Paper Citation Record · LEDGER

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting

As of 16 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:1908.07801.

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

pith.paper-citation-record.v1
1908.07801 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:00:09.121631Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

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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

45 of 45 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1e0e93e6-f4f0-4106-822a-f24f02dce1e1 · outbound

This paper cites https://github.com/ roytseng-tw/Detectron.pytorch, 2018.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting https://github.com/ roytseng-tw/Detectron.pytorch, 2018

Reference 1

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Observation 281778de-1c9b-4913-a7bc-4620989f5b55 · outbound

This paper cites http://cocodataset.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting http://cocodataset

Reference 2

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Observation bb419374-04db-4b04-8d72-07c3cbfc1c7f · outbound

This paper cites Visual thinking.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Visual thinking

Reference 3

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This paper cites Whats the point: Semantic segmentation with point supervision.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Whats the point: Semantic segmentation with point supervision

Reference 4

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Observation 40a61c9c-bd86-4b5b-affe-6a053477ef81 · outbound

This paper cites Navier-stokes, ﬂuid dynamics, and image and video inpainting.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Navier-stokes, ﬂuid dynamics, and image and video inpainting

Reference 5

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Observation bb5a9d33-b637-4f14-a0b1-7e472adc6db8 · outbound

This paper cites Watershed-based segmen- tation and region merging.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Watershed-based segmen- tation and region merging

Reference 6

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Observation 77d82a2e-c856-4e9d-b5c0-0bd39b1f780c · outbound

This paper cites Cascade r-cnn: Delving into high quality object detection.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Cascade r-cnn: Delving into high quality object detection

Reference 7

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Observation f5b1dec4-acf9-47c9-9c03-be0fa8c93660 · outbound

This paper cites mmdetection.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting mmdetection

Reference 8

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Observation f0587fdb-63df-46b6-9f0f-cbf49e743100 · outbound

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

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Masklab: Instance segmentation by reﬁning object detection with semantic and direction features

Reference 9

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Observation dd966ec3-4b4f-4af3-b1b1-4496e2bbd80a · outbound

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

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting The cityscapes dataset for semantic urban scene understanding

Reference 10

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Observation 2f51168e-d44d-43b9-a74c-26e703fb81a9 · outbound

This paper cites Instance-sensitive fully convolutional networks.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Instance-sensitive fully convolutional networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:00:09.570398Z

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Observation 846a9719-9d49-4310-a3eb-616546a7e4b0 · outbound

This paper cites Boxsup: Exploit- ing bounding boxes to supervise convolutional networks for semantic segmentation.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Boxsup: Exploit- ing bounding boxes to supervise convolutional networks for semantic segmentation

Reference 12

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Observation 051aa940-dff8-4488-b4e9-d8b5875b6d25 · outbound

This paper cites Instance-aware se- mantic segmentation via multi-task network cascades.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Instance-aware se- mantic segmentation via multi-task network cascades

Reference 13

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This paper cites Learning Segmentation Masks with the Independence Prior.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Learning Segmentation Masks with the Independence Prior

Reference 14

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Observation 644723fb-f0f9-4409-ba10-1c78417a0412 · outbound

This paper cites Mod- eling visual context is key to augmenting object detection datasets.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Mod- eling visual context is key to augmenting object detection datasets

Reference 15

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Observation 2a281047-ac1b-44c7-829f-02efd41ea2d1 · outbound

This paper cites Cut, paste and learn: Surprisingly easy synthesis for instance de- tection.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Cut, paste and learn: Surprisingly easy synthesis for instance de- tection

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:00:09.527188Z

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Observation c8132b58-809b-45da-a09c-ea72cc211253 · outbound

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

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting The pascal visual object classes (voc) challenge

Reference 17

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Observation 242585a3-cbad-4ce7-af59-63438a2ee5ac · outbound

This paper cites Weakly and semi supervised human body part parsing via pose-guided knowledge trans- fer.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Weakly and semi supervised human body part parsing via pose-guided knowledge trans- fer

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:00:09.505355Z

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Observation 38c2dd46-0c58-4bfb-bc10-41afb1642ae8 · outbound

This paper cites Rmpe: Regional multi-person pose estimation.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Rmpe: Regional multi-person pose estimation

Reference 19

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This paper cites Contour integration by the human visual system: evidence for a local association ﬁeld.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Contour integration by the human visual system: evidence for a local association ﬁeld

Reference 20

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Observation cf0108a5-8b96-43c8-92de-f3f1ea20100f · outbound

This paper cites Look into person: Self-supervised structure- sensitive learning and a new benchmark for human parsing.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Look into person: Self-supervised structure- sensitive learning and a new benchmark for human parsing

Reference 21

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Observation df1b1fb2-a098-460f-9f38-2317bdeeba7e · outbound

This paper cites Semantic contours from inverse detectors.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Semantic contours from inverse detectors

Reference 22

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Observation 57be46cf-b0f1-4bdd-8982-682427d179e4 · outbound

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InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Mask r-cnn

Reference 23

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This paper cites A global sampling method for alpha matting.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting A global sampling method for alpha matting

Reference 24

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This paper cites Cooperative holistic scene understanding: Unifying 3d object, layout, and cam- era pose estimation.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Cooperative holistic scene understanding: Unifying 3d object, layout, and cam- era pose estimation

Reference 25

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This paper cites Lucid data dreaming for video object seg- mentation.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Lucid data dreaming for video object seg- mentation

Reference 26

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

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Crowdpose: Efﬁcient crowded scenes pose estimation and a new benchmark

Reference 27

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This paper cites Fully convolutional instance-aware semantic segmentation.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Fully convolutional instance-aware semantic segmentation

Reference 28

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Observation e4967778-bcc4-4768-b8fb-e4cbe760c4d9 · outbound

This paper cites Transferable interactiveness knowledge for human-object interaction de- tection.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Transferable interactiveness knowledge for human-object interaction de- tection

Reference 29

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

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Scribblesup: Scribble-supervised convolutional networks for semantic segmentation

Reference 30

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This paper cites Complex background subtraction by pursuing dynamic spatio-temporal models.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Complex background subtraction by pursuing dynamic spatio-temporal models

Reference 31

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This paper cites Feature pyramid networks for object detection.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Feature pyramid networks for object detection

Reference 32

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This paper cites Microsoft coco: Common objects in context.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Microsoft coco: Common objects in context

Reference 33

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This paper cites See more, know more: Unsuper- vised video object segmentation with co-attention siamese networks.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting See more, know more: Unsuper- vised video object segmentation with co-attention siamese networks

Reference 34

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This paper cites Learn- ing to segment object candidates.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Learn- ing to segment object candidates

Reference 35

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This paper cites Learning human-object interactions by graph parsing neural networks.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Learning human-object interactions by graph parsing neural networks

Reference 36

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This paper cites Faster R-CNN: Towards real-time object detection with re- gion proposal networks.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Faster R-CNN: Towards real-time object detection with re- gion proposal networks

Reference 37

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This paper cites Segmentation of un- known objects in indoor environments.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Segmentation of un- known objects in indoor environments

Reference 38

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This paper cites Find and focus: Retrieve and localize video events with natural language queries.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Find and focus: Retrieve and localize video events with natural language queries

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:00:09.259944Z

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Observation 75f78ad3-a43c-4025-a02c-56f38739b7c5 · outbound

This paper cites Visual perception: An introduction.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Visual perception: An introduction

Reference 40

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Observation 184f58a2-8ca4-4eb8-baba-b4745bdd7408 · outbound

This paper cites Salient Object Detection in the Deep Learning Era: An In-Depth Survey.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Salient Object Detection in the Deep Learning Era: An In-Depth Survey

Reference 41

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InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Saliency-aware video object segmentation

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:00:09.234097Z

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Observation 22b1efd9-8f07-416a-81cb-1edf7e5345cf · outbound

This paper cites Srda: Generat- ing instance segmentation annotation via scanning, reason- ing and domain adaptation.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Srda: Generat- ing instance segmentation annotation via scanning, reason- ing and domain adaptation

Reference 43

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Observation e870c532-fc59-4aba-825a-1e8a9e6b84c0 · outbound

This paper cites Explicit Shape Encoding for Real-Time Instance Segmentation.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting Explicit Shape Encoding for Real-Time Instance Segmentation

Reference 44

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This paper cites A stochastic gram- mar of images.

InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting A stochastic gram- mar of images

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:00:09.208147Z

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Pith citing papers

No inbound Pith citation observations are available.