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Paper Citation Record · LEDGER

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory

As of 21 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 0 inbound Pith citation observations for arXiv:2603.03695.

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

pith.paper-citation-record.v1
2603.03695 v2

Coverage vector

measured 79 of 79 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T19:07:55.137495Z

measured 79 of 79 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

79 of 79 outbound references displayed

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Outbound references

Observation 7bdde78e-287a-4484-adde-6855d016ebac · outbound

This paper cites A survey on global lidar localization: Challenges, advances and open problems,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory A survey on global lidar localization: Challenges, advances and open problems,

Reference 1

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Observation b9e5ce55-8890-4f2b-b381-ec79b13d5cd4 · outbound

This paper cites Simultaneous localization and mapping for forest harvesters,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Simultaneous localization and mapping for forest harvesters,

Reference 2

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Observation 31e13d07-325b-4a4b-8ae5-27a6a8b203ca · outbound

This paper cites Wild visual navigation: Fast traversability learning via pre-trained models and online self-supervision,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Wild visual navigation: Fast traversability learning via pre-trained models and online self-supervision,

Reference 3

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Observation 18946e76-20c1-4725-b7c7-4848f63a8808 · outbound

This paper cites Building Forest Inventories with Autonomous Legged Robots -- System, Lessons, and Challenges Ahead.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Building Forest Inventories with Autonomous Legged Robots -- System, Lessons, and Challenges Ahead

Reference 4

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Observation 9f14ee5e-f9ff-4d76-b9ba-ea8dca201041 · outbound

This paper cites Terrestrial laser scanning in forest inventories,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Terrestrial laser scanning in forest inventories,

Reference 5

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Observation 296aca09-8808-4e3c-b8f8-9f3b53d158d3 · outbound

This paper cites Mapping forests using an unmanned ground vehicle with 3d lidar and graph-slam,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Mapping forests using an unmanned ground vehicle with 3d lidar and graph-slam,

Reference 6

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Observation d1373bcd-3215-4a3a-84d0-beb8ecefad7a · outbound

This paper cites Sloam: Semantic lidar odometry and mapping for forest inventory,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Sloam: Semantic lidar odometry and mapping for forest inventory,

Reference 7

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Observation 4cd1a512-ae6a-4ae2-a662-1893179c972f · outbound

This paper cites Large-scale autonomous flight with real-time semantic slam under dense forest canopy,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Large-scale autonomous flight with real-time semantic slam under dense forest canopy,

Reference 8

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Observation 211c5d86-172f-4114-9348-652c8c571a61 · outbound

This paper cites Accuracy and precision of gps receivers under forest canopies in a mountainous environment,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Accuracy and precision of gps receivers under forest canopies in a mountainous environment,

Reference 9

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Observation 5804af97-d0a8-4e75-b300-c2712fe529d8 · outbound

This paper cites The performance of rtk-gps for surveying under challenging environmental conditions,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory The performance of rtk-gps for surveying under challenging environmental conditions,

Reference 10

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Observation bc400ed8-d14e-4981-a672-262e1862e20b · outbound

This paper cites The use of terrestrial lidar technology in forest science: application fields, benefits and challenges,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory The use of terrestrial lidar technology in forest science: application fields, benefits and challenges,

Reference 11

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Observation b1fc74e8-cded-473e-acc1-7f6f50f49400 · outbound

This paper cites Application of real-time positioning systems to a forest stand for precision forest management.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Application of real-time positioning systems to a forest stand for precision forest management

Reference 12

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Observation 11bb65c4-618d-4b37-9c9c-f950b62596f0 · outbound

This paper cites The role of lidar in sustainable forest management,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory The role of lidar in sustainable forest management,

Reference 13

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Observation 9dd47c63-6889-401e-8048-7f42446292e8 · outbound

This paper cites Scan context: Egocentric spatial descriptor for place recognition within 3d point cloud map,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Scan context: Egocentric spatial descriptor for place recognition within 3d point cloud map,

Reference 14

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Observation 643802d8-cc51-406c-9dc0-1feafcfbc9b3 · outbound

This paper cites Scan context++: Structural place recog- nition robust to rotation and lateral variations in urban environments,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Scan context++: Structural place recog- nition robust to rotation and lateral variations in urban environments,

Reference 15

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Observation 963392de-540c-444b-94eb-e81bf2f6e53e · outbound

This paper cites Narrowing your fov with solid: Spatially organized and lightweight global descriptor for fov-constrained lidar place recognition,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Narrowing your fov with solid: Spatially organized and lightweight global descriptor for fov-constrained lidar place recognition,

Reference 16

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Observation ba62919a-4c53-43b3-8bf6-4ca15914dc24 · outbound

This paper cites Std: Stable triangle descriptor for 3d place recognition,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Std: Stable triangle descriptor for 3d place recognition,

Reference 17

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Observation ea1bd162-e74e-4853-ae8a-334c61bd8617 · outbound

This paper cites Btc: A binary and triangle combined descriptor for 3-d place recognition,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Btc: A binary and triangle combined descriptor for 3-d place recognition,

Reference 18

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Observation 4e883a0a-1cd2-4edf-bd09-d76c2e06542a · outbound

This paper cites Effectively detecting loop closures using point cloud density maps,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Effectively detecting loop closures using point cloud density maps,

Reference 19

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Observation 4b87e39e-0138-49ce-b40c-75b266c371c0 · outbound

This paper cites Teaser: Fast and certifiable point cloud registration,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Teaser: Fast and certifiable point cloud registration,

Reference 20

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Observation 5f346d7f-3398-4af6-86c5-bb8e05041570 · outbound

This paper cites A single correspondence is enough: Robust global registration to avoid degeneracy in urban environments,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory A single correspondence is enough: Robust global registration to avoid degeneracy in urban environments,

Reference 21

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Observation a3fd7769-0a87-4726-9d7b-5003f719b9f4 · outbound

This paper cites Kiss-matcher: Fast and robust point cloud registration revisited,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Kiss-matcher: Fast and robust point cloud registration revisited,

Reference 22

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Observation dd45f02f-9fd2-4b81-9604-206cfd950e6c · outbound

This paper cites Evaluation and deployment of lidar-based place recognition in dense forests,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Evaluation and deployment of lidar-based place recognition in dense forests,

Reference 23

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Observation 73be192f-18d8-40f4-92ef-9a8f6a0fc4d6 · outbound

This paper cites Ssc: Semantic scan context for large-scale place recognition,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Ssc: Semantic scan context for large-scale place recognition,

Reference 24

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Observation 0b883b0a-337d-43ef-b8f9-0ab4b00bafdf · outbound

This paper cites Segmatch: Segment based place recognition in 3d point clouds,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Segmatch: Segment based place recognition in 3d point clouds,

Reference 25

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Observation ca4a101f-d7c8-43e5-a1fb-d6dec36cc00e · outbound

This paper cites Wildscenes: A benchmark for 2d and 3d semantic segmentation in large-scale natural environments,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Wildscenes: A benchmark for 2d and 3d semantic segmentation in large-scale natural environments,

Reference 26

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Observation 816175e1-7d1c-4ead-8f61-a0ed9408d50b · outbound

This paper cites Learning to see the wood for the trees: Deep laser localization in urban and natural environments on a cpu,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Learning to see the wood for the trees: Deep laser localization in urban and natural environments on a cpu,

Reference 27

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Observation 8b15360c-38f0-4737-8b27-765436016b7b · outbound

This paper cites Seeing the wood for the trees: Reliable localization in urban and natural environments,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Seeing the wood for the trees: Reliable localization in urban and natural environments,

Reference 28

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Observation ebd072d4-ac39-4132-b682-73396bdb2da3 · outbound

This paper cites Treeloc: 6-dof lidar global localization in forests via inter- tree geometric matching,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Treeloc: 6-dof lidar global localization in forests via inter- tree geometric matching,

Reference 29

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Observation 62820a7e-415b-4d0a-884e-5c332c1e2e08 · outbound

This paper cites Forest biomass estimation from airborne lidar data using machine learning approaches,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Forest biomass estimation from airborne lidar data using machine learning approaches,

Reference 30

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Observation 06d8526a-6dc3-4693-85db-34b193472ddb · outbound

This paper cites A new method for segmenting individual trees from the lidar point cloud,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory A new method for segmenting individual trees from the lidar point cloud,

Reference 31

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Observation 420d9361-0af0-4986-9b3f-84da89d875f6 · outbound

This paper cites Evaluating tree detection and segmentation routines on very high resolution uav lidar data,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Evaluating tree detection and segmentation routines on very high resolution uav lidar data,

Reference 32

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Observation 2e011c4e-6f3a-4303-8803-11e54b615042 · outbound

This paper cites Estimating tree structural parameters via automatic tree segmentation from lidar point cloud data,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Estimating tree structural parameters via automatic tree segmentation from lidar point cloud data,

Reference 33

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Observation 3519dbcf-bc58-4412-8a79-080468f29597 · outbound

This paper cites Tree instance segmentation and traits estimation for forestry environments exploiting lidar data collected by mobile robots,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Tree instance segmentation and traits estimation for forestry environments exploiting lidar data collected by mobile robots,

Reference 34

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Observation 86ded534-6563-4dd7-97c3-de5f7146e93d · outbound

This paper cites Online tree reconstruction and forest inventory on a mobile robotic system,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Online tree reconstruction and forest inventory on a mobile robotic system,

Reference 35

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Observation 5bf19621-9055-4003-bae7-77a944763032 · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Pointnet++: Deep hierarchical feature learning on point sets in a metric space,

Reference 36

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Observation 0178670b-4363-4ea5-82a4-ea4b3834c48c · outbound

This paper cites Randla-net: Efficient semantic segmentation of large- scale point clouds,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Randla-net: Efficient semantic segmentation of large- scale point clouds,

Reference 37

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source=pdf_text observed=2026-08-02T19:07:54.971439Z digest=sha256:1a5beef15a91c9c664f56bb92bab4fca4ca590fb2401728319924f477b804e53

Observation 1c802923-b26c-4154-bdcc-91211be1b5b4 · outbound

This paper cites Digiforests: a longitudinal lidar dataset for forestry robotics,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Digiforests: a longitudinal lidar dataset for forestry robotics,

Reference 38

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source=pdf_text observed=2026-08-02T19:07:54.975445Z digest=sha256:51fc54b751e87ec257aa5f3fe37890183872ad6d582e1221b95dc63cf2582c9f

Observation 86f49c84-b965-4de5-aba1-294173ead6f8 · outbound

This paper cites Wild-places: A large-scale dataset for lidar place recognition in unstructured natural environments,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Wild-places: A large-scale dataset for lidar place recognition in unstructured natural environments,

Reference 39

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source=pdf_text observed=2026-08-02T19:07:54.979520Z digest=sha256:25e2a2b580b007534420e209135d76b10bc56e0a86588a93051cf12c34c306de

Observation 83436a92-43da-4ac9-a575-df12cbded7e7 · outbound

This paper cites Semi-direct tree reconstruction using terrestrial lidar point cloud data,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Semi-direct tree reconstruction using terrestrial lidar point cloud data,

Reference 40

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source=pdf_text observed=2026-08-02T19:07:54.983343Z digest=sha256:663eefe6e29045c5dc4569ed80ae8c9c145dec44385579945f0ec4e8b4121a88

Observation 10927f54-e9d0-414a-9f5a-d1c4acfd8c54 · outbound

This paper cites Global localization of autonomous robots in forest environments,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Global localization of autonomous robots in forest environments,

Reference 41

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source=pdf_text observed=2026-08-02T19:07:54.987132Z digest=sha256:b3f2cbf4b760bcfd9fea1e89d94e8cff2478b7ad9ddcdb15454c23f78b0f787d

Observation de3a5a16-4303-495a-ad94-68cc403e5c59 · outbound

This paper cites Ring++: Roto-translation invariant gram for global localization on a sparse scan map,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Ring++: Roto-translation invariant gram for global localization on a sparse scan map,

Reference 42

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source=pdf_text observed=2026-08-02T19:07:54.991051Z digest=sha256:ec7b05c75572c8ce2e3bfdd144329530c812b6fe6faf9e5556d89dc3f6e13b7f

Observation fcd762b0-c6fa-4d94-8a18-fee4f6318935 · outbound

This paper cites M2dp: A novel 3d point cloud descriptor and its application in loop closure detection,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory M2dp: A novel 3d point cloud descriptor and its application in loop closure detection,

Reference 43

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source=pdf_text observed=2026-08-02T19:07:54.994941Z digest=sha256:9bb3cbf893e3a929f20fa1c4e7d901772d2b54b72052638e06d0463e652ea9c9

Observation 9cd1ce26-6a34-4747-9356-1cd548b315db · outbound

This paper cites One ring to rule them all: Radon sinogram for place recognition, orientation and translation estimation,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory One ring to rule them all: Radon sinogram for place recognition, orientation and translation estimation,

Reference 44

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source=pdf_text observed=2026-08-02T19:07:54.999024Z digest=sha256:ad18f7e4f334d89d157af5441d4c3c82a0912a99479550b98e02c5bf39a28508

Observation 2079dbf3-59c4-4594-94d5-46a9ddb69c3d · outbound

This paper cites Fast point feature histograms (fpfh) for 3d registration,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Fast point feature histograms (fpfh) for 3d registration,

Reference 45

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source=pdf_text observed=2026-08-02T19:07:55.002921Z digest=sha256:6a8c490f6b9d3dba460b73f9d9bdb8ccb49b4c38d4cfe99a12301bdff147b84b

Observation 17c47dab-40c6-4849-b836-5db2cea02d05 · outbound

This paper cites Shot: Unique signatures of histograms for surface and texture description,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Shot: Unique signatures of histograms for surface and texture description,

Reference 46

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source=pdf_text observed=2026-08-02T19:07:55.007015Z digest=sha256:935a7361ab5fa8708a4ad3b1cf62351ea833e862bded1fc2a56fc55e5c86188a

Observation 8a00af91-02ac-4dd7-9af5-45d972d5dca0 · outbound

This paper cites Place recognition using keypoint voting in large 3d lidar datasets,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Place recognition using keypoint voting in large 3d lidar datasets,

Reference 47

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source=pdf_text observed=2026-08-02T19:07:55.010971Z digest=sha256:93e108b853c1159a1de694f4cd97743024df46cc3f3b7b7cac7f702613589e79

Observation e7d0555c-4406-44eb-882d-3edf9df08d74 · outbound

This paper cites Efficiently Closing Loops in LiDAR-Based SLAM Using Point Cloud Density Maps.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Efficiently Closing Loops in LiDAR-Based SLAM Using Point Cloud Density Maps

Reference 48

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source=pdf_text observed=2026-08-02T19:07:55.015036Z digest=sha256:b2ba526877ddd04862600b6e1a1a30bbd4d4e2c94a2cf740ec07cb5847095167

Observation 47a88651-ea9b-4c6f-9084-9c122b30fab4 · outbound

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

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Orb: An efficient alternative to sift or surf,

Reference 49

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source=pdf_text observed=2026-08-02T19:07:55.019130Z digest=sha256:9d93a6593da131486c07dc3249d76902d8c35dc25fd9326aad332b2c8919e8f5

Observation 1d96897a-ba84-48a2-84af-ba8fcfaa1f22 · outbound

This paper cites Intensity triangle descriptor constructed from high-resolution spinning lidar intensity image for loop closure detection,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Intensity triangle descriptor constructed from high-resolution spinning lidar intensity image for loop closure detection,

Reference 50

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source=pdf_text observed=2026-08-02T19:07:55.023301Z digest=sha256:77e835a8b04c4249cd483f9931015163bdf1f965817d08836b107214b229520e

Observation 883364e0-f71d-47c2-bfa6-a5980b8ce5ac · outbound

This paper cites Re-trip: Reflectivity instance augmented triangle descriptor for 3d place recognition,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Re-trip: Reflectivity instance augmented triangle descriptor for 3d place recognition,

Reference 51

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source=pdf_text observed=2026-08-02T19:07:55.027466Z digest=sha256:03e9e1de1293f733a50f79ae63f7d6cea0dd8a7fb50669fcb045915e5bd5328d

Observation 74a12252-7309-467a-8d38-4e22cdda7ae0 · outbound

This paper cites Pointnetvlad: Deep point cloud based retrieval for large-scale place recognition,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Pointnetvlad: Deep point cloud based retrieval for large-scale place recognition,

Reference 52

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source=pdf_text observed=2026-08-02T19:07:55.031563Z digest=sha256:c7b8ddfdad0019d16196a4293aa639e2ebac6d15d0b4220aec4a9856dae8df70

Observation dc045f01-2f5a-4f98-bb1e-5e2247b886e4 · outbound

This paper cites TransLoc3D : Point Cloud based Large-scale Place Recognition using Adaptive Receptive Fields.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory TransLoc3D : Point Cloud based Large-scale Place Recognition using Adaptive Receptive Fields

Reference 53

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source=pdf_text observed=2026-08-02T19:07:55.035522Z digest=sha256:758980c750ee0818d9b6b82497c1600cf350989873408a78e22d7eac927e4797

Observation e5eafa40-6542-4923-9526-3acc72a74f1d · outbound

This paper cites Logg3d-net: Locally guided global descriptor learning for 3d place recognition,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Logg3d-net: Locally guided global descriptor learning for 3d place recognition,

Reference 54

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source=pdf_text observed=2026-08-02T19:07:55.039795Z digest=sha256:5203abb682f7799c8a3515f915670b24c0bd231fdc150fa8726c90cef828f685

Observation a647791a-60de-4ace-9a65-0af2c6407696 · outbound

This paper cites 4d spatio-temporal convnets: Minkowski convolutional neural networks,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory 4d spatio-temporal convnets: Minkowski convolutional neural networks,

Reference 55

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source=pdf_text observed=2026-08-02T19:07:55.044103Z digest=sha256:a448562721aaf949dfc08379e477f65ab1194139e48cc32ac443bf53ed16e559

Observation f18d3bca-26c5-4317-9a87-e5b5bdbb3358 · outbound

This paper cites Improving point cloud based place recognition with ranking-based loss and large batch training,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Improving point cloud based place recognition with ranking-based loss and large batch training,

Reference 56

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source=pdf_text observed=2026-08-02T19:07:55.048020Z digest=sha256:8981566c12dc151417d19f81bc3588016e5ac8058267c370f12132197fbd5685

Observation ae50fa8f-3485-45ea-bc47-0a58badc8f4c · outbound

This paper cites Hotformerloc: Hierarchical octree transformer for versatile lidar place recognition across ground and aerial views,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Hotformerloc: Hierarchical octree transformer for versatile lidar place recognition across ground and aerial views,

Reference 57

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source=pdf_text observed=2026-08-02T19:07:55.051816Z digest=sha256:975c3a9e59ae58d0d75fc9b49caccb1364f4ddc0213cc70473330519504dbdf5

Observation 001acfce-cec7-4aa0-aafa-49d4e6be899b · outbound

This paper cites Forestlpr: Lidar place recognition in forests attentioning multiple bev density images,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Forestlpr: Lidar place recognition in forests attentioning multiple bev density images,

Reference 58

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source=pdf_text observed=2026-08-02T19:07:55.055652Z digest=sha256:7c9768a403fbdcd810e1d188def1b2770c84c7d2df9509d322ebdecaea1c300e

Observation a1f050e7-0c50-4098-b15a-7d7fb6de7eb4 · outbound

This paper cites Bevplace++: Fast, robust, and lightweight lidar global localization for unmanned ground vehicles,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Bevplace++: Fast, robust, and lightweight lidar global localization for unmanned ground vehicles,

Reference 59

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source=pdf_text observed=2026-08-02T19:07:55.059491Z digest=sha256:25588fd3369c04105caa68e59d1ab766968228eb7057ac1007114a5f10239624

Observation e55cd499-9986-4701-9525-5fe644fb701e · outbound

This paper cites Bvmatch: Lidar- based place recognition using bird’s-eye view images,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Bvmatch: Lidar- based place recognition using bird’s-eye view images,

Reference 60

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source=pdf_text observed=2026-08-02T19:07:55.063474Z digest=sha256:c99295808687df3cb8af099feaa3790f84a4f00ad086a93fc6f4a4f160b98c5c

Observation c6290134-8460-4a4c-ae9f-74c88b5f8ee2 · outbound

This paper cites ImLPR: Image-based LiDAR Place Recognition using Vision Foundation Models.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory ImLPR: Image-based LiDAR Place Recognition using Vision Foundation Models

Reference 61

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source=pdf_text observed=2026-08-02T19:07:55.067433Z digest=sha256:a0f5aa7aa74249ec068232d3a9c9796ee01421799299de34ed915a9d73a3e8ef

Observation 95b666db-d75f-469e-be65-a80a29a94a25 · outbound

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

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Dinov2: Learning robust visual features without supervision,

Reference 62

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source=pdf_text observed=2026-08-02T19:07:55.071741Z digest=sha256:5d123ee70855c5aaccd75ec1233bc61c41bb98ff6209f38df87949af73a6200c

Observation 81f78a66-b216-4e08-bfb1-ed7a80112c58 · outbound

This paper cites Boxgraph: Semantic place recognition and pose estimation from 3d lidar,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Boxgraph: Semantic place recognition and pose estimation from 3d lidar,

Reference 63

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source=pdf_text observed=2026-08-02T19:07:55.075758Z digest=sha256:44e2b0d0dd974e4a44a638d5f01d67d102a1b8eadc020f896524f52f8631ea89

Observation 624dd69c-a07a-4408-b1d2-bcc61f71d2b0 · outbound

This paper cites Tripletloc: One-shot global localization using semantic triplet in urban environ- ments,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Tripletloc: One-shot global localization using semantic triplet in urban environ- ments,

Reference 64

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source=pdf_text observed=2026-08-02T19:07:55.079758Z digest=sha256:afee8283f7c5bbfcaa23f8f8447ecd18befdc488c9efd5c25017fa8887e6812c

Observation 9b6ac154-3d2f-4ace-8401-6d1008459696 · outbound

This paper cites Spectral geometric verification: Re-ranking point cloud retrieval for metric localization,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Spectral geometric verification: Re-ranking point cloud retrieval for metric localization,

Reference 65

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source=pdf_text observed=2026-08-02T19:07:55.083473Z digest=sha256:050ecc31d3979cd2ee3b6b93352e6930fe0ce4200219940100d50b8ee05d6611

Observation cd04929e-a3c2-4481-aa14-4837e06e092a · outbound

This paper cites Lcdnet: Deep loop closure detection and point cloud registration for lidar slam,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Lcdnet: Deep loop closure detection and point cloud registration for lidar slam,

Reference 66

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source=pdf_text observed=2026-08-02T19:07:55.087282Z digest=sha256:f02572246fa5961047d1d3a2eba4217e78e38dd32257d5ab04cdad28c6d5a993

Observation dc82ccce-9837-44f5-b6c1-f316a096187d · outbound

This paper cites Egonn: Egocen- tric neural network for point cloud based 6dof relocalization at the city scale,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Egonn: Egocen- tric neural network for point cloud based 6dof relocalization at the city scale,

Reference 67

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source=pdf_text observed=2026-08-02T19:07:55.091261Z digest=sha256:4bba9b395490c0b8b958f3eb827a41ef236f2b817fb768c2cea3052fc8cf84e9

Observation 3c6bdaef-429e-4647-bcae-4b46bc3436bb · outbound

This paper cites Towards operational marker-free registration of terrestrial lidar data in forests,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Towards operational marker-free registration of terrestrial lidar data in forests,

Reference 68

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source=pdf_text observed=2026-08-02T19:07:55.095335Z digest=sha256:d5930bdcc3995180cca66384c7401aac79adf6655462bb1e8476df35724df1d0

Observation 148eb999-51fc-4af8-9910-b3e4dc1f73f1 · outbound

This paper cites Ground-to-air collaborative lidar global localization in forest environments,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Ground-to-air collaborative lidar global localization in forest environments,

Reference 69

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source=pdf_text observed=2026-08-02T19:07:55.099163Z digest=sha256:4466e6ed837e342521480037a614eb58b01056ac12111872c454b8f1411e356b

Observation fd2169f5-8ebd-4a77-a3d1-af4fa3672738 · outbound

This paper cites Fast-lio2: Fast direct lidar-inertial odometry,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Fast-lio2: Fast direct lidar-inertial odometry,

Reference 70

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source=pdf_text observed=2026-08-02T19:07:55.102811Z digest=sha256:22f07f263e67bb879c5eb3385b159a621e2ddff4377f12712cc0f33b386706a6

Observation 816e0299-dae0-48a5-8c16-b9c786461a17 · outbound

This paper cites Direct lidar-inertial odometry: Lightweight lio with continuous-time motion correction,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Direct lidar-inertial odometry: Lightweight lio with continuous-time motion correction,

Reference 71

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source=pdf_text observed=2026-08-02T19:07:55.106907Z digest=sha256:8d9840d382382ee65ff475fc7d22735b1b51d5e0d668d7262fe775676481ddae

Observation 01aa13c7-4e7f-4e7e-a20b-476e9b81aedd · outbound

This paper cites Geotransformer: Fast and robust point cloud registration with geometric transformer,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Geotransformer: Fast and robust point cloud registration with geometric transformer,

Reference 72

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Observation 039f615e-a6a4-470a-90f8-5f79c5d782bb · outbound

This paper cites evo: Python package for the evaluation of odometry and slam.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory evo: Python package for the evaluation of odometry and slam

Reference 73

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Observation 1e976b42-5459-4d80-8b7d-7218523375ce · outbound

This paper cites Register any point: Scaling 3d point cloud registration by flow matching,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Register any point: Scaling 3d point cloud registration by flow matching,

Reference 74

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Observation f1d6533f-1388-4427-8d6d-83b500669933 · outbound

This paper cites Vilens: Visual, inertial, lidar, and leg odometry for all-terrain legged robots,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Vilens: Visual, inertial, lidar, and leg odometry for all-terrain legged robots,

Reference 75

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Observation 30e9c494-a5d3-4dc4-975f-10096358baba · outbound

This paper cites Vision meets robotics: The kitti dataset,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Vision meets robotics: The kitti dataset,

Reference 76

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Observation de703ccc-91b6-4435-973e-61c7b626b4ec · outbound

This paper cites 1 year, 1000 km: The oxford robotcar dataset,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory 1 year, 1000 km: The oxford robotcar dataset,

Reference 77

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Observation db292693-bc3f-4bba-8194-f251242c09b5 · outbound

This paper cites Buffer: Balancing accuracy, efficiency, and generalizability in point cloud registration,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Buffer: Balancing accuracy, efficiency, and generalizability in point cloud registration,

Reference 78

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Observation 320d81dd-3497-40f6-b8b4-aa368d6cfe01 · outbound

This paper cites Buffer-x: Towards zero-shot point cloud registration in diverse scenes,.

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory Buffer-x: Towards zero-shot point cloud registration in diverse scenes,

Reference 79

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