Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:50:51.383065Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2506.04224.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:50:51.383065Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
68 of 68 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 733af7af-7203-4337-9012-9be93b501820 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset 1 year, 1000 km: The oxford robotcar dataset.IJRR, 2017
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8cd358dd-45c9-4b99-a51b-741013a0a059 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Visual topometric localization
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a43a0ae0-b6d8-4d0e-bcbd-d6eb0cd1e68c · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Posenet: A convolutional network for real-time 6-dof camera relocalization
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6118f844-eeb6-451e-9aa4-0c309fa98c6d · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Inloc: Indoor visual localization with dense matching and view synthesis
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 323d2fd0-28cf-42e7-bfc5-013acd66b16f · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Benchmarking 6dof outdoor visual localization in changing conditions
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 206120d9-de54-4430-a8bf-ae98986eccda · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Schönberger, Pablo Speciale, Lukas Gruber, Viktor Larsson, Ondrej Miksik, and Marc Pollefeys
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d1457d8b-5f78-4ee5-a1d6-8b0199a72122 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset The oxford spires dataset: Benchmarking large-scale lidar-visual localisation, reconstruction and radiance field methods.IJRR, 2025
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1393b250-cafe-4287-bc61-4c43505a5df8 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Matterport3D: Learning from RGB-D data in indoor environments
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a31d1b71-65b2-40e3-8683-649af07e8434 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5fa75240-4d4b-4b14-98bd-9ba0e76d0b09 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset The EuRoC micro aerial vehicle datasets.IJRR, 2016
Reference 10
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a734bb4c-489e-49e8-8ea9-efc704872809 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Large-scale data for multiple-view stereopsis.IJCV, 2016
Reference 11
Source-reported events for the cited work
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Observation a167092f-688b-452e-9c38-3702e8917d13 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset A benchmark for RGB-D visual odometry, 3D reconstruction and SLAM
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 32192856-f2fe-422c-b697-41ed7e294fd5 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset A comparison and evaluation of multi-view stereo reconstruction algorithms
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5b40033c-c0fe-4397-aaa6-56b140842d91 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset A multi-view stereo benchmark with high-resolution images and multi- camera videos
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e4ed3950-504f-455b-a955-d275a4c55cc1 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Tanks and Temples: Benchmarking large-scale scene reconstruction.ToG, 2017
Reference 15
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3513fc7a-08bf-4b48-9f6a-3af66ffe017c · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset ScanNet++: A high-fidelity dataset of 3D indoor scenes
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 29590f11-2fa0-469e-9341-4fad577e95e1 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset The Newer College dataset: Handheld lidar, inertial and vision with ground truth
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f3e27bc5-2c81-42ad-8b76-7b7983520909 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Hilti-Oxford dataset: A millimeter-accurate benchmark for simultaneous localization and mapping.RAL, 2022
Reference 18
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5f7baaee-ce49-4a11-b481-97c88a20b1fe · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset FusionPortableV2: A unified multi-sensor dataset for generalized SLAM across diverse platforms and scalable environments.IJRR, 2024
Reference 19
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 7c8ea7bc-a6ed-46b1-98aa-a209f8a739e1 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Sun, Hongwei Yu, Chun Liu, Long Chen, Wei Tao, and Hui Zhao
Reference 20
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d6a0bd7f-48e9-41c1-884f-7adf793cacd9 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset MCD: Diverse large-scale multi-campus dataset for robot perception
Reference 21
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f86f7bd8-5831-4a15-a30d-16e8ca44c3b5 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset ShapeNet: An Information-Rich 3D Model Repository
Reference 22
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6b769c52-1e5e-4fbf-be6e-58f9c80e712b · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Stereo magnification: learning view synthesis using multiplane images.ToG, 2018
Reference 23
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 27268b36-9a7a-41fe-9ff0-46f49ea2f314 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Srinivasan, Rodrigo Ortiz-Cayon, Nima Khademi Kalantari, Ravi Ramamoorthi, Ren Ng, and Abhishek Kar
Reference 24
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation feedc7a2-0c14-49be-929e-05a5b0f50f22 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Nerf: Representing scenes as neural radiance fields for view synthesis
Reference 25
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 155185d7-7874-47e9-89f1-7632af3b0221 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Barron, Ben Mildenhall, Dor Verbin, Pratul P
Reference 26
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b6a62816-32aa-4a57-92fc-a40709552e91 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Common objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction
Reference 27
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 84fd5c25-a4ef-477a-b2bb-d4124cc87c0e · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Objaverse-xl: A universe of 10m+ 3d objects
Reference 28
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e701061b-3c38-407d-989d-376666de0d85 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Image matching across wide baselines: From paper to practice.IJCV, 2021
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a6c50667-dd60-413e-827b-e49e5780b295 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Megascenes: Scene-level view synthesis at scale
Reference 30
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5da2b97a-e4f1-4726-b104-a971c47e1c61 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Dl3dv-10k: A large-scale scene dataset for deep learning-based 3d vision
Reference 31
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d70710f9-f6b8-4aad-9d91-8da1229f2e33 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Scene coordinate regression forests for camera relocalization in rgb-d images
Reference 32
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b7f5100f-651d-4090-a5b9-ffdb68a062c5 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Learning to navigate the energy landscape
Reference 33
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c5716485-40e7-4d75-b74a-47b2fdd3f2da · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Learning to detect scene landmarks for camera localization
Reference 34
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a472399a-0424-4c0c-b605-be3abd402656 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Large-scale localization datasets in crowded indoor spaces
Reference 35
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d5a17cdf-1490-4be1-9739-de47e2c203e3 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Vision meets robotics: The kitti dataset.IJRR, 2013
Reference 36
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation dc5c14e2-cd25-4dcc-bada-bb046296633c · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset The epic-kitchens dataset: Collection, challenges and baselines.TPAMI, 2020
Reference 37
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0172b1db-5bd5-455c-bdc9-56de954bbd3a · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset In the eye of beholder: Joint learning of gaze and actions in first person video
Reference 38
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation aff9ef8a-cfb8-46ab-a39d-3dc76a48f20c · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Introducing hot3d: An egocentric dataset for 3d hand and object tracking
Reference 39
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 21845a8a-1b93-448f-9fd1-5ae829a29665 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Ego4d: Around the world in 3,000 hours of egocentric video
Reference 40
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 259f6f08-efe0-4d4b-ac2c-913566405df4 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset EgoVid-5M: A Large-Scale Video-Action Dataset for Egocentric Video Generation
Reference 41
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d84937b2-58a9-487f-8896-1617f46cf184 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Aria digital twin: A new benchmark dataset for egocentric 3d machine perception
Reference 42
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6f97feba-7620-4e65-a04a-49947bf6a8f0 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Aria Everyday Activities Dataset
Reference 43
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 36276fe2-610f-402e-a672-a046de8b9e7a · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Ego-exo4d: Understanding skilled human activity from first-and third-person perspectives
Reference 44
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b928a696-738a-47f1-875c-293885971af2 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset 3d gaussian splatting for real-time radiance field rendering.ToG, 2023
Reference 45
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 38815c28-4a90-4fb7-b856-b13e6d262035 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Splatfacto-W: A Nerfstudio Implementation of Gaussian Splatting for Unconstrained Photo Collections
Reference 46
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ef81f915-8196-432e-967b-8764403af56b · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Gaussian in the wild: 3d gaussian splatting for unconstrained image collections
Reference 47
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f299b029-78f0-4528-98b2-7a29a5f5633e · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset From coarse to fine: Robust hierarchical localization at large scale
Reference 48
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d53ceba8-a344-444e-a635-27b3b6285772 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Superglue: Learning feature matching with graph neural networks
Reference 49
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8624fb57-bc87-4ab6-bc64-df0a0f5fc162 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Loftr: Detector-free local feature matching with transformers
Reference 50
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9ee5384d-024a-40e9-98d2-def231752c36 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Accelerated coordinate encoding: Learning to relocalize in minutes using rgb and poses
Reference 51
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d87ab11d-7cd9-46ee-b20f-f55dbe05102a · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Glace: Global local accelerated coordinate encoding
Reference 52
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 18b18af5-5135-4c1d-a971-b9be13014839 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset AprilTag: A robust and flexible visual fiducial system
Reference 53
Source-reported events for the cited work
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Observation aa1378f6-0b4a-4a64-b5d9-87231037860f · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset AprilTag 2: Efficient and robust fiducial detection
Reference 54
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6e25d9a2-252c-4359-ab09-805ae4b7b11d · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Extrinsic calibration of camera to lidar using a differentiable checkerboard model
Reference 55
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8369d7ed-92c0-47bb-8f68-5feb5f9d3749 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Besl and Neil D
Reference 56
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4325a955-b35f-4467-b0ec-84e534023ad0 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Netvlad: Cnn architecture for weakly supervised place recognition
Reference 57
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b9d628dd-4892-40e8-9f63-f10488ba18aa · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Object recognition from local scale-invariant features
Reference 58
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d184d857-75f9-4b21-9a96-1d159c2afee4 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Lightglue: Local feature matching at light speed
Reference 59
Source-reported events for the cited work
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Observation fe972e75-7bfd-4599-a2e2-899a7f5511d1 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Disk: Learning local features with policy gradient
Reference 60
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 066f2aac-8d13-47fd-b2b7-15bed5b5a1ed · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Roma: Robust dense feature matching
Reference 61
Source-reported events for the cited work
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Observation 3fbd6e9f-a624-4cc9-9c34-b9f8c379229e · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Grounding image matching in 3d with mast3r
Reference 62
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 010cd84e-9698-42dc-963d-aa3dd35ab4ab · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset R-score: Revisiting scene coordinate regression for robust large-scale visual localization
Reference 63
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6cdc7c4d-db2f-4087-bcfb-3315a0963f96 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Superpoint: Self-supervised interest point detection and description
Reference 64
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3287797c-6c5f-4de8-ab7c-ac0e82dddbe0 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Gordo, J
Reference 65
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c0a5f3f1-dae4-46b9-bb27-9dec19087b52 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Revaud, J
Reference 66
Source-reported events for the cited work
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Observation 46bd7e07-afe3-4fa0-8b26-1d97be7ff2d4 · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset Self-supervising fine-grained region similarities for large-scale image localization
Reference 67
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 644abfaf-cf5d-48db-aa3a-3ad31ee7cacb · outbound
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset MegaLoc: One Retrieval to Place Them All
Reference 68
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No inbound Pith citation observations are available.