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Paper Citation Record · LEDGER

Dense Match Summarization for Faster Two-view Estimation

As of 8 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2506.02893.

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

pith.paper-citation-record.v1
2506.02893 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:17:46.527526Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

40 of 40 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4e569257-c5d4-4390-976f-7e760b31dc00 · outbound

This paper cites Slic superpix- els compared to state-of-the-art superpixel methods.IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(11):2274–2282, 2012.

Dense Match Summarization for Faster Two-view Estimation Slic superpix- els compared to state-of-the-art superpixel methods.IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(11):2274–2282, 2012

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 92c0528b-a74d-47ee-a6c4-7fb8b52cbc47 · outbound

This paper cites Space-partitioning ransac.

Dense Match Summarization for Faster Two-view Estimation Space-partitioning ransac

Reference 2

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation a7cd77bd-fba5-4373-93c5-3f3ae5da2c71 · outbound

This paper cites MAGSAC: marginalizing sample consensus.

Dense Match Summarization for Faster Two-view Estimation MAGSAC: marginalizing sample consensus

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 32e2d8b6-787d-4c77-97ec-1b352c0b8fe1 · outbound

This paper cites Two-view geometry scoring without correspondences.

Dense Match Summarization for Faster Two-view Estimation Two-view geometry scoring without correspondences

Reference 4

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 42aecede-ba57-4662-8e37-1a8d9cd03225 · outbound

This paper cites Conic epipolar con- straints from affine correspondences.Computer Vision and Image Understanding (CVIU), 2014.

Dense Match Summarization for Faster Two-view Estimation Conic epipolar con- straints from affine correspondences.Computer Vision and Image Understanding (CVIU), 2014

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e1d2cf3f-eca0-4420-a3d3-bf2da2a5b60d · outbound

This paper cites Consensus-Adaptive RANSAC.

Dense Match Summarization for Faster Two-view Estimation Consensus-Adaptive RANSAC

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:17:46.780428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation f03659ba-2fe9-4d94-96c4-a435ec270478 · outbound

This paper cites Aspanformer: Detector-free image matching with adaptive span transformer.European Conference on Com- puter Vision (ECCV), 2022.

Dense Match Summarization for Faster Two-view Estimation Aspanformer: Detector-free image matching with adaptive span transformer.European Conference on Com- puter Vision (ECCV), 2022

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4791a925-09ef-4bf6-aa88-ccdea78c76e6 · outbound

This paper cites Chum and J.

Dense Match Summarization for Faster Two-view Estimation Chum and J

Reference 8

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation c3a06e8d-8871-4181-9a85-2554729d828c · outbound

This paper cites Optimal randomized ransac.

Dense Match Summarization for Faster Two-view Estimation Optimal randomized ransac

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 80543a9a-798a-4d9f-a2e1-a9c2b0cc0d69 · outbound

This paper cites Locally op- timized ransac.

Dense Match Summarization for Faster Two-view Estimation Locally op- timized ransac

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 8f1374c6-6f42-4f6c-a6ec-bac7049d85f3 · outbound

This paper cites Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner.

Dense Match Summarization for Faster Two-view Estimation Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner

Reference 11

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Source-reported events for the cited work

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Observation c0b331fb-0e9f-421a-b20d-1625ef49e45b · outbound

This paper cites Superpoint: Self-supervised interest point detection and description.

Dense Match Summarization for Faster Two-view Estimation Superpoint: Self-supervised interest point detection and description

Reference 12

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation dd032109-c6c1-40aa-9039-8b922931c64d · outbound

This paper cites The Faiss library.

Dense Match Summarization for Faster Two-view Estimation The Faiss library

Reference 13

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Source-reported events for the cited work

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Observation 3c128b58-c516-4ea3-8b81-4cbbd4d9a2bb · outbound

This paper cites D2- net: A trainable cnn for joint description and detection of local features.

Dense Match Summarization for Faster Two-view Estimation D2- net: A trainable cnn for joint description and detection of local features

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation f33c6ece-813b-4cad-bda9-3dff6fd3de32 · outbound

This paper cites DKM: Dense kernelized feature matching for geometry estimation.

Dense Match Summarization for Faster Two-view Estimation DKM: Dense kernelized feature matching for geometry estimation

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation da08725b-a3df-4882-8abf-361b75921423 · outbound

This paper cites RoMa: Robust Dense Feature Matching.Computer Vision and Pattern Recogni- tion (CVPR), 2024.

Dense Match Summarization for Faster Two-view Estimation RoMa: Robust Dense Feature Matching.Computer Vision and Pattern Recogni- tion (CVPR), 2024

Reference 16

Resolution
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Source-reported events for the cited work

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Observation d5622d65-17a1-47b4-b32a-05faec96f964 · outbound

This paper cites Affine correspon- dences between central cameras for rapid relative pose es- timation.

Dense Match Summarization for Faster Two-view Estimation Affine correspon- dences between central cameras for rapid relative pose es- timation

Reference 17

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 2b04179e-f1f1-45b1-bb84-5dd97bc180b4 · outbound

This paper cites Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography.Communications of the ACM, 24(6):381–395, 1981.

Dense Match Summarization for Faster Two-view Estimation Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography.Communications of the ACM, 24(6):381–395, 1981

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 15d276dc-6550-4ada-9b0f-40c74c113325 · outbound

This paper cites Fast glob- ally optimal surface normal estimation from an affine corre- spondence.

Dense Match Summarization for Faster Two-view Estimation Fast glob- ally optimal surface normal estimation from an affine corre- spondence

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9369bed2-1e0f-43c1-90f1-2a4b81052390 · outbound

This paper cites Cotr: Correspondence transformer for matching across images.

Dense Match Summarization for Faster Two-view Estimation Cotr: Correspondence transformer for matching across images

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6f0d3d59-a42c-43b6-8cf7-df3f2d5a919e · outbound

This paper cites Fast-slic.https://github.com/Algy/ fast-slic, 2019.

Dense Match Summarization for Faster Two-view Estimation Fast-slic.https://github.com/Algy/ fast-slic, 2019

Reference 21

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 08850baf-94bc-4651-b494-2a42efb43db0 · outbound

This paper cites Latent ransac.

Dense Match Summarization for Faster Two-view Estimation Latent ransac

Reference 22

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 119a4a8f-a056-4f6b-ac74-f4e38e96d752 · outbound

This paper cites PoseLib - Minimal Solvers for Camera Pose Estimation.https://github.com/ vlarsson/PoseLib, 2020.

Dense Match Summarization for Faster Two-view Estimation PoseLib - Minimal Solvers for Camera Pose Estimation.https://github.com/ vlarsson/PoseLib, 2020

Reference 23

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verified fuzzy
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e8e41bbf-38e4-4273-a35e-df21164e0bd6 · outbound

This paper cites Fixing the locally optimized ransac–full experimental evaluation.

Dense Match Summarization for Faster Two-view Estimation Fixing the locally optimized ransac–full experimental evaluation

Reference 24

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e6bb0013-3d4c-4c30-a237-41d96eda42a3 · outbound

This paper cites Ground- ing image matching in 3d with mast3r.

Dense Match Summarization for Faster Two-view Estimation Ground- ing image matching in 3d with mast3r

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:17:48.901710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e84e2bef-1ac6-4735-bcc0-05be5177445a · outbound

This paper cites Megadepth: Learning single- view depth prediction from internet photos.

Dense Match Summarization for Faster Two-view Estimation Megadepth: Learning single- view depth prediction from internet photos

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:17:48.680509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation c7706305-c076-4f35-8222-616360262cfc · outbound

This paper cites LightGlue: Local Feature Matching at Light Speed.

Dense Match Summarization for Faster Two-view Estimation LightGlue: Local Feature Matching at Light Speed

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:17:48.509934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:17:45.493912Z digest=sha256:565a132c95681d42b8d2126a6a1f3ca78cdeff3f256af14a72b94a52b6294b35

Observation 8e8f3bd7-5c67-4e43-bf39-5bba92889000 · outbound

This paper cites Distinctive image features from scale- invariant keypoints.International Journal of Computer Vi- sion (IJCV), 60:91–110, 2004.

Dense Match Summarization for Faster Two-view Estimation Distinctive image features from scale- invariant keypoints.International Journal of Computer Vi- sion (IJCV), 60:91–110, 2004

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-07T11:17:48.394872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation acbf2788-2ac4-4c46-b391-c54adb1f402e · outbound

This paper cites WxBS: Wide baseline stereo generalizations.

Dense Match Summarization for Faster Two-view Estimation WxBS: Wide baseline stereo generalizations

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:17:48.237690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 01cf5484-868c-486e-8560-7998632c4175 · outbound

This paper cites Groupsac: Efficient consensus in the presence of groupings.

Dense Match Summarization for Faster Two-view Estimation Groupsac: Efficient consensus in the presence of groupings

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:17:48.095385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:17:45.725177Z digest=sha256:476772cd314e229af87dee7591469aa9e1b75781231af3ad08101a14e41b7497

Observation b3f88836-b79b-4833-9716-ef842aaaeb31 · outbound

This paper cites An efficient solution to the five-point relative pose problem.IEEE Trans.

Dense Match Summarization for Faster Two-view Estimation An efficient solution to the five-point relative pose problem.IEEE Trans

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:17:47.966191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4ee67a8d-8428-49b4-82c8-36a134ef290b · outbound

This paper cites Accurate Motion Estimation through Random Sample Aggregated Consensus.

Dense Match Summarization for Faster Two-view Estimation Accurate Motion Estimation through Random Sample Aggregated Consensus

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:17:46.661003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:17:45.894422Z digest=sha256:d5c3dd1a26614432dc4e1872ea8003621fb365c3d33c8987e57d98746cc486cc

Observation 78cd51c6-2ab2-4f08-8bbb-f3623ed84343 · outbound

This paper cites Theory and practice of structure-from-motion using affine correspondences.

Dense Match Summarization for Faster Two-view Estimation Theory and practice of structure-from-motion using affine correspondences

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-07T11:17:47.829693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:17:45.974334Z digest=sha256:dfb192288ef15ad7688c60f9d7d68eca54f3699ab0cf154801eccc99da25c50a

Observation 60084667-671e-4a3d-aee1-6f4c38a6826b · outbound

This paper cites an unresolved cited work.

Dense Match Summarization for Faster Two-view Estimation Unresolved cited work

Reference 34

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unresolved
raw_fallback, observed 2026-08-07T11:17:47.677413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:17:46.037806Z digest=sha256:69be8ca92376d829bd087ff8f878769de924a85623fd602646ad27f881bf05b5

Observation a246f053-c16d-43e3-bdec-2545b91de078 · outbound

This paper cites Superglue: Learning feature matching with graph neural networks.

Dense Match Summarization for Faster Two-view Estimation Superglue: Learning feature matching with graph neural networks

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:17:47.558948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:17:46.132533Z digest=sha256:51b3851fee7ac3d42a2bfced897998cb2021cff94fbc353d99d1d8b27ffd5765

Observation b87e1796-1ddd-4fc6-b237-4ab7ef69cf99 · outbound

This paper cites LoFTR: Detector-free local feature matching with transformers.Computer Vision and Pattern Recognition (CVPR), 2021.

Dense Match Summarization for Faster Two-view Estimation LoFTR: Detector-free local feature matching with transformers.Computer Vision and Pattern Recognition (CVPR), 2021

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:17:47.421550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:17:46.199383Z digest=sha256:c36a6ff06f3a771b28d5ec9f27df69c1de6aa255df6ff9159dce306f6455cefb

Observation 1c74d1a0-8de1-4d0b-8507-be8132ea7bae · outbound

This paper cites Torr and A.

Dense Match Summarization for Faster Two-view Estimation Torr and A

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:17:47.281173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:17:46.259197Z digest=sha256:fd44a46d893515f76911ad372083b0caa0efe1b266b4e4c23d3752b2a46dc4ff

Observation 7f7b57e7-9d62-45fd-aa8f-265dda85f447 · outbound

This paper cites P1ac: Revisiting absolute pose from a sin- gle affine correspondence.

Dense Match Summarization for Faster Two-view Estimation P1ac: Revisiting absolute pose from a sin- gle affine correspondence

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:17:47.152352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:17:46.341636Z digest=sha256:6c8042a034d111f1996c9c1695abb4d028f5034e70e657fdbd2e3163b2ea1d3a

Observation 76117f79-c281-4fc8-8efb-54f8088ed96f · outbound

This paper cites Adaptive reorder- ing sampler with neurally guided magsac.

Dense Match Summarization for Faster Two-view Estimation Adaptive reorder- ing sampler with neurally guided magsac

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:17:47.027872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:17:46.436584Z digest=sha256:b30a30d8182e56aab90d7aa06fb1440c00eae4a7e039996e645bfcaff8215cc8

Observation 5a5078f9-120c-4c2f-b975-3ba985f94d1a · outbound

This paper cites In addition to AUC@5 ◦, we also present AUC@10◦ and AUC@20◦.

Dense Match Summarization for Faster Two-view Estimation In addition to AUC@5 ◦, we also present AUC@10◦ and AUC@20◦

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:17:46.908720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:17:46.527526Z digest=sha256:b18efada664cf58cb3d1c8cc749c4e515ec7d51412109c63465eccce11301cbe

Pith citing papers

No inbound Pith citation observations are available.