Paper Citation Record · LEDGER

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain

As of 13 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2411.13988.

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

pith.paper-citation-record.v1
2411.13988 v1

Coverage vector

measured 35 of 35 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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External citation measurements

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Outbound references

Observation 48523cd3-e2a8-40fa-b0ca-a1eb48423902 · outbound

This paper cites Real-time positioning and tracking for vision-based unmanned underwater vehicles,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Real-time positioning and tracking for vision-based unmanned underwater vehicles,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.612650Z

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Observation df38154d-0c98-47b5-8751-aac1343bb43d · outbound

This paper cites A survey on underwater computer vision,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain A survey on underwater computer vision,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.595431Z

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Observation fc18a8f2-f9ab-4b69-9f58-2700bec529d1 · outbound

This paper cites Experimental comparison of open source vision- based state estimation algorithms,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Experimental comparison of open source vision- based state estimation algorithms,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.579019Z

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Observation 07c97177-901b-4eb5-9ba5-cfa2e9547204 · outbound

This paper cites Underwater navigation, localization and path planning for autonomous vehicles: A review,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Underwater navigation, localization and path planning for autonomous vehicles: A review,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.562730Z

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Observation 4877a552-5883-4cb2-9995-70abb25ff72b · outbound

This paper cites Vinet: Visual-inertial odometry as a sequence-to-sequence learning problem,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Vinet: Visual-inertial odometry as a sequence-to-sequence learning problem,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.545441Z

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Observation 7a162280-7b5b-471a-a99a-6ac3729957b3 · outbound

This paper cites Multisensor fusion for marine infrastructures’ inspection and safety,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Multisensor fusion for marine infrastructures’ inspection and safety,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.528533Z

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Observation 358d8096-7a39-4b8e-b17f-71fc7eb4ed9f · outbound

This paper cites Ego-motion estimation using recurrent convolutional neural networks through optical flow learning,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Ego-motion estimation using recurrent convolutional neural networks through optical flow learning,

Reference 7

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Observation f42fbaa9-4312-4813-952b-540de35b7efb · outbound

This paper cites Selfvio: Self-supervised deep monocu- lar visual–inertial odometry and depth estimation,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Selfvio: Self-supervised deep monocu- lar visual–inertial odometry and depth estimation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.494752Z

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Observation e0844423-1f9d-424a-b450-bd710d39a60a · outbound

This paper cites Efficient deep visual and iner- tial odometry with adaptive visual modality selection,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Efficient deep visual and iner- tial odometry with adaptive visual modality selection,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.477648Z

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Observation 87c89716-78e6-4986-bc88-5b1b397b4296 · outbound

This paper cites Visibility enhancement for underwater visual slam based on underwater light scattering model,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Visibility enhancement for underwater visual slam based on underwater light scattering model,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.460334Z

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Observation 249e60d5-7f2c-4cfa-8ee5-e3967d8fe70b · outbound

This paper cites An underwater image enhancement method for simultaneous localization and mapping of autonomous underwater vehicle,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain An underwater image enhancement method for simultaneous localization and mapping of autonomous underwater vehicle,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.443606Z

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Observation a745972d-5890-4072-9ec4-807ede58c8de · outbound

This paper cites Real-time gan-based image enhancement for robust underwater monocular slam,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Real-time gan-based image enhancement for robust underwater monocular slam,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.426598Z

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Observation 63308d27-caf4-408f-9e12-d2a140aa410d · outbound

This paper cites Underwater image super- resolution using deep residual multipliers,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Underwater image super- resolution using deep residual multipliers,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.407039Z

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Observation a3a77474-00ab-4d54-afba-650680c1d7fc · outbound

This paper cites Real-time image enhancement for vision-based autonomous underwater vehicle nav- igation in murky waters,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Real-time image enhancement for vision-based autonomous underwater vehicle nav- igation in murky waters,

Reference 14

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Observation cc46e288-041e-4678-b778-a1da9c142807 · outbound

This paper cites A multi-state constraint kalman filter for vision-aided inertial navigation,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain A multi-state constraint kalman filter for vision-aided inertial navigation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.373397Z

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Observation 97a910a7-002c-4db2-b0db-4fc9cd8c0f45 · outbound

This paper cites Rd-vio: Relative-depth- aided visual-inertial odometry for autonomous underwater vehicles,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Rd-vio: Relative-depth- aided visual-inertial odometry for autonomous underwater vehicles,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.354087Z

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Observation 7695a287-35ee-4de2-acf2-9b3c1357307b · outbound

This paper cites Keyframe-based visual–inertial odometry using nonlinear optimization,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Keyframe-based visual–inertial odometry using nonlinear optimization,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.337128Z

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Observation 3fbbeeda-b818-4df9-a072-489f9eafe08c · outbound

This paper cites Vins-mono: A robust and versatile monoc- ular visual-inertial state estimator,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Vins-mono: A robust and versatile monoc- ular visual-inertial state estimator,

Reference 18

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Observation 707728b8-fc91-4d2b-9fb5-07658ea3019c · outbound

This paper cites Deepvo: Towards end-to-end visual odometry with deep recurrent convolutional neural networks,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Deepvo: Towards end-to-end visual odometry with deep recurrent convolutional neural networks,

Reference 19

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Observation 536b5958-3c80-441d-b0eb-2426e9af5328 · outbound

This paper cites Hvionet: A deep learning based hybrid visual–inertial odometry approach for unmanned aerial system position estimation,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Hvionet: A deep learning based hybrid visual–inertial odometry approach for unmanned aerial system position estimation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.290229Z

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Observation ba9fa2e5-b236-4285-96a6-d1c7f78b8f1d · outbound

This paper cites Flownet: Learning optical flow with convolutional networks,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Flownet: Learning optical flow with convolutional networks,

Reference 21

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Observation 81575ce8-9d6f-496f-821a-ddaf28a42a90 · outbound

This paper cites Deepvio: Self-supervised deep learning of monocular visual inertial odometry using 3d geometric constraints,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Deepvio: Self-supervised deep learning of monocular visual inertial odometry using 3d geometric constraints,

Reference 22

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Observation 22a900ed-ccfa-4073-874f-e0bbaa37c644 · outbound

This paper cites Vision-Based Autonomous Navigation for Unmanned Surface Vessel in Extreme Marine Conditions.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Vision-Based Autonomous Navigation for Unmanned Surface Vessel in Extreme Marine Conditions

Reference 23

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Observation e40b0c1c-072f-4a30-bbdd-1ec96fec35a9 · outbound

This paper cites Aqualoc: An underwater dataset for visual–inertial–pressure localization,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Aqualoc: An underwater dataset for visual–inertial–pressure localization,

Reference 24

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This paper cites Adam: A Method for Stochastic Optimization.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Adam: A Method for Stochastic Optimization

Reference 25

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Observation 7e6fd41c-fc47-4993-8e71-1fb79d51e1fc · outbound

This paper cites A survey on visual navigation and positioning for autonomous uuvs,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain A survey on visual navigation and positioning for autonomous uuvs,

Reference 26

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Observation 5a997325-c9ea-4612-a936-11ba0a281a93 · outbound

This paper cites Densely connected convolutional networks,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Densely connected convolutional networks,

Reference 27

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Observation a34b5cb3-a2c0-4c17-93b9-47172b72a0b3 · outbound

This paper cites Deep residual learning for image recognition,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Deep residual learning for image recognition,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.195569Z

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Observation a1f1c9de-9f14-4f21-b528-408445352c7c · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 29

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Observation 228ef059-7067-400d-85ba-95f3d7d6e40a · outbound

This paper cites Mo- bilenetv2: Inverted residuals and linear bottlenecks,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Mo- bilenetv2: Inverted residuals and linear bottlenecks,

Reference 30

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Observation 7473ce8b-b87e-4208-a4f0-6b4070d947bb · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 31

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Observation 2908fcbd-7f24-4bff-8013-320539519a90 · outbound

This paper cites Fda: Fourier domain adaptation for semantic segmentation,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Fda: Fourier domain adaptation for semantic segmentation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.160879Z

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Observation f8e3c231-8122-42dc-a15b-bc536f34212c · outbound

This paper cites Vision transformers for single image dehazing,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Vision transformers for single image dehazing,

Reference 33

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This paper cites Ffa-net: Feature fusion attention network for single image dehazing,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Ffa-net: Feature fusion attention network for single image dehazing,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:42:49.130972Z

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Observation 0a2c868d-156c-46fd-9905-7e1018e98828 · outbound

This paper cites Orb-slam3: An accurate open-source library for visual, visual–inertial, and multimap slam,.

Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Orb-slam3: An accurate open-source library for visual, visual–inertial, and multimap slam,

Reference 35

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