Paper Citation Record · LEDGER

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation

As of 24 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2501.09838.

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

pith.paper-citation-record.v1
2501.09838 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:39:48.301572Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

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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

46 of 46 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 794aafcc-f5a9-439c-b993-f36a468d1fa4 · outbound

This paper cites Raysar- 3d sar simulator: Now open source.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Raysar- 3d sar simulator: Now open source

Reference 1

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Observation fab8a9d8-0e86-4033-8e0a-69ebfa7b531d · outbound

This paper cites Mip-nerf: A multiscale representation for anti-aliasing neu- ral radiance fields.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Mip-nerf: A multiscale representation for anti-aliasing neu- ral radiance fields

Reference 2

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This paper cites Zip-nerf: Anti-aliased grid-based neural radiance fields.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Zip-nerf: Anti-aliased grid-based neural radiance fields

Reference 3

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This paper cites Sf3d: Stable fast 3d mesh reconstruction with uv-unwrapping and illumination disentanglement.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Sf3d: Stable fast 3d mesh reconstruction with uv-unwrapping and illumination disentanglement

Reference 4

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Observation e00edd8e-f6fd-49e9-8252-4dd8015a4542 · outbound

This paper cites Efficient geometry-aware 3d generative adversarial networks.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Efficient geometry-aware 3d generative adversarial networks

Reference 5

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Observation 8c988b66-e426-44fb-b2aa-d38da026f762 · outbound

This paper cites Generative novel view synthesis with 3d-aware diffusion models.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Generative novel view synthesis with 3d-aware diffusion models

Reference 6

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Observation b776f42b-f344-4047-b791-435b22bb7cdd · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation ShapeNet: An Information-Rich 3D Model Repository

Reference 7

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Unresolved cited work

Reference 8

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Observation 25c85ac9-652d-4162-9564-6e7b74d75ba0 · outbound

This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Encoder-decoder with atrous separable convolution for semantic image segmentation

Reference 9

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This paper cites Big data geospatial processing for massive aerial lidar datasets.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Big data geospatial processing for massive aerial lidar datasets

Reference 10

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Observation 61af7d8e-6d06-4249-b4c0-d741c4437d20 · outbound

This paper cites Image Quality Assessment: Unifying Structure and Texture Similarity.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Image Quality Assessment: Unifying Structure and Texture Similarity

Reference 11

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Observation c7f27f39-9f77-484d-9269-49c0d542160c · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation An image is worth 16x16 words: Transformers for image recognition at scale

Reference 12

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Observation c4f93213-4c61-4271-8c88-82acbfb4799e · outbound

This paper cites Sur la distance de deux lois de probabilit´e.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Sur la distance de deux lois de probabilit´e

Reference 13

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Observation 7ce55944-a873-4c50-80e8-66ce1cbde07c · outbound

This paper cites K-planes: Explicit radiance fields in space, time, and appearance.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation K-planes: Explicit radiance fields in space, time, and appearance

Reference 14

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Observation 96dba94f-66ae-48c5-b96e-b7fdd3b07228 · outbound

This paper cites CAT3D: Create Anything in 3D with Multi-View Diffusion Models.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation CAT3D: Create Anything in 3D with Multi-View Diffusion Models

Reference 15

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This paper cites Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 16

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Observation acc40f5b-835d-46f9-bb71-eb6da3761f2b · outbound

This paper cites Denoising dif- fusion probabilistic models.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Denoising dif- fusion probabilistic models

Reference 17

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Observation 1b9728ae-4927-4804-9114-125a93d5ea03 · outbound

This paper cites LRM: Large Reconstruction Model for Single Image to 3D.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation LRM: Large Reconstruction Model for Single Image to 3D

Reference 18

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Observation a0e27922-41dd-41ec-a29d-a80d3737a89e · outbound

This paper cites Segmentation models pytorch.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Segmentation models pytorch

Reference 19

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This paper cites Elucidating the design space of diffusion-based generative models.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Elucidating the design space of diffusion-based generative models

Reference 20

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Observation e2872eba-c92e-4179-8ba5-03421cc00c39 · outbound

This paper cites Analyzing and improving the training dynamics of diffusion models.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Analyzing and improving the training dynamics of diffusion models

Reference 21

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Observation e8a1335a-5721-4447-95b9-4388a9a09ffa · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation A style-based generator architecture for generative adversarial networks

Reference 22

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This paper cites 3d gaussian splatting for real-time radiance field rendering.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation 3d gaussian splatting for real-time radiance field rendering

Reference 23

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This paper cites Zero-1-to- 3: Zero-shot one image to 3d object.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Zero-1-to- 3: Zero-shot one image to 3d object

Reference 24

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This paper cites Nerf: Representing scenes as neural radiance fields for view syn- thesis.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Nerf: Representing scenes as neural radiance fields for view syn- thesis

Reference 25

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Improved denoising diffusion probabilistic models

Reference 26

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation The terrasar-x satel- lite

Reference 27

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Observation eb72f15d-1813-4f8e-96fc-a387d8bb2ebb · outbound

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Barron, and Ben Milden- hall

Reference 28

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Neural implicit surface reconstruction using imaging sonar

Reference 29

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Observation a1f54fbb-57f7-4f88-b5ac-2fbeda7191a6 · outbound

This paper cites Blainder—a blender ai add-on for generation of semantically labeled depth-sensing data.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Blainder—a blender ai add-on for generation of semantically labeled depth-sensing data

Reference 30

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation High-resolution image synthesis with latent diffusion models

Reference 31

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Zero123++: a single image to consistent multi-view dif- fusion base model, 2023

Reference 32

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation MVDream: Multi-view Diffusion for 3D Generation

Reference 33

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Scene representation networks: Continuous 3d- structure-aware neural scene representations

Reference 34

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Deep unsupervised learning using nonequilibrium thermodynamics

Reference 35

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Score-Based Generative Modeling through Stochastic Differential Equations

Reference 36

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Learned initializations for optimizing coordinate-based neural representations

Reference 37

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation

Reference 38

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation TripoSR: Fast 3D Object Reconstruction from a Single Image

Reference 39

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Attention is all you need

Reference 40

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Barron, and Pratul P

Reference 41

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This paper cites Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction

Reference 42

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Reconfusion: 3d reconstruction with diffusion priors

Reference 43

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Observation 542c8a54-7d9b-4efe-821c-6442da928e3c · outbound

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation pixelnerf: Neural radiance fields from one or few images

Reference 44

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CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation The unreasonable effectiveness of deep features as a perceptual metric

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:39:48.416222Z

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Observation 82bb5265-a865-44a6-96ae-e90ee0206960 · outbound

This paper cites Sparsefusion: Dis- tilling view-conditioned diffusion for 3d reconstruction.

CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation Sparsefusion: Dis- tilling view-conditioned diffusion for 3d reconstruction

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:39:48.405531Z

Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.