Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians | Paper Citation Record

Observation ade452fb-e9c5-4694-97e8-cdfefb20f62a · outbound

This paper cites Multilayer perceptrons.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Multilayer perceptrons

Reference 1

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Observation 023b8b38-2388-4759-878f-787bb348aa66 · outbound

This paper cites Distributions of the kullback–leibler divergence with applications.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Distributions of the kullback–leibler divergence with applications

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.104806Z

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Observation 496659cd-2b27-4b97-b682-d5a522bebf00 · outbound

This paper cites Generative and Discriminative Voxel Modeling with Convolutional Neural Networks.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Generative and Discriminative Voxel Modeling with Convolutional Neural Networks

Reference 3

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Observation 09ba7605-1d71-4a39-aaa5-16b431967c5f · outbound

This paper cites Pythae: Unifying generative autoencoders in python - a benchmarking use case.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Pythae: Unifying generative autoencoders in python - a benchmarking use case

Reference 4

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Observation 12e7cc7d-b285-436a-b611-84bf121c83c0 · outbound

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

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians ShapeNet: An Information-Rich 3D Model Repository

Reference 5

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Observation 6c8a98e7-4270-4ff2-9da0-fed938adb9ba · outbound

This paper cites MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers

Reference 6

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Observation c6020f08-3734-47da-af5a-4eb2928dee34 · outbound

This paper cites Gaussianpro: 3d gaussian splatting with progressive propagation.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Gaussianpro: 3d gaussian splatting with progressive propagation

Reference 7

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Observation 62746139-3a85-4283-abe3-44b82be68420 · outbound

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

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians 4d spatio-temporal convnets: Minkowski convolutional neural networks

Reference 8

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Observation efa55b27-6d37-4e61-b4d8-ccb10b6d65d5 · outbound

This paper cites LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenes.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenes

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.452250Z

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Observation 2099a656-76b5-44f3-8c3a-01bfdd9b631e · outbound

This paper cites Spconv: Spatially sparse convolu- tion library.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Spconv: Spatially sparse convolu- tion library

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.457495Z

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Observation 89fe8348-5639-4c75-acda-6ae6be271c0c · outbound

This paper cites Fu, Stefano Ermon, Atri Rudra, and Christopher R´e.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Fu, Stefano Ermon, Atri Rudra, and Christopher R´e

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.462086Z

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Observation 4fe76e6f-a265-4706-aceb-033c3f6ccf98 · outbound

This paper cites Objaverse: A universe of annotated 3d objects.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Objaverse: A universe of annotated 3d objects

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.466986Z

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Observation 8cab9c38-8427-44ed-bb1b-bedc96ddba8b · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.472046Z

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Observation d49d3394-ce2f-41c4-a3fc-2257e9f8c139 · outbound

This paper cites InstantSplat: Sparse-view Gaussian Splatting in Seconds.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians InstantSplat: Sparse-view Gaussian Splatting in Seconds

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.476687Z

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Observation f6d2a99f-df3b-4fa6-8f7c-ee09c4b379ae · outbound

This paper cites Scenescape: Text-driven consistent scene generation.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Scenescape: Text-driven consistent scene generation

Reference 15

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Observation c28b0003-e277-44d6-a5f3-6c14ac1e36e8 · outbound

This paper cites Get3d: A generative model of high quality 3d tex- tured shapes learned from images.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Get3d: A generative model of high quality 3d tex- tured shapes learned from images

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.486267Z

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Observation fda0f968-a72e-45b6-83ae-46ea0f4210b9 · outbound

This paper cites Vfusion3d: Learning scalable 3d generative models from video diffusion models.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Vfusion3d: Learning scalable 3d generative models from video diffusion models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.490648Z

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Observation fb019e7c-45d0-46ba-ac02-791b3236f3d1 · outbound

This paper cites Text2room: Extracting textured 3d meshes from 2d text-to-image models.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Text2room: Extracting textured 3d meshes from 2d text-to-image models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.496700Z

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Observation 1ab6946e-1969-4931-aaaf-e6a2414e183a · outbound

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

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians LRM: Large Reconstruction Model for Single Image to 3D

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.501550Z

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Observation 0e6afee0-c86d-4a48-9ee7-b67fc269e166 · outbound

This paper cites Mvd-fusion: Single-view 3d via depth-consistent multi-view generation.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Mvd-fusion: Single-view 3d via depth-consistent multi-view generation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.506250Z

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Observation 8cf3ff54-2f13-4926-a318-bfebfc014cc0 · outbound

This paper cites Perceiver IO: A General Architecture for Structured Inputs & Outputs.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Perceiver IO: A General Architecture for Structured Inputs & Outputs

Reference 21

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Observation 3efe8cf1-7abf-4ef0-963d-8cf724c9472d · outbound

This paper cites Perceiver: General perception with iterative attention.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Perceiver: General perception with iterative attention

Reference 22

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Observation cab6230d-1623-4ba1-b5b6-d17af05badd2 · outbound

This paper cites LEAP: Liberate Sparse-view 3D Modeling from Camera Poses.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians LEAP: Liberate Sparse-view 3D Modeling from Camera Poses

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.521050Z

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Observation f5fb7fdc-f3a0-46ed-bade-ce2f0ec93a19 · outbound

This paper cites Shap-E: Generating Conditional 3D Implicit Functions.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Shap-E: Generating Conditional 3D Implicit Functions

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.527010Z

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Observation 437589df-77f4-4abb-8f92-351468aa712a · outbound

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

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians 3d gaussian splatting for real-time radiance field rendering

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.531725Z

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Observation 72fcf7bf-885f-46f1-a285-e9e870bcff4b · outbound

This paper cites 9 A hierarchical 3d gaussian representation for real-time ren- dering of very large datasets.ACM Transactions on Graphics (TOG), 43(4):1–15, 2024.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians 9 A hierarchical 3d gaussian representation for real-time ren- dering of very large datasets.ACM Transactions on Graphics (TOG), 43(4):1–15, 2024

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.549373Z

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Observation 6d7118ea-e134-4f17-aead-d47ee34674b4 · outbound

This paper cites Auto-Encoding Variational Bayes.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Auto-Encoding Variational Bayes

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.542270Z

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Observation 9f35262f-b92d-4892-8831-f2feb60bb843 · outbound

This paper cites Segment any- thing.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Segment any- thing

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.533680Z

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Observation 2dc3e813-5c99-4db9-bcb6-2ad387bfca0b · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.518186Z

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Observation 810dd91f-cfbd-49cc-9f75-5b22f988582d · outbound

This paper cites Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.557093Z

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Observation 4578ced1-93ea-4352-8706-8864439b6d8f · outbound

This paper cites Infinitenature-zero: Learning perpetual view generation of natural scenes from single images.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Infinitenature-zero: Learning perpetual view generation of natural scenes from single images

Reference 31

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Observation a68b8336-dcc7-4569-a929-219152bdb894 · outbound

This paper cites Analytic-Splatting: Anti-Aliased 3D Gaussian Splatting via Analytic Integration.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Analytic-Splatting: Anti-Aliased 3D Gaussian Splatting via Analytic Integration

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.566659Z

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Observation f6bb1280-0788-443a-8a16-3aa92dadee76 · outbound

This paper cites Infinicity: Infinite-scale city synthesis.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Infinicity: Infinite-scale city synthesis

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.481920Z

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Observation 4b013dee-0750-4d5c-b847-82a3debca4fd · outbound

This paper cites Vastgaussian: Vast 3d gaussians for large scene reconstruction.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Vastgaussian: Vast 3d gaussians for large scene reconstruction

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.463222Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a7d45d92-ba02-4a5d-9962-d83ce799e55d · outbound

This paper cites Dl3dv-10k: A large-scale scene dataset for deep learning-based 3d vision.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Dl3dv-10k: A large-scale scene dataset for deep learning-based 3d vision

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.445521Z

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Observation 472fedf4-85c1-4912-961d-72d058c481b9 · outbound

This paper cites Infinite na- ture: Perpetual view generation of natural scenes from a sin- gle image.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Infinite na- ture: Perpetual view generation of natural scenes from a sin- gle image

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.428747Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f8f12821-eb1a-4a8e-8445-316c67277e3d · outbound

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

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Zero-1-to- 3: Zero-shot one image to 3d object

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.410680Z

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Observation 1d4aa7ab-a045-42f3-b94b-7afe827f26fd · outbound

This paper cites Scaffold-gs: Structured 3d gaussians for view-adaptive rendering.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Scaffold-gs: Structured 3d gaussians for view-adaptive rendering

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.596157Z

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Observation b1f4153d-2bdf-487c-bb04-eceb53bebb42 · outbound

This paper cites Learning Disentangled Representations of Timbre and Pitch for Musical Instrument Sounds Using Gaussian Mixture Variational Autoencoders.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Learning Disentangled Representations of Timbre and Pitch for Musical Instrument Sounds Using Gaussian Mixture Variational Autoencoders

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-06T05:40:04.427452Z

Source-reported events for the cited work

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Observation ed333991-0534-4922-a591-a516b4a7ad54 · outbound

This paper cites ShapeSplat: A Large-scale Dataset of Gaussian Splats and Their Self-Supervised Pretraining.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians ShapeSplat: A Large-scale Dataset of Gaussian Splats and Their Self-Supervised Pretraining

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.606488Z

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Observation a1e728a5-2d3f-4890-b9ba-94110db0d790 · outbound

This paper cites Normalized image representation for efficient coding.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Normalized image representation for efficient coding

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.381013Z

Source-reported events for the cited work

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Observation b4a7c29c-9b54-4ebc-b001-a5fcf01b8746 · outbound

This paper cites Text2mesh: Text-driven neural stylization for meshes.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Text2mesh: Text-driven neural stylization for meshes

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.364513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 09816c25-23ce-4a7c-ace4-847c01a4b2e7 · outbound

This paper cites Srinivasan, Matthew Tancik, Jonathan T.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Srinivasan, Matthew Tancik, Jonathan T

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.347659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d1e57c8d-f6a7-4787-84b7-15b7e9642349 · outbound

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

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Nerf: Representing scenes as neural radiance fields for view syn- thesis

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.330413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c85d9587-b574-4e03-9f4e-357b3cd0920d · outbound

This paper cites Point-E: A System for Generating 3D Point Clouds from Complex Prompts.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Point-E: A System for Generating 3D Point Clouds from Complex Prompts

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.630311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d89d24f1-cf36-49e0-8046-ec460767c623 · outbound

This paper cites RadSplat: Radiance Field-Informed Gaussian Splatting for Robust Real-Time Rendering with 900+ FPS.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians RadSplat: Radiance Field-Informed Gaussian Splatting for Robust Real-Time Rendering with 900+ FPS

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.635392Z

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Unavailable: canonical work link unavailable.

Observation 0d47e623-4ec9-4fee-9ccf-74502c821c11 · outbound

This paper cites Scalable diffusion models with transformers.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Scalable diffusion models with transformers

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.640434Z

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Observation ff760e60-3f2b-407f-ba3b-16fb0dbfaa22 · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians DreamFusion: Text-to-3D using 2D Diffusion

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.645160Z

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Observation be18c55e-aab9-4ea1-83ee-2516cfa635d8 · outbound

This paper cites PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.650167Z

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Observation e7174681-dd9c-4636-bfa0-e7a236832d27 · outbound

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

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.655993Z

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Unavailable: canonical work link unavailable.

Observation 655f993d-3f31-4595-9de9-0ebd6633efa3 · outbound

This paper cites PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.661798Z

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Unavailable: canonical work link unavailable.

Observation 9e772010-722b-40b4-8457-735a734f7839 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Learning transferable visual models from natural language supervi- sion

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.666531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1a82b3a-c634-4f46-a61a-5a0f17bfa062 · outbound

This paper cites L3DG: Latent 3D Gaussian Diffusion.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians L3DG: Latent 3D Gaussian Diffusion

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.671111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba95d573-68d7-4e9c-9b3c-61752b6d6945 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models, 2021.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians High-resolution image syn- thesis with latent diffusion models, 2021

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.676036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d360c3fe-e629-4b93-82ae-d81d1781652b · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians High-resolution image synthesis with latent diffusion models

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.255627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1f9e8531-9ea7-4d9b-8bd3-0ec54dd563f5 · outbound

This paper cites Structure-from-motion revisited.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Structure-from-motion revisited

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.238128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 880dcc3d-4c07-4cf1-8e3d-99e4786a7593 · outbound

This paper cites Structure- from-motion revisited.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Structure- from-motion revisited

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.219205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8654c724-b509-4a25-8e77-5bf7dc29bab9 · outbound

This paper cites MVDream: Multi-view Diffusion for 3D Generation.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians MVDream: Multi-view Diffusion for 3D Generation

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.695673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e441c834-65d7-4c12-97ed-0dec8a2a415d · outbound

This paper cites A Tutorial on Principal Component Analysis.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians A Tutorial on Principal Component Analysis

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.700583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5afa075-99b5-43a5-b83b-5d9c80a06a79 · outbound

This paper cites Meshgpt: Generating triangle meshes with decoder-only transformers.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Meshgpt: Generating triangle meshes with decoder-only transformers

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.201546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 800bfc10-c584-4bea-991f-cb1a6dde5a65 · outbound

This paper cites Flash3D: Feed-Forward Generalisable 3D Scene Reconstruction from a Single Image.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Flash3D: Feed-Forward Generalisable 3D Scene Reconstruction from a Single Image

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.710315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7689cadd-88f5-4789-b159-fd12638e3b7e · outbound

This paper cites Splatter image: Ultra-fast single-view 3d recon- struction.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Splatter image: Ultra-fast single-view 3d recon- struction

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.179695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6ef4870b-8a2f-473a-9072-3b8ca9271c83 · outbound

This paper cites Bolt3d: Generating 3d scenes in seconds.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Bolt3d: Generating 3d scenes in seconds

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.720173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46c7ef1d-a59a-4dc9-a82f-a8e278370c52 · outbound

This paper cites Fourier features let networks learn high frequency functions in low dimen- sional domains.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Fourier features let networks learn high frequency functions in low dimen- sional domains

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.157906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 389c69bb-f1bf-4678-8fdd-1a1527444e22 · outbound

This paper cites DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.729815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 864783cb-2e63-4a65-aa49-8f99e4d4d607 · outbound

This paper cites Lgm: Large multi-view gaussian model for high-resolution 3d content creation.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Lgm: Large multi-view gaussian model for high-resolution 3d content creation

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.139746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c3402165-9428-4b73-a476-1e49f995d8a2 · outbound

This paper cites Learning spatiotemporal features with 3d convolutional networks.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Learning spatiotemporal features with 3d convolutional networks

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.116960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e5d8dcb8-f2d7-439a-884b-0a7727a4788a · outbound

This paper cites NV AE: A deep hierarchical variational autoencoder.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians NV AE: A deep hierarchical variational autoencoder

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.095050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ffef42a3-b7a9-4ec7-8142-31937b787adf · outbound

This paper cites Visualizing data using t-sne.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Visualizing data using t-sne

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.074908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7a479ea5-e4d2-459a-aa2f-eecc8cc335cf · outbound

This paper cites Attention is all you need.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Attention is all you need

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.754762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be6d9391-b11c-4b4b-bfe9-10f299eaf454 · outbound

This paper cites Attentive normalization for conditional image generation.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Attentive normalization for conditional image generation

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.034413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 308b95f0-7914-45b9-bcc8-49faf60e8f19 · outbound

This paper cites Multimodal token fusion for vision transformers.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Multimodal token fusion for vision transformers

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:05.016471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d51641dd-2d35-4fe0-98ab-aaad3c7f177a · outbound

This paper cites Mio: A foundation model on multimodal tokens.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Mio: A foundation model on multimodal tokens

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.771362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 184e5407-d039-4cf4-b678-dc5ffbe31a0a · outbound

This paper cites Synsin: End-to-end view synthesis from a sin- gle image.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Synsin: End-to-end view synthesis from a sin- gle image

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:04.998607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c2ac9a19-5d1d-4f99-92a7-957996242c55 · outbound

This paper cites DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Model.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Model

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.782181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f385edd4-5504-4c06-a826-f69f12cf3d4a · outbound

This paper cites GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Models.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Models

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.787111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8023790f-ebaa-4222-a7cc-48e74919bcec · outbound

This paper cites WonderWorld: Interactive 3D Scene Generation from a Single Image.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians WonderWorld: Interactive 3D Scene Generation from a Single Image

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.792126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0548f45-576d-451f-bbbb-e1b66750237a · outbound

This paper cites Wonderjourney: Going from anywhere to everywhere.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Wonderjourney: Going from anywhere to everywhere

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:04.980977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ffbffcb8-a41f-4aa4-b6d3-54d2f7c77583 · outbound

This paper cites Mvimgnet: A large-scale dataset of multi-view images.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Mvimgnet: A large-scale dataset of multi-view images

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:04.963244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c7f5b902-c19e-4816-ba5e-9cd129ee0972 · outbound

This paper cites Mip-splatting: Alias-free 3d gaussian splat- ting.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Mip-splatting: Alias-free 3d gaussian splat- ting

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.806763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 377d8018-1edd-4e57-bc92-2441b99e5035 · outbound

This paper cites GaussianCube: A Structured and Explicit Radiance Representation for 3D Generative Modeling.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians GaussianCube: A Structured and Explicit Radiance Representation for 3D Generative Modeling

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.812830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ccaec45-27ef-4f44-b1ca-154e0ed79baf · outbound

This paper cites Gs-lrm: Large recon- struction model for 3d gaussian splatting.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Gs-lrm: Large recon- struction model for 3d gaussian splatting

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.818205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dedc7ccf-7714-4e97-918b-d3c5dbc888fd · outbound

This paper cites Point transformer.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Point transformer

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:04.920672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a9e58314-9994-4bde-b334-7b66a04ba59a · outbound

This paper cites CV-VAE: A Compatible Video VAE for Latent Generative Video Models.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians CV-VAE: A Compatible Video VAE for Latent Generative Video Models

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:03.827247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca6dc4fc-fa22-485a-be8b-936ef24e5b2b · outbound

This paper cites Michelangelo: Conditional 3d shape generation based on shape-image-text aligned latent representation.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Michelangelo: Conditional 3d shape generation based on shape-image-text aligned latent representation

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:04.902743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d6cd2609-1226-48b4-b6ac-18a2214dc6f4 · outbound

This paper cites an unresolved cited work.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Unresolved cited work

Reference 86

Resolution: unresolved; raw_fallback, observed 2026-08-06T05:40:04.884663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 700fe0d0-ed9d-4a4f-8d90-00ca0a5f42ab · outbound

This paper cites an unresolved cited work.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Unresolved cited work

Reference 87

Resolution: unresolved; raw_fallback, observed 2026-08-06T05:40:04.862807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d8a4fc10-ebaf-4fd0-9de2-b8252e747bfd · outbound

This paper cites Both Tab.2 and Fig.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Both Tab.2 and Fig

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:04.845243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0fd2ac06-a670-4ef6-833a-0220ba19cf2a · outbound

This paper cites an unresolved cited work.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Unresolved cited work

Reference 89

Resolution: unresolved; raw_fallback, observed 2026-08-06T05:40:04.826826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c1d055e3-7fd5-404e-9f03-417964634248 · outbound

This paper cites Instead, we append the positional embed- ding only from 3DGS’s position.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Instead, we append the positional embed- ding only from 3DGS’s position

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:04.804581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1f49fa39-f321-48f4-8658-db266acdcf7f · outbound

This paper cites an unresolved cited work.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Unresolved cited work

Reference 91

Resolution: unresolved; raw_fallback, observed 2026-08-06T05:40:04.786515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f9c0a4bd-b15a-419b-8a13-d0ebc82a621f · outbound

This paper cites 19, we demonstrate more results from our Can3Tok with various test scenes.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians 19, we demonstrate more results from our Can3Tok with various test scenes

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:04.766468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ec3709b4-2056-4d90-964b-11d62aa3ae8f · outbound

This paper cites Ground-Truth 3D Gaussian la- tents.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Ground-Truth 3D Gaussian la- tents

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:40:04.745741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7af35ee7-a0d4-4860-94e9-047aa5539341 · outbound

This paper cites an unresolved cited work.

Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians Unresolved cited work

Reference 94

Resolution: unresolved; raw_fallback, observed 2026-08-06T05:40:04.726919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers