Paper Citation Record · LEDGER

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds

As of 7 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2508.11265.

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

pith.paper-citation-record.v1
2508.11265 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:07:17.350618Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

verified exact0
verified fuzzy43
unresolved2
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 22353b9a-f694-4b41-87e6-f17423ba91d8 · outbound

This paper cites Se- mantickitti: A dataset for semantic scene understanding of lidar sequences.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Se- mantickitti: A dataset for semantic scene understanding of lidar sequences

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56c72e80-250d-4fc0-98f8-c0d7b6db6a80 · outbound

This paper cites Adpl: Adaptive dual path learning for do- main adaptation of semantic segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Adpl: Adaptive dual path learning for do- main adaptation of semantic segmentation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:26.396768Z

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Observation 11edf3a7-f807-4da3-a8ab-02cdd5b415bb · outbound

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

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds 4d spatio-temporal convnets: Minkowski convolutional neural networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:26.121534Z

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Observation 05c860af-0ed5-4626-935c-971d67f460c5 · outbound

This paper cites A novel object re-track framework for 3d point clouds.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds A novel object re-track framework for 3d point clouds

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:25.873574Z

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Observation 052aa329-59aa-44fa-aa20-bef0b1d28b92 · outbound

This paper cites Learning entropic wasserstein embeddings.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Learning entropic wasserstein embeddings

Reference 5

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Source-reported events for the cited work

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Observation 29e9c179-d558-4ae6-bcc5-e445c622c87d · outbound

This paper cites Handling open-set noise and novel target recognition in do- main adaptive semantic segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Handling open-set noise and novel target recognition in do- main adaptive semantic segmentation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:25.488191Z

Source-reported events for the cited work

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Observation 391e8681-6d61-4259-a677-6c81cd251b9c · outbound

This paper cites Deep learning for 3d point clouds: A survey.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Deep learning for 3d point clouds: A survey

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:25.248717Z

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 c56d874b-1500-4211-a306-6380853d047a · outbound

This paper cites Fog simulation on real lidar point clouds for 3d object detection in adverse weather.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Fog simulation on real lidar point clouds for 3d object detection in adverse weather

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:25.096236Z

Source-reported events for the cited work

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Observation 8fe22d6a-6ded-4d62-b1d4-f5e6e5520cd7 · outbound

This paper cites Manet: Multi- scale aware-relation network for semantic segmentation in aerial scenes.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Manet: Multi- scale aware-relation network for semantic segmentation in aerial scenes

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:24.879341Z

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 5193d170-ec67-4339-90be-79883a6476d6 · outbound

This paper cites Domain generalization-aware uncertainty introspective learning for 3d point clouds segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Domain generalization-aware uncertainty introspective learning for 3d point clouds segmentation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:24.516265Z

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 b3e5703c-f28e-4deb-92e7-75171ea2fa6d · outbound

This paper cites Cross-domain scene unsupervised learning segmentation with dynamic subdomains.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Cross-domain scene unsupervised learning segmentation with dynamic subdomains

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:24.201170Z

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 727f4740-5032-4359-8f58-503dce223fa6 · outbound

This paper cites A patch diversity transformer for domain generalized semantic segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds A patch diversity transformer for domain generalized semantic segmentation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:23.907269Z

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 60f3473e-e054-47dd-a5cf-725a2af9de85 · outbound

This paper cites Prototype adaption and projection for few- and zero-shot 3d point cloud semantic segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Prototype adaption and projection for few- and zero-shot 3d point cloud semantic segmentation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:23.594835Z

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 e42512eb-123b-4939-a702-e3f123899d26 · outbound

This paper cites Cross-modal learning for domain adaptation in 3d semantic segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Cross-modal learning for domain adaptation in 3d semantic segmentation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:23.282067Z

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 15efb40c-3998-4551-9b4c-3d708290f5e9 · outbound

This paper cites Scalable optimal trans- port methods in machine learning: A contemporary survey.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Scalable optimal trans- port methods in machine learning: A contemporary survey

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:23.101260Z

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 00a1ac49-2846-42f7-8762-baa262aebf25 · outbound

This paper cites Single domain generalization for lidar semantic segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Single domain generalization for lidar semantic segmentation

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:22.886579Z

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 f756dd12-0de4-44d7-88b1-268979531577 · outbound

This paper cites Virtual multi-view fusion for 3d semantic segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Virtual multi-view fusion for 3d semantic segmentation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:22.673444Z

Source-reported events for the cited work

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Observation f1073aba-4748-43a3-bcd4-050a4c64379b · outbound

This paper cites Stratified trans- former for 3d point cloud segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Stratified trans- former for 3d point cloud segmentation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:22.476705Z

Source-reported events for the cited work

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Observation e038e05e-8df5-4df0-a981-67dc654d2aee · outbound

This paper cites Domain generalization with adversarial feature learning.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Domain generalization with adversarial feature learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:22.261865Z

Source-reported events for the cited work

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Observation 052e19ba-f2e6-4c45-b64e-b5e6f704ab02 · outbound

This paper cites Semantic hierarchy-aware segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Semantic hierarchy-aware segmentation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:22.092035Z

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 0a32dcd9-378c-403f-a336-171ddf7cdf25 · outbound

This paper cites Chapman, Dongpu Cao, and Jonathan Li.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Chapman, Dongpu Cao, and Jonathan Li

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:21.915098Z

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 1bf39a0a-b5db-4345-8e90-9e8166daff53 · outbound

This paper cites Grab-net: Graph-based boundary-aware network for medical point cloud segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Grab-net: Graph-based boundary-aware network for medical point cloud segmentation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:21.700671Z

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 38bd4225-2f14-4e48-bb6d-92ef2f25e85c · outbound

This paper cites Explore the influence of shallow information on point cloud registration.IEEE Trans- actions on Neural Networks and Learning Systems, pages 1– 13, 2023.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Explore the influence of shallow information on point cloud registration.IEEE Trans- actions on Neural Networks and Learning Systems, pages 1– 13, 2023

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:21.528120Z

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 fa24de78-6452-44a7-bf0e-d81f067a6dee · outbound

This paper cites V oxnet: A 3d con- volutional neural network for real-time object recognition.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds V oxnet: A 3d con- volutional neural network for real-time object recognition

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:21.311233Z

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 f3a27664-2725-4d76-8320-078f0d229139 · outbound

This paper cites Re- thinking data augmentation for robust lidar semantic seg- mentation in adverse weather.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Re- thinking data augmentation for robust lidar semantic seg- mentation in adverse weather

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:21.141760Z

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 9a1cfae2-3341-4ab5-b0a1-3f5890404386 · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T20:07:15.958293Z

Source-reported events for the cited work

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Observation 2bae7803-56d2-43bf-b9e7-820ec2d08961 · outbound

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

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Pointnet++: Deep hierarchical feature learning on point sets in a metric space

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:20.904387Z

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 549bf00b-1067-4ea0-942c-0c05104f3678 · outbound

This paper cites Compositional seman- tic mix for domain adaptation in point cloud segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Compositional seman- tic mix for domain adaptation in point cloud segmentation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:20.701677Z

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 66facaa7-5431-4e87-bc3d-6933bad79727 · outbound

This paper cites Contrastive boundary learning for point cloud segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Contrastive boundary learning for point cloud segmentation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:20.546279Z

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 7febcc50-62b0-44c5-b8d9-c06a9d1ea360 · outbound

This paper cites Visualizing data using t-sne.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Visualizing data using t-sne

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:20.394742Z

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 2a086cf8-709b-4f40-a0e2-be8b9e471a87 · outbound

This paper cites Generalizing to unseen domains: A survey on do- main generalization.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Generalizing to unseen domains: A survey on do- main generalization

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:20.226149Z

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 c28c8193-886d-4872-a2ec-1fcf4f7e8fb4 · outbound

This paper cites Polarmix: A general data augmen- tation technique for lidar point clouds.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Polarmix: A general data augmen- tation technique for lidar point clouds

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:19.950896Z

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 e560968c-4aaf-45cd-af22-e8f6ce56e211 · outbound

This paper cites Transfer learning from synthetic to real lidar point cloud for semantic segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Transfer learning from synthetic to real lidar point cloud for semantic segmentation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:19.717598Z

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 215c7e99-1639-4910-8fc4-ea5a8afe86a1 · outbound

This paper cites Unsupervised point cloud rep- resentation learning with deep neural networks: A survey.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Unsupervised point cloud rep- resentation learning with deep neural networks: A survey

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:19.494930Z

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 749cf9c9-8387-4c0e-9b3c-b6ec405b0ec7 · outbound

This paper cites 3d semantic segmentation in the wild: Learning generalized models for adverse-condition point clouds.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds 3d semantic segmentation in the wild: Learning generalized models for adverse-condition point clouds

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:19.300885Z

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 148cf1e7-340a-4776-949d-4b287227e0ab · outbound

This paper cites Squeeze- segv3: Spatially-adaptive convolution for efficient point- cloud segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Squeeze- segv3: Spatially-adaptive convolution for efficient point- cloud segmentation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:19.070237Z

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 12c12cf9-e95c-4765-9ed5-5b31176fb136 · outbound

This paper cites Ept-net: Edge perception trans- former for 3d medical image segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Ept-net: Edge perception trans- former for 3d medical image segmentation

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:18.835474Z

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 5a52a0c8-f705-4541-8e6a-5132ed411f4a · outbound

This paper cites Pcl: Proxy-based contrastive learning for domain generalization.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Pcl: Proxy-based contrastive learning for domain generalization

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:18.678293Z

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 5f72e941-e8ad-4966-b153-c757267876f3 · outbound

This paper cites Com- plete & label: A domain adaptation approach to seman- tic segmentation of lidar point clouds.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Com- plete & label: A domain adaptation approach to seman- tic segmentation of lidar point clouds

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:18.444628Z

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 066838ca-3cf7-4e5c-8ab1-7681ba2a6bd7 · outbound

This paper cites Attan: Attention adversarial networks for 3d point cloud semantic segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Attan: Attention adversarial networks for 3d point cloud semantic segmentation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:18.276981Z

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 b8644ef2-0b5d-4297-8a55-180639e8592a · outbound

This paper cites A curriculum domain adaptation approach to the se- mantic segmentation of urban scenes.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds A curriculum domain adaptation approach to the se- mantic segmentation of urban scenes

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:18.130037Z

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 8854cb9c-eb32-457e-b717-e867f9390ffb · outbound

This paper cites Learning shape-invariant rep- resentation for generalizable semantic segmentation.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Learning shape-invariant rep- resentation for generalizable semantic segmentation

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:18.034802Z

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 637412ed-fbd1-41f4-824a-1491efccd32c · outbound

This paper cites Unimix: Towards domain adaptive and gener- alizable lidar semantic segmentation in adverse weather.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Unimix: Towards domain adaptive and gener- alizable lidar semantic segmentation in adverse weather

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:17.858846Z

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 53553aed-4254-4b2a-bfeb-ed08f04186e3 · outbound

This paper cites Domain generalization: A survey.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds Domain generalization: A survey

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:17.705998Z

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 a1cadd37-54cf-4620-a711-6f4f6bb0c514 · outbound

This paper cites A survey on open- vocabulary detection and segmentation: Past, present, and future.

Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds A survey on open- vocabulary detection and segmentation: Past, present, and future

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:07:17.556374Z

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.

Pith citing papers

No inbound Pith citation observations are available.