbd05b1b39e9011f8a38fea710a40b9530eae

Observation 50db03aa-b719-4ca3-b9c2-30aa8f329496 · outbound

This paper cites Object counting and instance segmentation with image-level supervision.

Where are the Masks: Instance Segmentation with Image-level Supervision Object counting and instance segmentation with image-level supervision

Reference 8

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Observation a9adf992-c1c9-4422-8dc3-9970d9e5fb91 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding.

Where are the Masks: Instance Segmentation with Image-level Supervision The cityscapes dataset for semantic urban scene understanding

Reference 9

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Observation 9b2811a2-fce7-4cd7-877a-cc9f04f4f69d · outbound

This paper cites Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation.

Where are the Masks: Instance Segmentation with Image-level Supervision Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation

Reference 10

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Observation 5f8b9d47-5174-40fb-81c6-c3dd2651f057 · outbound

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

Where are the Masks: Instance Segmentation with Image-level Supervision Imagenet: A large-scale hierarchical image database

Reference 11

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Observation 6391d045-3f82-47e4-9d21-dde6aa7ecc1d · outbound

This paper cites The pascal visual object classes (voc) challenge.

Where are the Masks: Instance Segmentation with Image-level Supervision The pascal visual object classes (voc) challenge

Reference 12

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Observation 6887519b-0aa7-4967-be0d-eba958b569ba · outbound

This paper cites RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free.

Where are the Masks: Instance Segmentation with Image-level Supervision RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free

Reference 13

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Observation 703ad6f8-9a65-46e1-b3df-85ff7044a759 · outbound

This paper cites Deep residual learning for image recognition.

Where are the Masks: Instance Segmentation with Image-level Supervision Deep residual learning for image recognition

Reference 14

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Observation 980d7936-1c6f-406d-9ea3-0cb52c0ba5ab · outbound

This paper cites Mask r-cnn.

Where are the Masks: Instance Segmentation with Image-level Supervision Mask r-cnn

Reference 15

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Observation c7d35240-9283-4617-8662-e291cc4fc29f · outbound

This paper cites What makes for ef- fective detection proposals? T-PAMI.

Where are the Masks: Instance Segmentation with Image-level Supervision What makes for ef- fective detection proposals? T-PAMI

Reference 16

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Observation 5758c492-b54e-4ad0-981c-2a068431933e · outbound

This paper cites Simple does it: Weakly supervised instance and semantic segmentation.

Where are the Masks: Instance Segmentation with Image-level Supervision Simple does it: Weakly supervised instance and semantic segmentation

Reference 17

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Observation c8b56855-9d38-4d25-a27a-e87b1cc80714 · outbound

This paper cites Seed, expand and constrain: Three principles for weakly-supervised image segmentation.

Where are the Masks: Instance Segmentation with Image-level Supervision Seed, expand and constrain: Three principles for weakly-supervised image segmentation

Reference 18

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Observation b421e0ca-3241-4578-b47c-36f51c61dbeb · outbound

This paper cites Konopczynski, Thorben Kröger, Lei Zheng, and Jürgen Hesser.

Where are the Masks: Instance Segmentation with Image-level Supervision Konopczynski, Thorben Kröger, Lei Zheng, and Jürgen Hesser

Reference 19

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Observation 84803280-bcab-4da3-a879-bd8dc692af95 · outbound

This paper cites Analysis and optimization of loss functions for multiclass, top-k, and multilabel classification.

Where are the Masks: Instance Segmentation with Image-level Supervision Analysis and optimization of loss functions for multiclass, top-k, and multilabel classification

Reference 20

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Observation e0064a4e-e631-4010-968b-97eb6a156924 · outbound

This paper cites Where are the blobs: Counting by localization with point supervision.

Where are the Masks: Instance Segmentation with Image-level Supervision Where are the blobs: Counting by localization with point supervision

Reference 21

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Observation 57d20c50-afab-4233-a884-36da85af07ff · outbound

This paper cites Instance Segmentation with Point Supervision.

Where are the Masks: Instance Segmentation with Image-level Supervision Instance Segmentation with Point Supervision

Reference 22

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Observation b51ec217-40cf-40a9-915d-a0b7fe48a272 · outbound

This paper cites Scribblesup: Scribble- supervised convolutional networks for semantic segmentation.

Where are the Masks: Instance Segmentation with Image-level Supervision Scribblesup: Scribble- supervised convolutional networks for semantic segmentation

Reference 23

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Observation b8ee5ebf-bf6e-4d46-92ef-08338be482f8 · outbound

This paper cites Microsoft coco: Common objects in context.

Where are the Masks: Instance Segmentation with Image-level Supervision Microsoft coco: Common objects in context

Reference 24

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Observation 480a649e-99e1-4dba-8e4b-18f04009964c · outbound

This paper cites Feature pyramid networks for object detection.

Where are the Masks: Instance Segmentation with Image-level Supervision Feature pyramid networks for object detection

Reference 25

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Observation 24dad8cf-aaa0-4692-b7b7-23a5e85cbd7f · outbound

This paper cites Fully convolutional networks for semantic segmentation.

Where are the Masks: Instance Segmentation with Image-level Supervision Fully convolutional networks for semantic segmentation

Reference 26

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source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:cb65ecad4500632f4d3f0289165302187d90346f55d22e7048d2e2d6137f51f0

Observation 2b063535-6ed3-45a3-af69-61ab37b96ee6 · outbound

This paper cites Convo- lutional oriented boundaries.

Where are the Masks: Instance Segmentation with Image-level Supervision Convo- lutional oriented boundaries

Reference 27

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Source-reported events for the cited work

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Observation 4629bc0a-7f34-4492-a7e8-022caa0a94b4 · outbound

This paper cites maskrcnn-benchmark: Fast, mod- ular reference implementation of Instance Segmentation and Object Detec- tion algorithms in PyTorch.

Where are the Masks: Instance Segmentation with Image-level Supervision maskrcnn-benchmark: Fast, mod- ular reference implementation of Instance Segmentation and Object Detec- tion algorithms in PyTorch

Reference 28

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 6f7a084d-4f18-415d-9c49-141c3345a2a2 · outbound

This paper cites From image-level to pixel-level labeling with convolutional networks.

Where are the Masks: Instance Segmentation with Image-level Supervision From image-level to pixel-level labeling with convolutional networks

Reference 29

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 25181cf5-1ce0-4cb4-acbd-e95bfd1166b1 · outbound

This paper cites Learning to segment object can- didates.

Where are the Masks: Instance Segmentation with Image-level Supervision Learning to segment object can- didates

Reference 30

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation deece4c4-15aa-4084-8207-4f7d85bda534 · outbound

This paper cites Learning to refine object segments.

Where are the Masks: Instance Segmentation with Image-level Supervision Learning to refine object segments

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:13ef38c7d68eac8b5fcac65144b2d1ce3b8e0cb90f723b3ea4594b041d496a54

Observation 339af045-aba4-4e8a-a8ba-80d2ecca3867 · outbound

This paper cites Segmentation of medical images using adaptive region growing.

Where are the Masks: Instance Segmentation with Image-level Supervision Segmentation of medical images using adaptive region growing

Reference 32

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 036e65a1-b486-4a6f-a5bd-924165c3c89a · outbound

This paper cites Boosting object proposals: From pascal to coco.

Where are the Masks: Instance Segmentation with Image-level Supervision Boosting object proposals: From pascal to coco

Reference 33

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:41282e04de534661e68a55440caa4357f6081ad7decf2290c41266680c72c9ef

Observation 823693ed-95e2-40a8-a461-6d68772fa0b0 · outbound

This paper cites Augmented feedback in semantic segmentation under image level supervision.

Where are the Masks: Instance Segmentation with Image-level Supervision Augmented feedback in semantic segmentation under image level supervision

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:e1362dadb9e1e13c2eb4e8418d8430b0e52f5c85396e3ac399301bb795d0c996

Observation fe08b1d3-9383-433a-9624-ce6642072f25 · outbound

This paper cites End-to-end instance segmentation with recurrent attention.

Where are the Masks: Instance Segmentation with Image-level Supervision End-to-end instance segmentation with recurrent attention

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T11:06:58.041920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:f60b0621b1143ab6ff53f84d977728406d1eb03eff9a77c440ba972d6660e10c

Observation f3a72c7c-dcdb-4e37-9e2e-797005edae7c · outbound

This paper cites Faster r-cnn: Towards real- time object detection with region proposal networks.

Where are the Masks: Instance Segmentation with Image-level Supervision Faster r-cnn: Towards real- time object detection with region proposal networks

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T11:06:57.998196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:5bf3661d610210eb1cc619e7cdab1b2f2d8b921dd5f2364764d7f8ce51891e8a

Observation e751ad34-f50d-467c-b11c-11f6b1444e76 · outbound

This paper cites Recurrent instance segmen- tation.

Where are the Masks: Instance Segmentation with Image-level Supervision Recurrent instance segmen- tation

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T11:06:58.003417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:19c0ec96c8e12312617db98ceb675c10044dd3abfe69d4ae3c925cbc0cb51884

Observation c39a4224-0a30-429e-91c1-5b97987097ae · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization.

Where are the Masks: Instance Segmentation with Image-level Supervision Grad-cam: Visual explanations from deep networks via gradient-based localization

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T11:06:58.008860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:a3d5529e44f439c26dbc17be79294a1011e899b6bfc0d19bd4acad3564ca1445

Observation 1284191d-f05c-4f39-8f67-2a90e5087c9f · outbound

This paper cites Multiple instance detection network with online instance classifier refinement.

Where are the Masks: Instance Segmentation with Image-level Supervision Multiple instance detection network with online instance classifier refinement

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T11:06:58.011418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:0bc63800ef61619ec2a7bb942f2d41f0152a0f3315dc3e081f5b95b67da67077

Observation 987c635f-d19c-43e8-bb75-0d1253693a6b · outbound

This paper cites Weakly supervised region proposal network and object de- tection.

Where are the Masks: Instance Segmentation with Image-level Supervision Weakly supervised region proposal network and object de- tection

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T11:06:58.017456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:6570509925effd95ed24d91d67b0487ae1bb1ca221ed9dd3a7d02d9b6f250da6

Observation a6017e99-25d4-4762-9f38-3eaf42f23b14 · outbound

This paper cites Selective search for object recognition.

Where are the Masks: Instance Segmentation with Image-level Supervision Selective search for object recognition

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T11:06:58.031449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:8292676ccfb84699e1c634e800d48c8f5d1c54a984e98590d91d555919cabd92

Observation 9cd10918-0ad5-4dd0-96b2-3a74bbd7d383 · outbound

This paper cites Learning deep features for discriminative localization.

Where are the Masks: Instance Segmentation with Image-level Supervision Learning deep features for discriminative localization

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T11:06:58.046827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:a164a7c6054706eabf272b12880e36828acebebb6392978f5b1971cfe7fdd185

Observation 56b8308a-f42b-4431-a6cc-32930773f7f0 · outbound

This paper cites Weakly supervised instance segmentation using class peak response.

Where are the Masks: Instance Segmentation with Image-level Supervision Weakly supervised instance segmentation using class peak response

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T11:06:57.960901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:2cfc00567da90ebfa8b4782fa9df4433991b6197efbe318fc14366116b69bc65

Observation bb88d4ff-f019-4e94-a818-adfb02466bd9 · outbound

This paper cites Edge boxes: Locating object proposals from edges.

Where are the Masks: Instance Segmentation with Image-level Supervision Edge boxes: Locating object proposals from edges

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T11:06:57.963445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-25T11:00:54.626141Z digest=sha256:c1e4adbcb584aea777192f8c81cf6b20aedafea6a398ac92125c2b0bdf48012a

Pith citing papers

No inbound Pith citation observations are available.