Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:20:55.559949Z
Paper Citation Record · LEDGER
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy
As of 16 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 1 inbound Pith citation observation for arXiv:2506.14525.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T08:13:16.505751Z
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
27 of 27 outbound references displayed
- verified exact1
- verified fuzzy25
- unresolved1
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 1b171a70-3b06-43ec-aa70-849e0378be08 · outbound
This paper cites Target localization for autonomous landing site detection: A review and preliminary result with static image photogrammetry[J].
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Target localization for autonomous landing site detection: A review and preliminary result with static image photogrammetry[J]
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:21:00.779348Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e44ef938-92ec-46ff-b3f2-3abd5698ca98 · outbound
This paper cites Vision-based autonomous landing for the uav: A review[J].
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Vision-based autonomous landing for the uav: A review[J]
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:21:00.596531Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation cb85e0fe-032e-4047-9731-42164156eb0c · outbound
This paper cites Towards vision- based safe landing for an autonomous helicopter[J].
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Towards vision- based safe landing for an autonomous helicopter[J]
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:21:00.350275Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6d8bc86d-5b5f-440a-a7e9-2caa15eb8561 · outbound
This paper cites Metric3d v2: A versatile monocular geometric foundation model for zero-shot metric depth and surface normal estimation[J].
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Metric3d v2: A versatile monocular geometric foundation model for zero-shot metric depth and surface normal estimation[J]
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:21:00.085212Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a380a2c6-d1bb-4445-9e86-9a54f7532ec7 · outbound
This paper cites Wilduav: Monocular uav dataset for depth estimation tasks[C]//2021 IEEE 17th International Confer- ence on Intelligent Computer Communication and Processing (ICCP).
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Wilduav: Monocular uav dataset for depth estimation tasks[C]//2021 IEEE 17th International Confer- ence on Intelligent Computer Communication and Processing (ICCP)
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:59.895157Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f57cdc30-aa4f-4912-b8c6-8ff8ed896f21 · outbound
This paper cites ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth.
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:20:53.783127Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b2e7f56e-0902-4568-a070-564552818b72 · outbound
This paper cites Drone Dataset[DB/OL].
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Drone Dataset[DB/OL]
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:59.797065Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation bb6e0f23-4936-4164-9216-caea6bde9ee3 · outbound
This paper cites UniDepth: Universal monocular metric depth estimation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy UniDepth: Universal monocular metric depth estimation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:59.655944Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5076dc51-fa59-492a-a98c-8c684055ea34 · outbound
This paper cites Towards zero-shot scale- aware monocular depth estimation[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision.
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Towards zero-shot scale- aware monocular depth estimation[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:59.522599Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d48b335f-bf63-4be4-b7c6-81c3f34125e9 · outbound
This paper cites Depth anything v2[J].
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Depth anything v2[J]
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:59.348660Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 52d34f82-c8c2-4e6f-8c0e-3adf693d3d66 · outbound
This paper cites Repurposing diffusion-based image generators for monocular depth estimation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Repurposing diffusion-based image generators for monocular depth estimation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:59.173831Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 114dddca-eb13-447f-be87-344d0e7359d9 · outbound
This paper cites Diffusiondepth: Diffusion denoising approach for monocular depth estimation[C]//European Conference on Com- puter Vision.
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Diffusiondepth: Diffusion denoising approach for monocular depth estimation[C]//European Conference on Com- puter Vision
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:58.987094Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 742f5a50-1875-41c9-af4e-24a7833bd520 · outbound
This paper cites Csrnet: Dilated convolutional neural networks for understanding the highly congested scenes[C]//Proceedings of the IEEE conference on computer vision and pattern recognition.
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Csrnet: Dilated convolutional neural networks for understanding the highly congested scenes[C]//Proceedings of the IEEE conference on computer vision and pattern recognition
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:58.814386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b67f8ee7-c7f3-4172-8442-362f058030d5 · outbound
This paper cites Geometric and physical con- straints for drone-based head plane crowd density estimation[C]//2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Geometric and physical con- straints for drone-based head plane crowd density estimation[C]//2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:58.636583Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2ae97386-9e08-4cf2-9360-cd0d9c1c0b2f · outbound
This paper cites Human crowd detection for drone flight safety using convolutional neural networks[C]//2017 25th European Signal Processing Conference (EUSIPCO).
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Human crowd detection for drone flight safety using convolutional neural networks[C]//2017 25th European Signal Processing Conference (EUSIPCO)
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:58.464624Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c87db607-0361-423c-8300-2ef8ad75908f · outbound
This paper cites Graph embedded convolutional neural networks in human crowd detection for drone flight safety[J].
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Graph embedded convolutional neural networks in human crowd detection for drone flight safety[J]
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:58.288971Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 577c3118-e351-4d70-8135-2bc10526e52a · outbound
This paper cites SafeUA V: Learning to es- timate depth and safe landing areas for UA Vs from synthetic data[C]//Proceedings of the European Conference on Computer Vision (ECCV) Workshops.
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy SafeUA V: Learning to es- timate depth and safe landing areas for UA Vs from synthetic data[C]//Proceedings of the European Conference on Computer Vision (ECCV) Workshops
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:58.045529Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 643a4200-da95-4a42-bffa-6b7c2faf71fd · outbound
This paper cites Robust autonomous landing of UA Vs in non-cooperative environments based on comprehensive terrain un- derstanding[J].
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Robust autonomous landing of UA Vs in non-cooperative environments based on comprehensive terrain un- derstanding[J]
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:57.821390Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fba9c8d8-4118-42f2-8590-5e634fb8508c · outbound
This paper cites Safe landing zones detection for uavs using deep regression[C]//2022 19th conference on robots and vision (CRV).
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Safe landing zones detection for uavs using deep regression[C]//2022 19th conference on robots and vision (CRV)
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:57.606223Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a4f2347a-c395-4f79-bb8e-cad38252ff8e · outbound
This paper cites YOLO-based terrain classification for uav safe landing zone detection[C]//2023 IEEE Region 10 Symposium (TENSYMP).
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy YOLO-based terrain classification for uav safe landing zone detection[C]//2023 IEEE Region 10 Symposium (TENSYMP)
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:57.349040Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4c137c09-9abd-4d0a-99a9-aee955832aab · outbound
This paper cites You only look once: Unified, real-time object detection[C]//Proceedings of the IEEE conference on computer vision and pattern recognition.
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy You only look once: Unified, real-time object detection[C]//Proceedings of the IEEE conference on computer vision and pattern recognition
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:57.164364Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 995c9ce0-4f3e-4807-bfde-4e3dd59efbb3 · outbound
This paper cites Risk Assessment for Autonomous Landing in Urban Environments using Semantic Segmentation.
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Risk Assessment for Autonomous Landing in Urban Environments using Semantic Segmentation
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T00:20:55.822489Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 714bd721-ac04-4dd9-8aea-100adc6eb778 · outbound
This paper cites SegFormer: Simple and efficient design for semantic segmentation with transformers[J].
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy SegFormer: Simple and efficient design for semantic segmentation with transformers[J]
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:56.931636Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 08c2b376-03a1-4a54-8f29-d97701720c7b · outbound
This paper cites (2024).ISAT with Segment Anything: An Interactive Semi-Automatic Annotation Tool.
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy (2024).ISAT with Segment Anything: An Interactive Semi-Automatic Annotation Tool
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:56.736452Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e9ffc635-756e-4409-9143-c14df4b868b2 · outbound
This paper cites DINOv2: Learning Robust Visual Features without Supervision[J].
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy DINOv2: Learning Robust Visual Features without Supervision[J]
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:56.477083Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 78508501-1f93-48f6-87d7-19eacdaca550 · outbound
This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale[C]//International Conference on Learning Representations.
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale[C]//International Conference on Learning Representations
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:56.281423Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation be24301e-ec1b-4c85-82ea-6d15f1c0dce7 · outbound
This paper cites Vision transformers for dense prediction[C]//Proceedings of the IEEE/CVF international conference on computer vision.
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy Vision transformers for dense prediction[C]//Proceedings of the IEEE/CVF international conference on computer vision
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:20:56.100146Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
Observation 42785175-cb53-4a22-9b33-de278d04fa54 · inbound
Human-Inspired Neuro-Symbolic World Modeling and Logic Reasoning for Interpretable Safe UAV Landing Site Assessment cites this paper.
Human-Inspired Neuro-Symbolic World Modeling and Logic Reasoning for Interpretable Safe UAV Landing Site Assessment VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T08:13:16.505751Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.