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Paper Citation Record · LEDGER

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization

As of 15 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2507.11653.

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

pith.paper-citation-record.v1
2507.11653 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:10:10.459556Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

43 of 43 outbound references displayed

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  • verified fuzzy35
  • unresolved7
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6f21c39e-b635-4d3d-b040-cee8252c69d6 · outbound

This paper cites A robust localization solution for an uncrewed ground vehicle in unstructured outdoor gnss-denied environments,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization A robust localization solution for an uncrewed ground vehicle in unstructured outdoor gnss-denied environments,

Reference 1

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Observation 3e464c56-7b72-4ff1-9acb-04091c6ab049 · outbound

This paper cites A survey on global lidar localization: Challenges, advances and open problems,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization A survey on global lidar localization: Challenges, advances and open problems,

Reference 2

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 5e62dd62-f1b9-4a20-a3d7-89f72a5d6e63 · outbound

This paper cites Sos- match: segmentation for open-set robust correspondence search and robot localization in unstructured environments,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Sos- match: segmentation for open-set robust correspondence search and robot localization in unstructured environments,

Reference 3

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Source-reported events for the cited work

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Observation 9f3d4bc5-808a-4dde-95a1-5d791509b132 · outbound

This paper cites Bags of binary words for fast place recognition in image sequences,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Bags of binary words for fast place recognition in image sequences,

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation a192f574-a57d-40fc-b4fc-02976099553f · outbound

This paper cites X-view: Graph-based semantic multi-view localization,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization X-view: Graph-based semantic multi-view localization,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c52fac34-4851-48b9-b1f6-8e7351c7c3cd · outbound

This paper cites Visual place recognition: A survey,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Visual place recognition: A survey,

Reference 6

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d466a63c-1b82-4dab-b2eb-a7fd523cd268 · outbound

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

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization D2-net: A trainable cnn for joint description and detection of local features,

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1cb1f386-975b-4a59-9e7b-7b0e988103ab · outbound

This paper cites Appearance-Invariant 6-DoF Visual Localization using Generative Adversarial Networks.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Appearance-Invariant 6-DoF Visual Localization using Generative Adversarial Networks

Reference 8

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d15d2ada-cd16-45f9-a84a-75260f26c98e · outbound

This paper cites Kimera-multi: Robust, distributed, dense metric-semantic slam for multi-robot systems,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Kimera-multi: Robust, distributed, dense metric-semantic slam for multi-robot systems,

Reference 9

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 517d2e76-fd00-4aa7-b7b6-37784374cf72 · outbound

This paper cites Semantic pose verification for outdoor visual localization with self-supervised contrastive learn- ing,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Semantic pose verification for outdoor visual localization with self-supervised contrastive learn- ing,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation fa2945bc-4fb9-4e8f-9b5f-24ff35e07973 · outbound

This paper cites ROMAN: Open-Set Object Map Alignment for Robust View-Invariant Global Localization.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization ROMAN: Open-Set Object Map Alignment for Robust View-Invariant Global Localization

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a4fa4e9a-c8b6-4b50-92b5-9c792d23c851 · outbound

This paper cites Segment anything,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Segment anything,

Reference 12

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unresolved
no resolver link, observed 2026-08-06T17:10:10.325557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b661f6ea-e6ef-4343-a3d7-b73c349c4f63 · outbound

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

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization SAM 2: Segment Anything in Images and Videos

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T17:10:10.329676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3f97393d-1094-4243-9d3c-c03bb3a68d2b · outbound

This paper cites Elasticfusion: Dense slam without a pose graph.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Elasticfusion: Dense slam without a pose graph

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 2026-08-15T06:32:42.880941+00:00.

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Observation b6f075ef-ae16-49ff-8d2b-b4971f6e31b6 · outbound

This paper cites Gaussian-slam: Photo- realistic dense slam with gaussian splatting,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Gaussian-slam: Photo- realistic dense slam with gaussian splatting,

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c79d0594-7150-45b0-a476-72581152bec3 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Nerf: Representing scenes as neural radiance fields for view synthesis,

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 238afba4-7df1-4ef0-a7b1-9b401e91a3f6 · outbound

This paper cites Real-time 3d reconstruction at scale using voxel hashing,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Real-time 3d reconstruction at scale using voxel hashing,

Reference 17

Resolution
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Source-reported events for the cited work

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Observation 4f344c94-c9a8-4648-b4ca-12e424fc5255 · outbound

This paper cites Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age,

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b6439543-bb93-4fdb-8fb3-8cf5b2856c2c · outbound

This paper cites Cubeslam: Monocular 3-d object slam,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Cubeslam: Monocular 3-d object slam,

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 2026-08-15T06:32:42.880941+00:00.

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Observation b569e6fe-4300-458d-81b8-36ca7e10e0e4 · outbound

This paper cites Quadricslam: Dual quadrics from object detections as landmarks in object-oriented slam,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Quadricslam: Dual quadrics from object detections as landmarks in object-oriented slam,

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 2026-08-15T06:32:42.880941+00:00.

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Observation 10942cfd-c0a5-44e0-97d3-19ccaedc55d5 · outbound

This paper cites Distinctive image features from scale-invariant key- points,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Distinctive image features from scale-invariant key- points,

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e99531cc-22f2-4a22-98d8-dbb90114129e · outbound

This paper cites Speeded-up robust features (surf),.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Speeded-up robust features (surf),

Reference 22

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 49c34cfa-b211-4385-a159-c3518178ec4e · outbound

This paper cites Orb: An efficient alternative to sift or surf,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Orb: An efficient alternative to sift or surf,

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 18ef4dd3-bdaf-49c3-bb70-eb2af82073ce · outbound

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

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Superpoint: Self- supervised interest point detection and description,

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 2026-08-15T06:32:42.880941+00:00.

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Observation 86e78336-c93e-469e-9687-421f38418019 · outbound

This paper cites Su- perglue: Learning feature matching with graph neural networks,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Su- perglue: Learning feature matching with graph neural networks,

Reference 25

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 861a162e-b0b6-4cff-aaec-acd1e54933b1 · outbound

This paper cites Loftr: Detector- free local feature matching with transformers,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Loftr: Detector- free local feature matching with transformers,

Reference 26

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f70dca98-9cdc-4c05-b1d7-0592983fee0c · outbound

This paper cites Anyloc: Towards universal visual place recognition,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Anyloc: Towards universal visual place recognition,

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 1b0bcb87-914a-4776-8aeb-89765290629f · outbound

This paper cites Image segmentation using deep learning: A survey,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Image segmentation using deep learning: A survey,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.791285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 63d5c3a0-c7b1-46e9-9d10-ad080deebab5 · outbound

This paper cites Towards high- definition 3d urban mapping: Road feature-based registration of mobile mapping systems and aerial imagery,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Towards high- definition 3d urban mapping: Road feature-based registration of mobile mapping systems and aerial imagery,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.772401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation fd6bffc5-fb5e-4eed-a862-0e2dbf731437 · outbound

This paper cites Scan context++: Structural place recog- nition robust to rotation and lateral variations in urban environments,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Scan context++: Structural place recog- nition robust to rotation and lateral variations in urban environments,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.756753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 2b811447-e46f-456e-ad8d-7470dec8ccf0 · outbound

This paper cites Visual map matching and localization using a global feature map,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Visual map matching and localization using a global feature map,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.742463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation f636c72d-13a4-4413-912e-9fb15ba34b5c · outbound

This paper cites Present and future of slam in extreme environments: The darpa subt challenge,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Present and future of slam in extreme environments: The darpa subt challenge,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.727160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T17:10:10.412377Z digest=sha256:828d63c22629351cdeda40328ee0716a79c62dbcf503c27dd805da2cb63efd22

Observation 9ade2b0a-383d-47f4-92d4-e3aa55ed42a6 · outbound

This paper cites Search and rescue under the forest canopy using multiple uavs,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Search and rescue under the forest canopy using multiple uavs,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.711597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T17:10:10.416314Z digest=sha256:0cb4b2b95d81f9056cc3da298c80fe52271d76799632a992082c63af4fecbe6f

Observation df32f01f-0ada-40af-a61e-380de3ac64ec · outbound

This paper cites Forestvo: Enhancing visual odometry in forest environments through forestglue,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Forestvo: Enhancing visual odometry in forest environments through forestglue,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.694926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T17:10:10.420195Z digest=sha256:72bf77f6990a7da037d06d9e8f6ff789c869e6dd485836b166aa39d17ef85ee9

Observation e4ca5231-3e22-4a1d-a5d7-c3b8220bd548 · outbound

This paper cites Interpretation of image segmentation in terms of justifiable granularity,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Interpretation of image segmentation in terms of justifiable granularity,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.678970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T17:10:10.424641Z digest=sha256:17140791fa2f2273752dfa3764e1259512b662733df25d6cd3f2fda39df6b2ed

Observation 943d6a11-e18e-4ac7-8ab7-03f765f13e84 · outbound

This paper cites Semantic-sam: Segment and recognize anything at any granularity,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Semantic-sam: Segment and recognize anything at any granularity,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.664213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T17:10:10.429839Z digest=sha256:37d76f38589733a41e77682366bf3d7e349d620e49297be5c768bb0b882ebb2f

Observation 2b9ac686-542c-471f-baf2-80537fa79254 · outbound

This paper cites Factor graphs for robot perception,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Factor graphs for robot perception,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.648821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T17:10:10.434320Z digest=sha256:5f8c24968ea17ae3328b17bd014ecf82dc7e321c7693808c4020e23c3762e266

Observation 28ffb643-0553-4975-90db-221cde6b2180 · outbound

This paper cites Factor graphs and gtsam: A hands-on introduction,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Factor graphs and gtsam: A hands-on introduction,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.635113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T17:10:10.438553Z digest=sha256:61d7d383986bdafc1ace9f105064bf3c1204447b3ee028279d3437cb227cba48

Observation bfa6189d-ef60-4461-b95b-64bbbc2c3519 · outbound

This paper cites Clipper: A graph-theoretic framework for robust data association,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Clipper: A graph-theoretic framework for robust data association,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.618785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T17:10:10.442551Z digest=sha256:75ec11e6eace38824f5bf9cf6e55c416eee1f79dee808904d078d8e184118d45

Observation 2dc5b237-28ff-4add-8179-c25fc4c26d56 · outbound

This paper cites Clipper: Robust data association without an initial guess,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Clipper: Robust data association without an initial guess,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.602527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T17:10:10.446676Z digest=sha256:f547538524054bfcddd70aa0a461315ef8dbf7a61feec87444bff2e3ac0ad156

Observation 5657a69f-51f3-46b4-a538-62de860780ce · outbound

This paper cites Least-squares fitting of two 3-d point sets,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Least-squares fitting of two 3-d point sets,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.587442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T17:10:10.450875Z digest=sha256:6c36b0732443381ed501e5071d902703af1d2fb6ae70fc96680df3159fbe02c5

Observation 00d8bc17-2ffb-4ab2-8452-76d609ea7c15 · outbound

This paper cites Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.572445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T17:10:10.455053Z digest=sha256:6ffe8e856b59e813d69504bf49aea4324a490c496c3be00f528935c3c1863b0d

Observation 262331bd-35a9-41e2-b6b8-0bb5be343961 · outbound

This paper cites Airsim: High-fidelity visual and physical simulation for autonomous vehicles,.

VISTA: Monocular Segmentation-Based Mapping for Appearance and View-Invariant Global Localization Airsim: High-fidelity visual and physical simulation for autonomous vehicles,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:10:10.557645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T17:10:10.459556Z digest=sha256:bcfee6e95ee042ce57664eb7bbfcb7068a7b0b9480ecfc30ddf1b50c4f34fb01

Pith citing papers

No inbound Pith citation observations are available.