DINO-VO: Learning Where to Focus for Enhanced State Estimation | Paper Citation Record

Observation 5bb542b3-360f-4bbd-a4db-fa5d74d5c236 · outbound

This paper cites Codeslam—learning a compact, optimisable representation for dense visual slam.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Codeslam—learning a compact, optimisable representation for dense visual slam

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.865891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 049d3179-df1f-46e1-bb46-696737312b3a · outbound

This paper cites Lift-slam: A deep-learning feature-based monocular visual slam method.Neurocomputing, 455:97–110.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Lift-slam: A deep-learning feature-based monocular visual slam method.Neurocomputing, 455:97–110

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.876088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 71015ed3-f52b-4524-a58d-2a91050aa823 · outbound

This paper cites The euroc micro aerial vehicle datasets.The International Journal of Robotics Research, 35 (10):1157–1163.

DINO-VO: Learning Where to Focus for Enhanced State Estimation The euroc micro aerial vehicle datasets.The International Journal of Robotics Research, 35 (10):1157–1163

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.869882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ce385c7c-bf11-4d04-8119-1e5d44f97270 · outbound

This paper cites Orb-slam3: An accu- rate open-source library for visual, visual–inertial, and mul- timap slam.IEEE Transactions on Robotics, 37(6):1874– 1890.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Orb-slam3: An accu- rate open-source library for visual, visual–inertial, and mul- timap slam.IEEE Transactions on Robotics, 37(6):1874– 1890

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.872822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation aa85e7c3-67a5-4a7c-ba30-d3f605ac6891 · outbound

This paper cites Vpl- slam: A vertical line supported point line monocular slam system.IEEE Transactions on Intelligent Transportation Systems.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Vpl- slam: A vertical line supported point line monocular slam system.IEEE Transactions on Intelligent Transportation Systems

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.938699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2db2eb34-df06-40e7-9720-6d040d8275d2 · outbound

This paper cites Multi- lio: A lightweight multiple lidar-inertial odometry system.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Multi- lio: A lightweight multiple lidar-inertial odometry system

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.908724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation dc1528a1-a7a4-4826-81e6-c8b508eae14c · outbound

This paper cites Deepfactors: Real-time probabilistic dense monocular slam.IEEE Robotics and Automation Letters, 5 (2):721–728.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Deepfactors: Real-time probabilistic dense monocular slam.IEEE Robotics and Automation Letters, 5 (2):721–728

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.892534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation cc80c285-a08e-430e-97da-ca7b07b518b7 · outbound

This paper cites Monoslam: Real-time single camera slam.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Monoslam: Real-time single camera slam

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.992813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 59451c40-f510-4c26-9f3a-e7ea8b284a6d · outbound

This paper cites Compact 3D Gaussian Splatting For Dense Visual SLAM.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Compact 3D Gaussian Splatting For Dense Visual SLAM

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-14T01:54:32.068473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fea9c1a7-2c1b-4475-b948-b9e1be7ff167 · outbound

This paper cites Plgslam: Progressive neural scene represenation with local to global bundle adjustment.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Plgslam: Progressive neural scene represenation with local to global bundle adjustment

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.885690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5472f68e-b5be-45cc-862f-2f8792081ba3 · outbound

This paper cites GaussianDWM: 3D Gaussian Driving World Model for Unified Scene Understanding and Multi-Modal Generation.

DINO-VO: Learning Where to Focus for Enhanced State Estimation GaussianDWM: 3D Gaussian Driving World Model for Unified Scene Understanding and Multi-Modal Generation

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-20T00:03:01.148630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f51d7c7f-5f9b-4961-94f5-dfc8325af484 · outbound

This paper cites What is the best 3d scene representation for robotics? from geometric to foundation models.

DINO-VO: Learning Where to Focus for Enhanced State Estimation What is the best 3d scene representation for robotics? from geometric to foundation models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:08:00.938623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation de7fd923-30bb-48dd-8858-6e9866f19585 · outbound

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

DINO-VO: Learning Where to Focus for Enhanced State Estimation Superpoint: Self-supervised interest point detection and description

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.905600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4ee40f19-488f-406d-83d5-ce58a032d171 · outbound

This paper cites Lsd- slam: Large-scale direct monocular slam.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Lsd- slam: Large-scale direct monocular slam

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.956548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6279fc7d-5435-44b4-9524-6a5ce84e3eb3 · outbound

This paper cites Direct sparse odometry.IEEE transactions on pattern analysis and machine intelligence, 40(3):611–625.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Direct sparse odometry.IEEE transactions on pattern analysis and machine intelligence, 40(3):611–625

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.984325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6affdfbd-6762-490c-bffd-65193ee93092 · outbound

This paper cites Svo: Fast semi-direct monocular visual odometry.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Svo: Fast semi-direct monocular visual odometry

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.902299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0182821a-495d-4dd8-bc9f-094230e78591 · outbound

This paper cites Bags of binary words for fast place recognition in image sequences.IEEE Transactions on robotics, 28(5):1188–1197.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Bags of binary words for fast place recognition in image sequences.IEEE Transactions on robotics, 28(5):1188–1197

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.895441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8afdde99-0ca9-46c2-9f32-734201e5548c · outbound

This paper cites Deep incomplete multi-view learning via cyclic permutation of vaes.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Deep incomplete multi-view learning via cyclic permutation of vaes

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.961856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5dcd509c-e82c-43ad-bef3-13653d1d6792 · outbound

This paper cites Ldso: Direct sparse odometry with loop closure.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Ldso: Direct sparse odometry with loop closure

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.928838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5234b1a8-ed61-4089-970f-0870ce17e973 · outbound

This paper cites Good: Training-free guided diffusion sampling for out-of-distribution detection.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Good: Training-free guided diffusion sampling for out-of-distribution detection

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.978909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5242c2b1-91d2-4c0c-8ce3-6b94c18a4d5a · outbound

This paper cites Vision meets robotics: The kitti dataset.The Inter- national Journal of Robotics Research, 32(11):1231–1237.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Vision meets robotics: The kitti dataset.The Inter- national Journal of Robotics Research, 32(11):1231–1237

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.987242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 38464ba1-0b7f-4de5-80b1-83621ed82438 · outbound

This paper cites evo: Python package for the evalua- tion of odometry and slam.https://github.com/ MichaelGrupp/evo.

DINO-VO: Learning Where to Focus for Enhanced State Estimation evo: Python package for the evalua- tion of odometry and slam.https://github.com/ MichaelGrupp/evo

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.898752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 668a40b0-e652-4b0b-b8e7-ccc9008159a0 · outbound

This paper cites Dark-isp: Enhancing raw image processing for low-light object detection.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Dark-isp: Enhancing raw image processing for low-light object detection

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.995424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0d8ae6a8-e11b-4c83-a387-a24c61c7f479 · outbound

This paper cites Toward camera open-set 3d object detection for autonomous driving scenar- ios.IEEE Transactions on Intelligent Transportation Sys- tems, 26(12):23190–23201.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Toward camera open-set 3d object detection for autonomous driving scenar- ios.IEEE Transactions on Intelligent Transportation Sys- tems, 26(12):23190–23201

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.882532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 25b71fec-ac37-4cc2-a42d-87209090b4c7 · outbound

This paper cites DynamicVGGT: Learning dynamic point maps for 4D scene reconstruction in autonomous driving.

DINO-VO: Learning Where to Focus for Enhanced State Estimation DynamicVGGT: Learning dynamic point maps for 4D scene reconstruction in autonomous driving

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:08:00.941371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ddaec180-d10e-4b09-9b48-5d641b49e5be · outbound

This paper cites MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving.

DINO-VO: Learning Where to Focus for Enhanced State Estimation MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-13T17:08:00.944304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d892961f-d3d7-4236-8e88-82eb3bb250a0 · outbound

This paper cites Photo-slam: Real-time simultaneous localization and photo- realistic mapping for monocular stereo and rgb-d cameras.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Photo-slam: Real-time simultaneous localization and photo- realistic mapping for monocular stereo and rgb-d cameras

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.916223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 09222a9c-5326-4fdb-aafa-aff61722dd02 · outbound

This paper cites Eslam: Efficient dense slam system based on hy- brid representation of signed distance fields.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Eslam: Efficient dense slam system based on hy- brid representation of signed distance fields

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.964933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8d700724-11d7-4b19-92a7-19ca4cf41894 · outbound

This paper cites Splatam: Splat track & map 3d gaus- sians for dense rgb-d slam.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Splatam: Splat track & map 3d gaus- sians for dense rgb-d slam

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.919097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 176804ef-a8ca-406b-90af-cf7b37729f95 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.ACM Trans.

DINO-VO: Learning Where to Focus for Enhanced State Estimation 3d gaussian splatting for real-time radiance field rendering.ACM Trans

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.935670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2a3b0198-f01e-4a9d-b744-6144dd43d6cb · outbound

This paper cites Parallel tracking and map- ping for small ar workspaces.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Parallel tracking and map- ping for small ar workspaces

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.971022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5e514e0a-06f8-4df1-9cea-2b324b783817 · outbound

This paper cites Artdeco: Toward high-fidelity on-the-fly reconstruction with hierarchical gaussian structure and feed- forward guidance.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Artdeco: Toward high-fidelity on-the-fly reconstruction with hierarchical gaussian structure and feed- forward guidance

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.998078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 093dcfdc-d566-4957-adc6-bc51a4dcb87c · outbound

This paper cites Papl-slam: Principal axis-anchored monocu- lar point-line slam.IEEE Robotics and Automation Letters.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Papl-slam: Principal axis-anchored monocu- lar point-line slam.IEEE Robotics and Automation Letters

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.968219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 51805d5a-254e-4954-804c-dd96c8627fe2 · outbound

This paper cites Constrained gaussian splatting via implicit tsdf hash grid for dense rgb-d slam.IEEE Transactions on Artificial Intelli- gence.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Constrained gaussian splatting via implicit tsdf hash grid for dense rgb-d slam.IEEE Transactions on Artificial Intelli- gence

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.879287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 915c987e-152d-44f3-857d-86d3bf684710 · outbound

This paper cites Ec-slam: Effectively constrained neural rgb-d slam with tsdf hash en- coding and joint optimization.Pattern Recognition, 170: 112034.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Ec-slam: Effectively constrained neural rgb-d slam with tsdf hash en- coding and joint optimization.Pattern Recognition, 170: 112034

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.925714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 90dd4c6f-537b-4773-811d-b8d53fd3a158 · outbound

This paper cites Undeepvo: Monocular visual odometry through unsuper- vised deep learning.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Undeepvo: Monocular visual odometry through unsuper- vised deep learning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.932400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8f28b2f6-9e1c-4030-b6d1-4173b5163290 · outbound

This paper cites Deepslam: A ro- bust monocular slam system with unsupervised deep learn- ing.IEEE Transactions on Industrial Electronics, 68(4): 3577–3587.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Deepslam: A ro- bust monocular slam system with unsupervised deep learn- ing.IEEE Transactions on Industrial Electronics, 68(4): 3577–3587

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.889054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2e0d7bd3-204a-450f-bb54-c886341b9fa5 · outbound

This paper cites Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-05-13T17:08:00.947378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b50e6696-4039-4e56-aa4c-905534f27bec · outbound

This paper cites Lightglue: Local feature matching at light speed.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Lightglue: Local feature matching at light speed

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.953711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation bd0d0c24-a8ac-44c7-acc0-064deec8a68b · outbound

This paper cites Deep patch visual slam.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Deep patch visual slam

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.981485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c68d5d6f-00b8-4597-862a-4aae8c185692 · outbound

This paper cites Loopy-slam: Dense neural slam with loop closures.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Loopy-slam: Dense neural slam with loop closures

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.976125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 29f1ba24-1c86-4ce9-8209-8e21e967bea8 · outbound

This paper cites MMG-Vid: Maximizing Marginal Gains at Segment-level and Token-level for Efficient Video LLMs.

DINO-VO: Learning Where to Focus for Enhanced State Estimation MMG-Vid: Maximizing Marginal Gains at Segment-level and Token-level for Efficient Video LLMs

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:08:00.956426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d689379c-06d1-4894-b74b-995de8fcf44f · outbound

This paper cites Gift: Global irreplaceability frame tar- geting for efficient video understanding.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Gift: Global irreplaceability frame tar- geting for efficient video understanding

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:08:00.932689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 16031932-0580-4112-b375-db3765992731 · outbound

This paper cites Gaussian splatting slam.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Gaussian splatting slam

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.003158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 545d594c-0ff3-44e1-908e-595e1059a534 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.912811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3c0e5584-48eb-4974-97b5-6cc6059a9a0c · outbound

This paper cites Orb-slam2: An open- source slam system for monocular, stereo, and rgb-d cam- eras.IEEE transactions on robotics, 33(5):1255–1262.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Orb-slam2: An open- source slam system for monocular, stereo, and rgb-d cam- eras.IEEE transactions on robotics, 33(5):1255–1262

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.950861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0f705efc-9f63-4365-9ee8-d180543b2135 · outbound

This paper cites Orb-slam: a versatile and accurate monocular slam system.IEEE Transactions on Robotics, 31(5):1147–1163.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Orb-slam: a versatile and accurate monocular slam system.IEEE Transactions on Robotics, 31(5):1147–1163

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.922274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9874e5d5-c2df-47a2-8f6a-78d12100156a · outbound

This paper cites Dinov2: Learning robust visual features without supervision.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Dinov2: Learning robust visual features without supervision

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.944099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 493fd4c5-7690-4857-84a8-8ca398fe7bf3 · outbound

This paper cites Rtg-slam: Real-time 3d re- construction at scale using gaussian splatting.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Rtg-slam: Real-time 3d re- construction at scale using gaussian splatting

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.947451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d4a4a1f7-c821-4943-843d-0f6806e4df7f · outbound

This paper cites Vi- sion transformers for dense prediction.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Vi- sion transformers for dense prediction

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.941486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2102df67-99b3-4154-bc96-8f3db2d1daa5 · outbound

This paper cites Machine learning for high-speed corner detection.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Machine learning for high-speed corner detection

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.973545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 65359457-d2eb-4103-9a0b-23e974b546d0 · outbound

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

DINO-VO: Learning Where to Focus for Enhanced State Estimation Orb: An efficient alternative to sift or surf

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.990287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2f05d425-f82b-462d-9f7b-310420d27025 · outbound

This paper cites Good features to track.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Good features to track

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:08.959124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 676706f0-d027-434c-8e80-b8b182fb7154 · outbound

This paper cites imap: Implicit mapping and positioning in real-time.

DINO-VO: Learning Where to Focus for Enhanced State Estimation imap: Implicit mapping and positioning in real-time

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.000630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9e5a29fa-08cf-40b1-b282-1f8e647b1c5a · outbound

This paper cites Decoupling scene perception and ego status: A multi-context fusion approach for enhanced generaliza- tion in end-to-end autonomous driving.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Decoupling scene perception and ego status: A multi-context fusion approach for enhanced generaliza- tion in end-to-end autonomous driving

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.023480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e0158c81-752e-44c5-8d04-055b2f726966 · outbound

This paper cites CausalVAD: De-confounding End-to-End Autonomous Driving via Causal Intervention.

DINO-VO: Learning Where to Focus for Enhanced State Estimation CausalVAD: De-confounding End-to-End Autonomous Driving via Causal Intervention

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-05-13T17:08:00.935656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 630b30bb-2c06-455e-b40a-e35035b40249 · outbound

This paper cites Cnn-slam: Real-time dense monocular slam with learned depth prediction.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Cnn-slam: Real-time dense monocular slam with learned depth prediction

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.010819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9fb6fbef-15da-43b8-a21e-a9659d7712d7 · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Raft: Recurrent all-pairs field transforms for optical flow

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.030405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 41822919-ec29-45ca-90cc-e38612e2639c · outbound

This paper cites Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras.Advances in Neu- ral Information Processing Systems, 34:16558–16569.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras.Advances in Neu- ral Information Processing Systems, 34:16558–16569

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.025907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 21195aad-5a7b-4e40-9c0f-277b8bacda90 · outbound

This paper cites Deep patch vi- sual odometry.Advances in Neural Information Processing Systems, 36.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Deep patch vi- sual odometry.Advances in Neural Information Processing Systems, 36

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.013470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 604c81cf-ea4e-4555-8e8d-0d64585deaf4 · outbound

This paper cites Co- slam: Joint coordinate and sparse parametric encodings for neural real-time slam.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Co- slam: Joint coordinate and sparse parametric encodings for neural real-time slam

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.008328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3f7cfa11-4a5e-4c94-9189-1be7f59614f0 · outbound

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

DINO-VO: Learning Where to Focus for Enhanced State Estimation Deepvo: Towards end-to-end visual odometry with deep recurrent convolutional neural networks

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.016341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 99f7a5b7-e272-4a58-8111-1db9ed98c586 · outbound

This paper cites Tartanair: A dataset to push the limits of visual slam.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Tartanair: A dataset to push the limits of visual slam

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.021124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation df6e4265-8f53-446c-a019-a74dc1711f8b · outbound

This paper cites Tartanvo: A generalizable learning-based vo.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Tartanvo: A generalizable learning-based vo

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.028106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f80be053-e072-4e1b-b790-8d7b9e48d617 · outbound

This paper cites AirSLAM: An Efficient and Illumination-Robust Point-Line Visual SLAM System.

DINO-VO: Learning Where to Focus for Enhanced State Estimation AirSLAM: An Efficient and Illumination-Robust Point-Line Visual SLAM System

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:08:00.918619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4a590cf0-b5e4-4af7-9a43-5be87eca8825 · outbound

This paper cites Depth Anything V2.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Depth Anything V2

Reference 66

Resolution: verified exact; local_arxiv, observed 2026-05-13T17:08:00.926951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ed401678-2066-429f-9672-4296f399a841 · outbound

This paper cites Go-slam: Global optimization for consistent 3d in- stant reconstruction.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Go-slam: Global optimization for consistent 3d in- stant reconstruction

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.018751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 735cf995-5c67-4147-b990-2d8d30107ffb · outbound

This paper cites SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference.

DINO-VO: Learning Where to Focus for Enhanced State Estimation SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-15T14:58:32.742607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation aa8e5f64-67bc-4dcf-9364-f7cea4017188 · outbound

This paper cites Light-SLAM: A Robust Deep-Learning Visual SLAM System Based on LightGlue under Challenging Lighting Conditions.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Light-SLAM: A Robust Deep-Learning Visual SLAM System Based on LightGlue under Challenging Lighting Conditions

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:08:00.924476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation de5da952-7124-4333-bb07-db27a758406c · outbound

This paper cites Deeptam: Deep tracking and mapping.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Deeptam: Deep tracking and mapping

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.005470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b7245d58-5a2a-446b-82ae-aba36e6c4a19 · outbound

This paper cites Spatialreward: Verifiable spatial re- ward modeling for fine-grained spatial consistency in text-to- image generation.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Spatialreward: Verifiable spatial re- ward modeling for fine-grained spatial consistency in text-to- image generation

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:08:00.929943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e6e3dc28-e3b4-4afe-b5dd-49f3e8c121d4 · outbound

This paper cites Nice-slam: Neural implicit scalable encoding for slam.

DINO-VO: Learning Where to Focus for Enhanced State Estimation Nice-slam: Neural implicit scalable encoding for slam

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T05:28:09.032601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Reference resolution

Outbound references

Pith citing papers