Paper Citation Record · LEDGER

Foundational Models for 3D Point Clouds: A Survey and Outlook

As of 23 August 2026, this Paper Citation Record lists 100 of 195 outbound references and 5 inbound Pith citation observations for arXiv:2501.18594.

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

pith.paper-citation-record.v1
2501.18594 v1

Coverage vector

measured 100 of 195 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T22:54:24.659200Z

measured 105 of 105 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T06:42:45.558324Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T22:54:01.275994Z

Reference resolution

100 of 195 outbound references displayed

verified exact2
verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bc7dfbd2-6cdc-4bd3-8472-062479939c3e · outbound

This paper cites an unresolved cited work.

Foundational Models for 3D Point Clouds: A Survey and Outlook Unresolved cited work

Reference 1

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Observation f141d820-27cb-4ce3-a978-ffcc93217c27 · outbound

This paper cites 3D Vision with Transformers: A Survey.

Foundational Models for 3D Point Clouds: A Survey and Outlook 3D Vision with Transformers: A Survey

Reference 2

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Observation 8bb0e135-0162-41fc-8432-76b6fb5d3bd2 · outbound

This paper cites contributors.

Foundational Models for 3D Point Clouds: A Survey and Outlook contributors

Reference 3

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Foundational Models for 3D Point Clouds: A Survey and Outlook Unresolved cited work

Reference 4

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Observation 20447c8a-fbf4-4d37-9540-7176bb0df6ab · outbound

This paper cites Transformers in 3D Point Clouds: A Survey.

Foundational Models for 3D Point Clouds: A Survey and Outlook Transformers in 3D Point Clouds: A Survey

Reference 5

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This paper cites Mao et al.

Foundational Models for 3D Point Clouds: A Survey and Outlook Mao et al

Reference 6

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Observation cfd23933-5876-48c9-9cb0-de581a0ca20a · outbound

This paper cites Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey.

Foundational Models for 3D Point Clouds: A Survey and Outlook Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey

Reference 7

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Observation ac8e1277-fb34-422f-ad22-1865194f2548 · outbound

This paper cites Dai et al.

Foundational Models for 3D Point Clouds: A Survey and Outlook Dai et al

Reference 8

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Observation 78db49e9-2475-4fba-9b21-1733fe422694 · outbound

This paper cites Yeshwanth et al.

Foundational Models for 3D Point Clouds: A Survey and Outlook Yeshwanth et al

Reference 9

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Observation a77482dc-5236-4f9c-873b-5a3a07246b3c · outbound

This paper cites Schult et al.

Foundational Models for 3D Point Clouds: A Survey and Outlook Schult et al

Reference 10

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This paper cites Wang et al.

Foundational Models for 3D Point Clouds: A Survey and Outlook Wang et al

Reference 11

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Observation 83dd8ea5-363b-4d0a-92ae-53c094e5eacf · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Foundational Models for 3D Point Clouds: A Survey and Outlook On the Opportunities and Risks of Foundation Models

Reference 12

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Foundational Models for 3D Point Clouds: A Survey and Outlook Unresolved cited work

Reference 13

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Observation b4234848-7739-4bf8-9e04-9f1df796c7e5 · outbound

This paper cites an unresolved cited work.

Foundational Models for 3D Point Clouds: A Survey and Outlook Unresolved cited work

Reference 14

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Observation 737309a8-aada-4185-8384-4667304a0c71 · outbound

This paper cites Devlin et al.

Foundational Models for 3D Point Clouds: A Survey and Outlook Devlin et al

Reference 15

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This paper cites Brown et al.

Foundational Models for 3D Point Clouds: A Survey and Outlook Brown et al

Reference 16

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Observation c56ea6b1-d4cd-4d5b-aec2-a7c0db22d09a · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Radford et al

Reference 17

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Observation 8028499c-c671-4f34-8ca9-1dbb57287e87 · outbound

This paper cites Zhu et al.

Foundational Models for 3D Point Clouds: A Survey and Outlook Zhu et al

Reference 18

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Observation 6e0d6973-bbd4-4ed9-b284-083a3ca99db6 · outbound

This paper cites CLIP model is an Efficient Continual Learner.

Foundational Models for 3D Point Clouds: A Survey and Outlook CLIP model is an Efficient Continual Learner

Reference 19

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Observation 4b49d000-fbf9-43c2-b45b-678daf5e64cd · outbound

This paper cites Kirillov et al.

Foundational Models for 3D Point Clouds: A Survey and Outlook Kirillov et al

Reference 20

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Observation 4e49623e-56e3-4c0d-b9f7-1f31966aff56 · outbound

This paper cites Towards Segment Anything Model (SAM) for Medical Image Segmentation: A Survey.

Foundational Models for 3D Point Clouds: A Survey and Outlook Towards Segment Anything Model (SAM) for Medical Image Segmentation: A Survey

Reference 21

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Observation 6cab5ee9-ecdb-4907-85a4-258c7f4fe6e1 · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Yang et al

Reference 22

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Foundational Models for 3D Point Clouds: A Survey and Outlook Xue et al

Reference 23

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Foundational Models for 3D Point Clouds: A Survey and Outlook Xue et al

Reference 24

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Foundational Models for 3D Point Clouds: A Survey and Outlook Zhang et al

Reference 25

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Foundational Models for 3D Point Clouds: A Survey and Outlook Liu et al

Reference 26

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Observation 0a22f031-f50a-466d-8d30-2f4dbe6c4148 · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Umam et al

Reference 27

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Observation cf57f40c-da85-4d11-ae8b-ce21da69f734 · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Bai et al

Reference 28

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Foundational Models for 3D Point Clouds: A Survey and Outlook Liu et al

Reference 29

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This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Foundational Models for 3D Point Clouds: A Survey and Outlook Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 30

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Foundational Models for 3D Point Clouds: A Survey and Outlook Chiang et al

Reference 31

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Foundational Models for 3D Point Clouds: A Survey and Outlook Textbooks Are All You Need

Reference 32

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Foundational Models for 3D Point Clouds: A Survey and Outlook Luo et al

Reference 33

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Foundational Models for 3D Point Clouds: A Survey and Outlook Qi et al

Reference 34

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Foundational Models for 3D Point Clouds: A Survey and Outlook RegionBLIP: A Unified Multi-modal Pre-training Framework for Holistic and Regional Comprehension

Reference 35

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Observation 61f03748-4333-4386-899c-90051ae9eaa7 · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Chen et al

Reference 36

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Foundational Models for 3D Point Clouds: A Survey and Outlook Roh et al

Reference 37

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Foundational Models for 3D Point Clouds: A Survey and Outlook Huang et al

Reference 38

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Foundational Models for 3D Point Clouds: A Survey and Outlook Ye et al

Reference 39

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Foundational Models for 3D Point Clouds: A Survey and Outlook ImageBind-LLM: Multi-modality Instruction Tuning

Reference 40

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Foundational Models for 3D Point Clouds: A Survey and Outlook Jia et al

Reference 41

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Foundational Models for 3D Point Clouds: A Survey and Outlook Liu et al

Reference 42

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Observation 85db6d7a-47ce-45e4-8ba4-3260ff566c69 · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Zhu et al

Reference 43

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Foundational Models for 3D Point Clouds: A Survey and Outlook Guo et al

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Foundational Models for 3D Point Clouds: A Survey and Outlook Zeng et al

Reference 45

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Foundational Models for 3D Point Clouds: A Survey and Outlook Wang et al

Reference 46

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Foundational Models for 3D Point Clouds: A Survey and Outlook Prakash et al

Reference 47

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Foundational Models for 3D Point Clouds: A Survey and Outlook Tang et al

Reference 48

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Foundational Models for 3D Point Clouds: A Survey and Outlook Awais et al

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Foundational Models for 3D Point Clouds: A Survey and Outlook Xiao et al

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Foundational Models for 3D Point Clouds: A Survey and Outlook Unresolved cited work

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Foundational Models for 3D Point Clouds: A Survey and Outlook Wu et al

Reference 52

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Foundational Models for 3D Point Clouds: A Survey and Outlook Fu et al

Reference 53

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Foundational Models for 3D Point Clouds: A Survey and Outlook Collins et al

Reference 54

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Foundational Models for 3D Point Clouds: A Survey and Outlook Jensen et al

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Foundational Models for 3D Point Clouds: A Survey and Outlook Yao et al

Reference 56

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Foundational Models for 3D Point Clouds: A Survey and Outlook Unresolved cited work

Reference 57

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Foundational Models for 3D Point Clouds: A Survey and Outlook Downs et al

Reference 58

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Foundational Models for 3D Point Clouds: A Survey and Outlook Liu et al

Reference 59

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Foundational Models for 3D Point Clouds: A Survey and Outlook Reizenstein et al

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Foundational Models for 3D Point Clouds: A Survey and Outlook Wu et al

Reference 61

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Observation 137a3fd0-db7c-491c-93d1-d3cf16152da5 · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Chang et al

Reference 62

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Foundational Models for 3D Point Clouds: A Survey and Outlook Zhou et al

Reference 63

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Observation 506d69c3-c801-4091-a066-7f9fd4bf9cbf · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Baruch et al

Reference 64

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Foundational Models for 3D Point Clouds: A Survey and Outlook Rozenberszki et al

Reference 65

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Observation 390d3a2b-fd14-436b-911d-a2b5466c6b3f · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Behley et al

Reference 66

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Foundational Models for 3D Point Clouds: A Survey and Outlook Deschaud et al

Reference 67

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Foundational Models for 3D Point Clouds: A Survey and Outlook Caesar et al

Reference 68

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Foundational Models for 3D Point Clouds: A Survey and Outlook Dai et al

Reference 69

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Foundational Models for 3D Point Clouds: A Survey and Outlook Caesar et al

Reference 70

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Foundational Models for 3D Point Clouds: A Survey and Outlook Deitke et al

Reference 71

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Foundational Models for 3D Point Clouds: A Survey and Outlook Chen et al

Reference 72

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This paper cites SceneVerse: Scaling 3D Vision-Language Learning for Grounded Scene Understanding.

Foundational Models for 3D Point Clouds: A Survey and Outlook SceneVerse: Scaling 3D Vision-Language Learning for Grounded Scene Understanding

Reference 73

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This paper cites LiDAR-LLM: Exploring the Potential of Large Language Models for 3D LiDAR Understanding.

Foundational Models for 3D Point Clouds: A Survey and Outlook LiDAR-LLM: Exploring the Potential of Large Language Models for 3D LiDAR Understanding

Reference 74

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This paper cites GPT-4 Technical Report.

Foundational Models for 3D Point Clouds: A Survey and Outlook GPT-4 Technical Report

Reference 75

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Foundational Models for 3D Point Clouds: A Survey and Outlook Unresolved cited work

Reference 76

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Foundational Models for 3D Point Clouds: A Survey and Outlook Achlioptas et al

Reference 77

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Foundational Models for 3D Point Clouds: A Survey and Outlook Zhang et al

Reference 78

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This paper cites Ma et al.

Foundational Models for 3D Point Clouds: A Survey and Outlook Ma et al

Reference 79

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Foundational Models for 3D Point Clouds: A Survey and Outlook Donahue et al

Reference 80

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Foundational Models for 3D Point Clouds: A Survey and Outlook Russakovsky et al

Reference 81

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Observation bf05aae9-72e2-48b4-85ad-9628eea6d0dd · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook He et al

Reference 82

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Foundational Models for 3D Point Clouds: A Survey and Outlook Radford et al

Reference 83

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This paper cites Emergent Abilities of Large Language Models.

Foundational Models for 3D Point Clouds: A Survey and Outlook Emergent Abilities of Large Language Models

Reference 84

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Foundational Models for 3D Point Clouds: A Survey and Outlook Dosovitskiy et al

Reference 85

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Foundational Models for 3D Point Clouds: A Survey and Outlook He et al

Reference 86

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Foundational Models for 3D Point Clouds: A Survey and Outlook Deng et al

Reference 87

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Foundational Models for 3D Point Clouds: A Survey and Outlook Sun et al

Reference 88

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This paper cites A Survey of Large Language Models.

Foundational Models for 3D Point Clouds: A Survey and Outlook A Survey of Large Language Models

Reference 89

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Foundational Models for 3D Point Clouds: A Survey and Outlook Li et al

Reference 90

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Foundational Models for 3D Point Clouds: A Survey and Outlook Alayrac et al

Reference 91

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This paper cites Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment.

Foundational Models for 3D Point Clouds: A Survey and Outlook Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 92

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This paper cites Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation.

Foundational Models for 3D Point Clouds: A Survey and Outlook Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation

Reference 93

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Foundational Models for 3D Point Clouds: A Survey and Outlook Lester et al

Reference 94

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Observation f37aa857-0d03-4527-adfe-73ca234ac738 · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Unresolved cited work

Reference 95

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Observation 810a3b8b-f2e5-422f-9e1a-638ca1a16670 · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Dettmers et al

Reference 96

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Observation cc9b5f96-106b-4529-a30c-3334a3f7a7ee · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Xu et al

Reference 97

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Observation 6d6e4d42-4c70-4368-8bcc-3d40dc65baea · outbound

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Foundational Models for 3D Point Clouds: A Survey and Outlook Qian et al

Reference 98

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Observation 7a18df7f-ea35-4c60-9745-fad8c9bc6701 · outbound

This paper cites Kang et al.

Foundational Models for 3D Point Clouds: A Survey and Outlook Kang et al

Reference 99

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Observation 2adb0d4b-30b4-4f76-9536-be8dddb82c01 · outbound

This paper cites Wu et al.

Foundational Models for 3D Point Clouds: A Survey and Outlook Wu et al

Reference 100

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Pith citing papers

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C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion cites this paper.

C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion Foundational Models for 3D Point Clouds: A Survey and Outlook

Reference 29

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Observation 6c619908-0f0d-4af6-96a4-8251ef3ea15a · inbound

Discretizing Group-Convolutional Neural Networks for 3D Geometry in Feature Space cites this paper.

Discretizing Group-Convolutional Neural Networks for 3D Geometry in Feature Space Foundational Models for 3D Point Clouds: A Survey and Outlook

Reference 53

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Observation 62c0f79f-3ac6-4cbd-8f70-b94359546e27 · inbound

Resolving Long-Tail Ambiguity in Unsupervised 3D Point Cloud Segmentation with Language Priors cites this paper.

Resolving Long-Tail Ambiguity in Unsupervised 3D Point Cloud Segmentation with Language Priors Foundational Models for 3D Point Clouds: A Survey and Outlook

Reference 39

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Observation 6f19c1d6-2b2d-45c2-bb93-beb760a76afb · inbound

Pantheon360: Taming Digital Twin Generation via 3D-Aware 360{\deg} Video Diffusion cites this paper.

Pantheon360: Taming Digital Twin Generation via 3D-Aware 360{\deg} Video Diffusion Foundational Models for 3D Point Clouds: A Survey and Outlook

Reference 61

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Source-reported events for the cited work

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Observation 18b2e2e1-2824-43e5-a7cd-9cdbe6c006c3 · inbound

GReFEM: Multimodal LLMs as Zero-Shot Semantic Assistants for Physics-Guided 3D Mesh Refinement cites this paper.

GReFEM: Multimodal LLMs as Zero-Shot Semantic Assistants for Physics-Guided 3D Mesh Refinement Foundational Models for 3D Point Clouds: A Survey and Outlook

Reference 65

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