Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T10:24:42.839305Z
Paper Citation Record · LEDGER
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring
As of 20 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2504.18203.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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
Reference resolution
51 of 51 outbound references displayed
- verified exact1
- verified fuzzy35
- unresolved14
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation c55ade13-3088-4e70-ba2f-c78dd87af708 · outbound
This paper cites Trains: The backbone of mobility,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Trains: The backbone of mobility,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.587459Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 5fb61c98-e762-464b-99ef-60ad38fd35d4 · outbound
This paper cites What is digitale schiene deutschland?.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring What is digitale schiene deutschland?
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.572992Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 4130dbef-acc9-45c3-8ac8-2f90d08aeb76 · outbound
This paper cites About shift2rail,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring About shift2rail,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.559168Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 6d0266f4-aa9a-452a-832d-5193490c4fff · outbound
This paper cites safe.train: Rethinking mobility.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring safe.train: Rethinking mobility
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.545360Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 02d3a959-1eca-460a-9e91-f078af462bf6 · outbound
This paper cites [Online].
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring [Online]
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.531341Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a60d486f-573b-41c9-a2c5-dec38aa67699 · outbound
This paper cites A Review of Vision-Based On-Board Obstacle Detection and Distance Estimation in Railways,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring A Review of Vision-Based On-Board Obstacle Detection and Distance Estimation in Railways,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.517710Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a41e666e-1c74-4272-b1ba-29edd11aa8f9 · outbound
This paper cites High-Precision Low-Cost Gimballing Platform for Long-Range Railway Obstacle Detection,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring High-Precision Low-Cost Gimballing Platform for Long-Range Railway Obstacle Detection,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.503427Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 71b0af15-955b-4d13-9c8f-f0ba7dd59fd5 · outbound
This paper cites Improving distant 3d object detection using 2d box supervision,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Improving distant 3d object detection using 2d box supervision,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.488520Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a73e9cdb-7756-4233-884a-a03671ad817a · outbound
This paper cites Lidar on its way out? camera’s market size from 76% to 79% by 2033,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Lidar on its way out? camera’s market size from 76% to 79% by 2033,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.473043Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 95e4b3ad-9d83-4bf1-bf90-f4b4326f46d6 · outbound
This paper cites Virtual Sparse Convolution for Multimodal 3D Object Detection,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Virtual Sparse Convolution for Multimodal 3D Object Detection,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.458752Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 860307c6-d13f-4761-a0fc-0afa320694e9 · outbound
This paper cites LoGoNet: Towards Accurate 3D Object Detection With Local-to-Global Cross-Modal Fusion,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring LoGoNet: Towards Accurate 3D Object Detection With Local-to-Global Cross-Modal Fusion,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.444825Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 06b292af-3996-4b9a-a5a4-4b57199a9c2b · outbound
This paper cites V oxel Field Fusion for 3D Object Detection,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring V oxel Field Fusion for 3D Object Detection,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.429887Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f26dca34-e5bc-4c90-b8d0-d4e6b1f1ad2c · outbound
This paper cites Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detection,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detection,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.415945Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cf3ac740-8fc9-448e-8698-2bb90daade1d · outbound
This paper cites Chapter 13 - 3D object detection and tracking,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Chapter 13 - 3D object detection and tracking,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.401767Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 4c9f842d-de09-4aec-bf58-4166ae440f21 · outbound
This paper cites MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.387417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 574754ad-e48f-4c26-8ce9-bcbe80c7a830 · outbound
This paper cites Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.371901Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e86080fc-d58e-4824-a84d-e8df876c5d9a · outbound
This paper cites BEVDepth: Acquisition of Reliable Depth for Multi-View 3D Object Detection,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring BEVDepth: Acquisition of Reliable Depth for Multi-View 3D Object Detection,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.356019Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f62f58ba-f738-4b78-a223-79a9da043abd · outbound
This paper cites Towards Unified 3D Object Detection via Algorithm and Data Unification.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Towards Unified 3D Object Detection via Algorithm and Data Unification
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.697256Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ec5e6ab5-0845-47cd-b1c0-ee12abe678b2 · outbound
This paper cites Collision avoidance route planning for autonomous medical devices using multiple depth cameras,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Collision avoidance route planning for autonomous medical devices using multiple depth cameras,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.342005Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c4bf43c7-d678-4d9c-9eeb-9b22a75196e4 · outbound
This paper cites Frustum PointNets for 3D Object Detection From RGB-D Data,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Frustum PointNets for 3D Object Detection From RGB-D Data,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.327465Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 26e0bbe5-2ae8-4742-a4f7-6a4e35320abf · outbound
This paper cites Faraway-Frustum: Dealing with Lidar Sparsity for 3D Object Detec- tion using Fusion,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Faraway-Frustum: Dealing with Lidar Sparsity for 3D Object Detec- tion using Fusion,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.313400Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 7d27efa9-f9fe-4655-a109-bee64a3a16fd · outbound
This paper cites Pv-rcnn: Point-voxel feature set abstraction for 3d object detection,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Pv-rcnn: Point-voxel feature set abstraction for 3d object detection,
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.299307Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e5484776-e555-45e9-b4df-acd528597040 · outbound
This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.725119Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0c27e3e2-c9ec-4764-88c7-7fec54d75998 · outbound
This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Are we ready for autonomous driving? the kitti vision benchmark suite,
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.729989Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 37243d77-423e-4859-8f57-2e0be1fd8aa8 · outbound
This paper cites You only look once: Unified, real-time object detection,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring You only look once: Unified, real-time object detection,
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.734387Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9ba76fd9-17bc-4b96-834a-3d94e1d42638 · outbound
This paper cites YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.738379Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 17f5f13c-4b14-4b4c-9370-6a4197d28ae5 · outbound
This paper cites YOLOv1 to YOLOv10: The fastest and most accurate real-time object detection systems.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring YOLOv1 to YOLOv10: The fastest and most accurate real-time object detection systems
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.743176Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5f80b35f-ce92-4b27-8a2f-194eca937605 · outbound
This paper cites Machine learning techniques for autonomous multi- sensor long-range environmental perception system,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Machine learning techniques for autonomous multi- sensor long-range environmental perception system,
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.266297Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 601ac6ea-f4f3-456a-920d-6619228cfdee · outbound
This paper cites Dist-yolo: Fast object detection with distance estimation,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Dist-yolo: Fast object detection with distance estimation,
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.252060Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a62b0c89-0bf5-44c3-b723-95c9e0996073 · outbound
This paper cites Masoumian, D.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Masoumian, D
Reference 30
- Resolution
- verified exact
- doi, observed 2026-08-16T10:24:42.875826Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e8103d8e-965a-4521-89dd-7116e34135d8 · outbound
This paper cites Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.765172Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1f44a9c-d5ba-49ca-bac9-f589046b9ec2 · outbound
This paper cites High Quality Monocular Depth Estimation via Transfer Learning.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring High Quality Monocular Depth Estimation via Transfer Learning
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.769787Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dedec693-4702-48c4-99aa-d1772e7afd66 · outbound
This paper cites Densely Connected Convolutional Networks.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Densely Connected Convolutional Networks
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.774245Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f463552e-a28f-4e49-804c-8c9fb0f10d8f · outbound
This paper cites Colorization using optimiza- tion,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Colorization using optimiza- tion,
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.223445Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1bbba774-5bf3-45f4-a8a0-3d5d6787919e · outbound
This paper cites Repurposing diffusion-based image generators for monocular depth estimation,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Repurposing diffusion-based image generators for monocular depth estimation,
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.783367Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 061d8a15-66ff-42ca-8df0-caa00fc77eb3 · outbound
This paper cites nuscenes: A multimodal dataset for autonomous driving,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring nuscenes: A multimodal dataset for autonomous driving,
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.787816Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 366bea1a-9f63-424d-8f84-c07bfd597e6b · outbound
This paper cites Waymo Open Dataset: Panoramic Video Panoptic Segmentation.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Waymo Open Dataset: Panoramic Video Panoptic Segmentation
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.792104Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 88ea37a4-08d8-4cbc-be29-9aea2e6e8e4d · outbound
This paper cites RailSem19: A Dataset for Semantic Rail Scene Understanding,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring RailSem19: A Dataset for Semantic Rail Scene Understanding,
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.190774Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 665946b4-5a8e-4fb6-a29b-2eeac6d3e130 · outbound
This paper cites Railnet: A segmentation network for railroad detection,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Railnet: A segmentation network for railroad detection,
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.176772Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 0e0bab53-0860-46f4-bcdf-007efcb827dc · outbound
This paper cites FRSign: A Large-Scale Traffic Light Dataset for Autonomous Trains.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring FRSign: A Large-Scale Traffic Light Dataset for Autonomous Trains
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.804986Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f04fa726-3c1d-4eb5-99df-cedfb0757b50 · outbound
This paper cites A lightweight framework for obstacle detection in the railway image based on fast region proposal and improved yolo-tiny network,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring A lightweight framework for obstacle detection in the railway image based on fast region proposal and improved yolo-tiny network,
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.162600Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d5716373-b2c3-4c07-b4aa-181c7a659780 · outbound
This paper cites Railset: A unique dataset for railway anomaly detection,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Railset: A unique dataset for railway anomaly detection,
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.148668Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 41bb45e2-61eb-4a7d-9467-664a72a1d6c7 · outbound
This paper cites A lightweight lidar-camera sensing method of obstacles detection and classification for autonomous rail rapid transit,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring A lightweight lidar-camera sensing method of obstacles detection and classification for autonomous rail rapid transit,
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.134915Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 04f10fbf-007a-45fb-9437-6681fecc3241 · outbound
This paper cites Road and Railway Smart Mobility: A High- Definition Ground Truth Hybrid Dataset,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Road and Railway Smart Mobility: A High- Definition Ground Truth Hybrid Dataset,
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.120054Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b08024ce-38aa-4380-bff7-1204036740bf · outbound
This paper cites 3D Object Detection on Synthetic Point Clouds for Railway Applications,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring 3D Object Detection on Synthetic Point Clouds for Railway Applications,
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.105709Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f09e2df0-33c7-49d7-8263-5205a8497517 · outbound
This paper cites Open sensor data for rail 2023,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Open sensor data for rail 2023,
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.091733Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 993b6e41-2b3f-486c-a9c5-42559d4d34f7 · outbound
This paper cites Asam openlabel,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Asam openlabel,
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.076714Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a0bcad39-1cb9-4ebe-a769-3e298dedff25 · outbound
This paper cites Multi-view 3d object detection network for autonomous driving,.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Multi-view 3d object detection network for autonomous driving,
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.061891Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 02c4274d-7d2e-4d80-ae91-1753840952f1 · outbound
This paper cites PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:24:42.720212Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e2ee55de-5a40-4142-adec-28b7305f1e05 · outbound
This paper cites Available: https://www.mdpi.com/2076-3417/12/3/ 1354.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Available: https://www.mdpi.com/2076-3417/12/3/ 1354
Reference 2022
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T10:24:43.238052Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 53ce90da-4917-4645-b844-31b594282278 · outbound
This paper cites Improving Distant 3D Object Detection Using 2D Box Supervision.
LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring Improving Distant 3D Object Detection Using 2D Box Supervision
Reference 2024
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-16T10:24:43.047098Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Pith citing papers
No inbound Pith citation observations are available.