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Paper Citation Record · LEDGER

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models

As of 20 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 0 inbound Pith citation observations for arXiv:2607.19120.

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

pith.paper-citation-record.v1
2607.19120 v1

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measured 83 of 83 reference resolution

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measured 0 of 0 inbound itemization

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83 of 83 outbound references displayed

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Outbound references

Observation fb201c52-ea36-45a7-8e3e-6fe8e1f187c5 · outbound

This paper cites In: Proceedings of the IEEE/CVF international conference on computer vision.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF international conference on computer vision

Reference 1

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This paper cites In: The Twelfth International Conference on Learning Representations (2024) 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: The Twelfth International Conference on Learning Representations (2024) 3

Reference 2

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This paper cites Cambridge University Press (2023) 18.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models Cambridge University Press (2023) 18

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This paper cites arXiv preprint arXiv:2506.07198 (2025) 4.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models arXiv preprint arXiv:2506.07198 (2025) 4

Reference 4

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This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 5

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This paper cites In: Proceedings of the IEEE/CVF international conference on computer vision.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF international conference on computer vision

Reference 6

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This paper cites In: The Twelfth International Conference on Learning Representations (2024) 2, 4, 17.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: The Twelfth International Conference on Learning Representations (2024) 2, 4, 17

Reference 7

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This paper cites SceneCompleter: Dense 3D Scene Completion for Generative Novel View Synthesis.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models SceneCompleter: Dense 3D Scene Completion for Generative Novel View Synthesis

Reference 8

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This paper cites In: European conference on computer vision.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: European conference on computer vision

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This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 10

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 11

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This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF International Conference on Computer Vision

Reference 12

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This paper cites arXiv preprint arXiv:2510.14586 (2025) 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models arXiv preprint arXiv:2510.14586 (2025) 3

Reference 13

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This paper cites Advances in Neural Information Processing Systems (2024) 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models Advances in Neural Information Processing Systems (2024) 3

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 15

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This paper cites Advances in neural information processing systems30(2017) 7.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models Advances in neural information processing systems30(2017) 7

Reference 16

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: ACM SIGGRAPH 2024 conference papers

Reference 17

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This paper cites arXiv preprint arXiv:2601.04090 (2026) 2, 3, 6, 7, 19 12.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models arXiv preprint arXiv:2601.04090 (2026) 2, 3, 6, 7, 19 12

Reference 18

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This paper cites Advances in neural information processing systems37, 33007–33036 (2024) 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models Advances in neural information processing systems37, 33007–33036 (2024) 3

Reference 19

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF international conference on computer vision

Reference 20

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recog- nition (CVPR)

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models arXiv preprint arXiv:2603.22275 (2026) 3

Reference 23

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This paper cites In: The Thirteenth Interna- tional Conference on Learning Representations (2025),https://openreview.net/forum? id=QQBPWtvtcn1, 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: The Thirteenth Interna- tional Conference on Learning Representations (2025),https://openreview.net/forum? id=QQBPWtvtcn1, 3

Reference 24

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models ACM Trans

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: arXiv preprint arXiv:2602.21341 (2026) 1, 3

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 27

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models Adam: A Method for Stochastic Optimization

Reference 29

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 30

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Reference 31

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceed- ings of the European Conference on Computer Vision (2024) 3

Reference 32

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This paper cites arXiv preprint arXiv:2507.10496 (2025) 6.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models arXiv preprint arXiv:2507.10496 (2025) 6

Reference 33

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Reference 34

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: 8th Annual Conference on Robot Learning (2024) 3

Reference 35

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models Depth Anything 3: Recovering the Visual Space from Any Views

Reference 36

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: The Eleventh International Conference on Learning Representations (2023) 2, 3, 5

Reference 37

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Observation b5f1f9ae-2869-464e-aa82-384dff7f99f0 · outbound

This paper cites ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model

Reference 38

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Observation 4842a797-e422-41bd-9919-aa1201f9dc15 · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV).

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)

Reference 39

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Observation 32f659d0-0e97-4cc0-9aab-c2af449469d6 · outbound

This paper cites ProSplat: Improved Feed-Forward 3D Gaussian Splatting for Wide-Baseline Sparse Views.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models ProSplat: Improved Feed-Forward 3D Gaussian Splatting for Wide-Baseline Sparse Views

Reference 40

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Observation 1c2ce45a-eeef-44d2-8476-b1b6ecaeee50 · outbound

This paper cites Communications of the ACM 65(1), 99–106 (2021) 1, 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models Communications of the ACM 65(1), 99–106 (2021) 1, 3

Reference 41

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This paper cites In: International Conference on Machine Learning.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: International Conference on Machine Learning

Reference 42

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Observation 135e2d80-a1fd-482f-8047-c6c70b9c6649 · outbound

This paper cites In: Intelligent Systems for Molecular Biology (ISMB) (2025) 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Intelligent Systems for Molecular Biology (ISMB) (2025) 3

Reference 43

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Observation d46a3926-10cc-423f-81d0-b01257efd6d2 · outbound

This paper cites ACM transactions on graphics (TOG)41(4), 1–15 (2022) 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models ACM transactions on graphics (TOG)41(4), 1–15 (2022) 3

Reference 44

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogni- tion.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogni- tion

Reference 45

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Observation 3edea52f-3cbc-4391-a21e-95862daff04b · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV).

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)

Reference 46

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This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 47

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This paper cites In: The Thirty-ninth Annual Conference on Neural Information Processing Systems (2025) 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: The Thirty-ninth Annual Conference on Neural Information Processing Systems (2025) 3

Reference 48

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This paper cites In: Proceed- ings of the IEEE/CVF international conference on computer vision.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceed- ings of the IEEE/CVF international conference on computer vision

Reference 49

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Observation 2766da83-7a97-4c09-8223-deeadd28d6ba · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recog- nition (CVPR).

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recog- nition (CVPR)

Reference 50

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 51

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This paper cites In: Conference on Computer Vision and Pattern Recognition (CVPR) (2016) 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Conference on Computer Vision and Pattern Recognition (CVPR) (2016) 3

Reference 52

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This paper cites In: European Conference on Computer Vision (ECCV) (2016) 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: European Conference on Computer Vision (ECCV) (2016) 3

Reference 53

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This paper cites In: Proceedings of the IEEE conference on computer vision and pattern recognition.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 54

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Observation b1445b2d-c061-4bb4-8f56-fb0a29014fef · outbound

This paper cites Advances in Neural Information Processing Systems (NeurIPS) (2024) 2, 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models Advances in Neural Information Processing Systems (NeurIPS) (2024) 2, 3

Reference 55

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Observation cb765f99-62b4-4009-81ed-514600db00cf · outbound

This paper cites Neurocomputing568, 127063 (2024) 6 14.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models Neurocomputing568, 127063 (2024) 6 14

Reference 56

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This paper cites arXiv preprint arXiv:2603.12655 (2026) 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models arXiv preprint arXiv:2603.12655 (2026) 3

Reference 57

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This paper cites IEEE Transactions on pattern analysis and machine intelligence13(4), 376–380 (1991) 6, 22.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models IEEE Transactions on pattern analysis and machine intelligence13(4), 376–380 (1991) 6, 22

Reference 58

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This paper cites In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recognition.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recognition

Reference 59

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2025) 2, 3, 4, 7, 19.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2025) 2, 3, 4, 7, 19

Reference 60

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2024) 2, 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2024) 2, 3

Reference 61

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Observation 126cdfe7-2be9-4289-91c9-a169cd468621 · outbound

This paper cites IEEE transactions on image processing13(4), 600–612 (2004) 7.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models IEEE transactions on image processing13(4), 600–612 (2004) 7

Reference 62

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This paper cites In: ACM SIGGRAPH 2024 Con- ference Papers (2024).

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: ACM SIGGRAPH 2024 Con- ference Papers (2024)

Reference 63

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This paper cites GSFix3D: Diffusion-Guided Repair of Novel Views in Gaussian Splatting.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models GSFix3D: Diffusion-Guided Repair of Novel Views in Gaussian Splatting

Reference 64

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This paper cites In: European conference on computer vi- sion.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: European conference on computer vi- sion

Reference 65

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This paper cites International Conference on Learning Representations (ICLR) (2026) 2, 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models International Conference on Learning Representations (ICLR) (2026) 2, 3

Reference 66

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024)

Reference 67

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This paper cites In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recognition.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recognition

Reference 68

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This paper cites In: Proceedings of the Computer Vision and Pattern Recognition Conference.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the Computer Vision and Pattern Recognition Conference

Reference 69

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Observation bd6cc6de-73ca-4480-bd98-faeb2eb7af22 · outbound

This paper cites generation: Taming optimization dilemma in latent diffusion models.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models generation: Taming optimization dilemma in latent diffusion models

Reference 70

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Observation 7f554886-159a-4daf-94ae-6316ef2c9698 · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF International Conference on Computer Vision

Reference 71

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Observation 274fd6fd-73eb-4680-8fa2-bec8d4431043 · outbound

This paper cites Fast protein backbone generation with SE(3) flow matching.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models Fast protein backbone generation with SE(3) flow matching

Reference 72

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Observation 6db8af50-3745-44f2-87ca-814b57fdb79f · outbound

This paper cites GSFixer: Improving 3D Gaussian Splatting with Reference-Guided Video Diffusion Priors.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models GSFixer: Improving 3D Gaussian Splatting with Reference-Guided Video Diffusion Priors

Reference 73

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Observation 69338f4a-47ec-40ab-874a-5714327b5a87 · outbound

This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 74

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Observation 4dd6c27a-9b04-413b-ae76-03e350293ef7 · outbound

This paper cites IEEE Transactions on Pattern Analysis & Machine Intelligence (2025).

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models IEEE Transactions on Pattern Analysis & Machine Intelligence (2025)

Reference 75

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This paper cites In: European Conference on Computer Vision.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: European Conference on Computer Vision

Reference 76

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This paper cites In: Proceedings of the IEEE/CVF Con- ference on Computer Vision and Pattern Recognition (CVPR).

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE/CVF Con- ference on Computer Vision and Pattern Recognition (CVPR)

Reference 77

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This paper cites In: Proceedings of the IEEE conference on computer vision and pattern recognition.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 78

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This paper cites In: The Fourteenth International Conference on Learning Representations (2026) 2, 3, 4.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: The Fourteenth International Conference on Learning Representations (2026) 2, 3, 4

Reference 79

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This paper cites In: Advances in Neural Information Processing Systems (2024) 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: Advances in Neural Information Processing Systems (2024) 3

Reference 80

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This paper cites In: SIGGRAPH (2018) 6.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: SIGGRAPH (2018) 6

Reference 81

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This paper cites In: The Thirty-ninth Annual Conference on Neural Information Processing Systems (2025) 3.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models In: The Thirty-ninth Annual Conference on Neural Information Processing Systems (2025) 3

Reference 82

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Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models a realistic scene

Reference 83

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Pith citing papers

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