A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition | Paper Citation Record

Observation 11c927e7-ac06-4333-a49c-4d4af3e0eac4 · outbound

This paper cites write newline.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition write newline

Reference 1

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Observation 9e8b3a97-bdbb-4cf4-80c1-95f0f306d0f9 · outbound

This paper cites Database-friendly random projections: J ohnson- L indenstrauss with binary coins.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Database-friendly random projections: J ohnson- L indenstrauss with binary coins

Reference 2

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Observation 878da734-3e64-4235-a6fc-6bf79e2fefb9 · outbound

This paper cites Gsv-cities: Toward appropriate supervised visual place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Gsv-cities: Toward appropriate supervised visual place recognition

Reference 3

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This paper cites Mixvpr: Feature mixing for visual place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Mixvpr: Feature mixing for visual place recognition

Reference 4

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This paper cites Boq: A place is worth a bag of learnable queries.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Boq: A place is worth a bag of learnable queries

Reference 5

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This paper cites All about VLAD.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition All about VLAD

Reference 6

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Observation 33b12d7c-c046-447d-ad71-ba1529c6bae3 · outbound

This paper cites NetVLAD: CNN architecture for weakly supervised place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition NetVLAD: CNN architecture for weakly supervised place recognition

Reference 7

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Observation 1849850c-5ec6-449a-bfd7-9d03cbc8f3fc · outbound

This paper cites Are local features all you need for cross-domain visual place recognition? In IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 6155--6165, 2023.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Are local features all you need for cross-domain visual place recognition? In IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 6155--6165, 2023

Reference 8

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Observation 8fe7de12-8607-409d-b601-73087464f910 · outbound

This paper cites Speeded-up robust features (SURF).

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Speeded-up robust features (SURF)

Reference 9

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Observation cb92efad-c7d8-49c3-83e9-2e2d8ce7b274 · outbound

This paper cites Rethinking visual geo-localization for large-scale applications.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Rethinking visual geo-localization for large-scale applications

Reference 10

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Observation e65afcab-15ed-4ae9-a183-12d17f81729e · outbound

This paper cites Eigenplaces: Training viewpoint robust models for visual place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Eigenplaces: Training viewpoint robust models for visual place recognition

Reference 11

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This paper cites MeshVPR: Citywide Visual Place Recognition Using 3D Meshes.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition MeshVPR: Citywide Visual Place Recognition Using 3D Meshes

Reference 12

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This paper cites Adaptive-attentive geolocalization from few queries: A hybrid approach.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Adaptive-attentive geolocalization from few queries: A hybrid approach

Reference 13

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This paper cites The SFU mountain dataset: S emi-structured woodland trails under changing environmental conditions.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition The SFU mountain dataset: S emi-structured woodland trails under changing environmental conditions

Reference 14

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

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age

Reference 15

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This paper cites Unifying deep local and global features for image search.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Unifying deep local and global features for image search

Reference 16

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This paper cites A survey on map-based localization techniques for autonomous vehicles.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition A survey on map-based localization techniques for autonomous vehicles

Reference 17

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This paper cites Superposition of many models into one.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Superposition of many models into one

Reference 18

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This paper cites Practice makes perfect? managing and leveraging visual experiences for lifelong navigation.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Practice makes perfect? managing and leveraging visual experiences for lifelong navigation

Reference 19

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This paper cites Visual categorization with bags of keypoints.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Visual categorization with bags of keypoints

Reference 20

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This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition An image is worth 16x16 words: Transformers for image recognition at scale

Reference 21

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This paper cites Simultaneous localization and mapping: part I.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Simultaneous localization and mapping: part I

Reference 22

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This paper cites Event-based visual place recognition with ensembles of temporal windows.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Event-based visual place recognition with ensembles of temporal windows

Reference 23

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This paper cites Where is your place, visual place recognition? In International Joint Conferences on Artificial Intelligence, pages 4416--4425, 2021.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Where is your place, visual place recognition? In International Joint Conferences on Artificial Intelligence, pages 4416--4425, 2021

Reference 24

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This paper cites Classification using hyperdimensional computing: A review.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Classification using hyperdimensional computing: A review

Reference 25

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This paper cites A survey on vision transformer.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition A survey on vision transformer

Reference 26

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This paper cites Patch-NetVLAD: Multi-scale fusion of locally-global descriptors for place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Patch-NetVLAD: Multi-scale fusion of locally-global descriptors for place recognition

Reference 27

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This paper cites Fe-fusion-vpr: Attention-based multi-scale network architecture for visual place recognition by fusing frames and events.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Fe-fusion-vpr: Attention-based multi-scale network architecture for visual place recognition by fusing frames and events

Reference 28

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This paper cites Dasgil: Domain adaptation for semantic and geometric-aware image-based localization.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Dasgil: Domain adaptation for semantic and geometric-aware image-based localization

Reference 29

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This paper cites Spiking neural networks for visual place recognition via weighted neuronal assignments.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Spiking neural networks for visual place recognition via weighted neuronal assignments

Reference 30

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This paper cites Applications of Spiking Neural Networks in Visual Place Recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Applications of Spiking Neural Networks in Visual Place Recognition

Reference 31

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This paper cites Optimal transport aggregation for visual place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Optimal transport aggregation for visual place recognition

Reference 32

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This paper cites Autonomous multisensor calibration and closed-loop fusion for slam.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Autonomous multisensor calibration and closed-loop fusion for slam

Reference 33

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This paper cites Aggregating local descriptors into a compact image representation.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Aggregating local descriptors into a compact image representation

Reference 34

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This paper cites In-memory hyperdimensional computing.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition In-memory hyperdimensional computing

Reference 35

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This paper cites Anyloc: Towards universal visual place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Anyloc: Towards universal visual place recognition

Reference 36

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This paper cites Classification and recall with binary hyperdimensional computing: Tradeoffs in choice of density and mapping characteristics.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Classification and recall with binary hyperdimensional computing: Tradeoffs in choice of density and mapping characteristics

Reference 37

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This paper cites A survey on hyperdimensional computing aka vector symbolic architectures, part ii: Applications, cognitive models, and challenges.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition A survey on hyperdimensional computing aka vector symbolic architectures, part ii: Applications, cognitive models, and challenges

Reference 38

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This paper cites A survey on localization for autonomous vehicles.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition A survey on localization for autonomous vehicles

Reference 39

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This paper cites Data-efficient large scale place recognition with graded similarity supervision.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Data-efficient large scale place recognition with graded similarity supervision

Reference 40

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This paper cites Work smart, not hard: Recalling relevant experiences for vast-scale but time-constrained localisation.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Work smart, not hard: Recalling relevant experiences for vast-scale but time-constrained localisation

Reference 41

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A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Unresolved cited work

Reference 42

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This paper cites Visual place recognition: A survey.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Visual place recognition: A survey

Reference 43

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This paper cites CricaVPR: Cross-image Correlation-aware Representation Learning for Visual Place Recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition CricaVPR: Cross-image Correlation-aware Representation Learning for Visual Place Recognition

Reference 44

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This paper cites Towards seamless adaptation of pre-trained models for visual place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Towards seamless adaptation of pre-trained models for visual place recognition

Reference 45

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This paper cites Similarity min-max: Zero-shot day-night domain adaptation.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Similarity min-max: Zero-shot day-night domain adaptation

Reference 46

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This paper cites 1 Year, 1000km: The Oxford RobotCar Dataset.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition 1 Year, 1000km: The Oxford RobotCar Dataset

Reference 47

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This paper cites A survey on deep visual place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition A survey on deep visual place recognition

Reference 48

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This paper cites Learnable pooling with Context Gating for video classification.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Learnable pooling with Context Gating for video classification

Reference 49

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This paper cites Intelligent reference curation for visual place recognition via bayesian selective fusion.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Intelligent reference curation for visual place recognition via bayesian selective fusion

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.837232Z

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Observation ac326024-4a9b-43a6-9c14-3993ab4fa617 · outbound

This paper cites From omnidirectional images to hierarchical localization.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition From omnidirectional images to hierarchical localization

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.803828Z

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This paper cites Hyperdimensional computing as a framework for systematic aggregation of image descriptors.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Hyperdimensional computing as a framework for systematic aggregation of image descriptors

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.795372Z

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This paper cites An introduction to hyperdimensional computing for robotics.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition An introduction to hyperdimensional computing for robotics

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.784791Z

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Observation 50f42770-9142-4528-98fc-fbda6a0eda4b · outbound

This paper cites Vector semantic representations as descriptors for visual place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Vector semantic representations as descriptors for visual place recognition

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.773740Z

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Observation 96917bd4-6008-4491-885c-ac1e25b76b7a · outbound

This paper cites Large-scale image retrieval with attentive deep local features.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Large-scale image retrieval with attentive deep local features

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.668000Z

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This paper cites Fisher kernels on visual vocabularies for image categorization.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Fisher kernels on visual vocabularies for image categorization

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.604950Z

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Observation ccfd6bbb-300a-41b8-8548-d415c3183eee · outbound

This paper cites Large-scale image retrieval with compressed fisher vectors.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Large-scale image retrieval with compressed fisher vectors

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.596184Z

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This paper cites On model-free re-ranking for visual place recognition with deep learned local features.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition On model-free re-ranking for visual place recognition with deep learned local features

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.587313Z

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Observation 35ac0543-1f2f-4a7c-9fbe-7770f1411394 · outbound

This paper cites An outlook into the future of egocentric vision.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition An outlook into the future of egocentric vision

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.576605Z

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Observation 8d37b5ce-4101-422b-8757-a3a1b39b4424 · outbound

This paper cites Cnn image retrieval learns from bow: Unsupervised fine-tuning with hard examples.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Cnn image retrieval learns from bow: Unsupervised fine-tuning with hard examples

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.415942Z

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This paper cites Fine-tuning cnn image retrieval with no human annotation.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Fine-tuning cnn image retrieval with no human annotation

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.299765Z

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This paper cites Learning with average precision: Training image retrieval with a listwise loss.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Learning with average precision: Training image retrieval with a listwise loss

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.287855Z

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Observation 8e2971b0-0e8e-47f3-b6aa-39d0563eef81 · outbound

This paper cites Leveraging deep visual descriptors for hierarchical efficient localization.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Leveraging deep visual descriptors for hierarchical efficient localization

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.277250Z

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Observation bd91e401-5c61-47d6-800a-5c87e3f44439 · outbound

This paper cites From coarse to fine: Robust hierarchical localization at large scale.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition From coarse to fine: Robust hierarchical localization at large scale

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:36.266071Z

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

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Superglue: Learning feature matching with graph neural networks

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.960929Z

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Observation 74b09358-e242-4589-8807-0efaa4bf15b4 · outbound

This paper cites Lamar: Benchmarking localization and mapping for augmented reality.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Lamar: Benchmarking localization and mapping for augmented reality

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.790217Z

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Observation 8f122bd0-c074-4c4f-9271-c4dc1496a6ac · outbound

This paper cites A comparison of vector symbolic architectures.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition A comparison of vector symbolic architectures

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.784095Z

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Observation c705430f-9aad-40bc-a46a-71722159f3fd · outbound

This paper cites Visual place recognition in changing environments using additional data-inherent knowledge.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Visual place recognition in changing environments using additional data-inherent knowledge

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.775584Z

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Observation e37a4d7c-3831-4da8-aaf9-4148bf30cdbb · outbound

This paper cites Visual place recognition: A tutorial.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Visual place recognition: A tutorial

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.768113Z

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Observation c87b6bb4-49c7-4167-82fc-0415b839398f · outbound

This paper cites Omnidirectional multisensory perception fusion for long-term place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Omnidirectional multisensory perception fusion for long-term place recognition

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.556268Z

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Observation 0230690c-a28e-44eb-bc8d-7a21a2d361b9 · outbound

This paper cites Video google: A text retrieval approach to object matching in videos.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Video google: A text retrieval approach to object matching in videos

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.428295Z

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This paper cites Are we there yet? challenging seqslam on a 3000 km journey across all four seasons.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Are we there yet? challenging seqslam on a 3000 km journey across all four seasons

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.420177Z

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This paper cites Long-term visual localization revisited.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Long-term visual localization revisited

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.412032Z

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Observation f837aa28-79e1-48e3-9bcd-81fd188d52c5 · outbound

This paper cites Divide&classify: Fine-grained classification for city-wide visual geo-localization.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Divide&classify: Fine-grained classification for city-wide visual geo-localization

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.405067Z

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Observation 21a3ba9b-0b8d-4ae5-a49e-aa2bebeaec50 · outbound

This paper cites The revisiting problem in simultaneous localization and mapping: A survey on visual loop closure detection.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition The revisiting problem in simultaneous localization and mapping: A survey on visual loop closure detection

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.271333Z

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Observation 473a4eb1-287b-4cb2-8e33-d0c8abd0dd97 · outbound

This paper cites EffoVPR: Effective Foundation Model Utilization for Visual Place Recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition EffoVPR: Effective Foundation Model Utilization for Visual Place Recognition

Reference 76

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This paper cites Effective visual place recognition using multi-sequence maps.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Effective visual place recognition using multi-sequence maps

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.075203Z

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Observation 8aff3bc1-695d-46a7-bc55-cc40ef6243c1 · outbound

This paper cites Transvpr: Transformer-based place recognition with multi-level attention aggregation.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Transvpr: Transformer-based place recognition with multi-level attention aggregation

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.037442Z

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Observation 4fb8466b-514c-4e96-9655-1b876758ee2d · outbound

This paper cites Mapillary street-level sequences: A dataset for lifelong place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Mapillary street-level sequences: A dataset for lifelong place recognition

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.027933Z

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Observation c7eba5f2-ed31-4c74-808d-63a51002073e · outbound

This paper cites Hyperdimensional feature fusion for out-of-distribution detection.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Hyperdimensional feature fusion for out-of-distribution detection

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:35.017391Z

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Observation e1ff99aa-8ada-4f77-9d61-333dba20c4d6 · outbound

This paper cites Real-time visual place recognition based on analyzing distribution of multi-scale cnn landmarks.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Real-time visual place recognition based on analyzing distribution of multi-scale cnn landmarks

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:34.842478Z

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Observation 04538dbf-48df-471d-9989-bad889b6be2f · outbound

This paper cites Probabilistic visual place recognition for hierarchical localization.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Probabilistic visual place recognition for hierarchical localization

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:34.621292Z

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Observation 51796880-60ad-4964-98d1-7bc5bed5cb16 · outbound

This paper cites Dolg: Single-stage image retrieval with deep orthogonal fusion of local and global features.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Dolg: Single-stage image retrieval with deep orthogonal fusion of local and global features

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:34.614421Z

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Observation 48289582-d90e-425d-a35b-46c6192420df · outbound

This paper cites Spatial pyramid-enhanced NetVLAD with weighted triplet loss for place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Spatial pyramid-enhanced NetVLAD with weighted triplet loss for place recognition

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:34.606301Z

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Observation 4084f7fd-c209-4a42-855f-55c68371bce3 · outbound

This paper cites Etr: An efficient transformer for re-ranking in visual place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Etr: An efficient transformer for re-ranking in visual place recognition

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:34.596332Z

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Observation e0bf05a1-4231-4947-a8cb-dd477516e576 · outbound

This paper cites Visual place recognition: A survey from deep learning perspective.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition Visual place recognition: A survey from deep learning perspective

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:34.587575Z

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Observation 16f06a2c-44ae-4ac2-95b5-21b6561bafbe · outbound

This paper cites R2former: Unified retrieval and reranking transformer for place recognition.

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition R2former: Unified retrieval and reranking transformer for place recognition

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:03:34.350087Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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