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Paper Citation Record · LEDGER

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion

As of 18 August 2026, this Paper Citation Record lists 100 of 129 outbound references and 0 inbound Pith citation observations for arXiv:2502.02187.

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

pith.paper-citation-record.v1
2502.02187 v2

Coverage vector

measured 100 of 129 reference resolution

Typed states for the displayed outbound observations.

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measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

100 of 129 outbound references displayed

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  • verified fuzzy36
  • unresolved64
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External citation measurements

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Outbound references

Observation fac6e961-9645-40b6-a5b7-03bb90e47c9d · outbound

This paper cites Photo-realistic floating wood.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Photo-realistic floating wood

Reference 1

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Observation d100b7f9-8528-4015-91d7-e941d44882ab · outbound

This paper cites Learning representations and generative models for 3d point clouds.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Learning representations and generative models for 3d point clouds

Reference 2

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Observation 65f8b743-0fdd-4335-bff3-d57adc6d8ad0 · outbound

This paper cites State of the art on diffusion models for visual computing.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion State of the art on diffusion models for visual computing

Reference 3

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Observation c00505b1-94a9-4bef-b5b8-7ddae237ba83 · outbound

This paper cites Small town.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Small town

Reference 4

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Observation 6b6325a9-c6a1-4696-8b23-b8d41749c441 · outbound

This paper cites Patchmatch: A randomized correspon- dence algorithm for structural image editing.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Patchmatch: A randomized correspon- dence algorithm for structural image editing

Reference 5

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Observation d4920cc3-983f-4d0a-b4ab-39e96a17a1ce · outbound

This paper cites Learn- ing long-term dependencies with gradient descent is diffi- cult.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Learn- ing long-term dependencies with gradient descent is diffi- cult

Reference 6

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Observation e6af0cc1-86c0-42b7-b11b-3bf2b3a2258b · outbound

This paper cites Blender - a 3D modelling and rendering package.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Blender - a 3D modelling and rendering package

Reference 7

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Observation 0a3ec42f-6c2f-4aaa-aaa6-9ec3c86320c2 · outbound

This paper cites Texfusion: Synthesizing 3d textures with text-guided image diffusion models.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Texfusion: Synthesizing 3d textures with text-guided image diffusion models

Reference 8

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Observation 5d00e60d-68d8-4128-9a6b-ef40e057686a · outbound

This paper cites Industrial building.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Industrial building

Reference 9

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Observation ba74710d-539a-4f35-bbeb-44ddbced9e32 · outbound

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

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Efficient geometry-aware 3d generative adversarial networks

Reference 10

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Observation 1df76245-5784-45ed-b79d-18b7976caf3b · outbound

This paper cites Single-stage dif- fusion nerf: A unified approach to 3d generation and recon- struction.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Single-stage dif- fusion nerf: A unified approach to 3d generation and recon- struction

Reference 11

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Observation 98317a43-27d9-4cc0-9fd3-d57c4fc2e322 · outbound

This paper cites Fan- tasia3d: Disentangling geometry and appearance for high- quality text-to-3d content creation.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Fan- tasia3d: Disentangling geometry and appearance for high- quality text-to-3d content creation

Reference 12

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Observation 5eed17d4-cfec-42fc-9d1b-738cad74d319 · outbound

This paper cites On the Importance of Noise Scheduling for Diffusion Models.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion On the Importance of Noise Scheduling for Diffusion Models

Reference 13

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Observation 9cf9193c-2458-4ba9-8824-2009fecf09ea · outbound

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

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers

Reference 14

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Observation 5410ba47-856e-4f15-8a6d-d5bcc41f14d7 · outbound

This paper cites Learning implicit fields for generative shape modeling.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Learning implicit fields for generative shape modeling

Reference 15

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Observation 6235bd20-c13b-4600-9046-8286ffdd9dce · outbound

This paper cites Decor- gan: 3d shape detailization by conditional refinement.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Decor- gan: 3d shape detailization by conditional refinement

Reference 16

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Observation 7ccd9613-5c34-484a-9ebb-b1761db4510a · outbound

This paper cites Sdfusion: Multimodal 3d shape completion, reconstruction, and generation.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Sdfusion: Multimodal 3d shape completion, reconstruction, and generation

Reference 17

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Observation 7099cde4-99fc-4849-8dd7-7da74391c30f · outbound

This paper cites Objaverse-xl: A universe of 10m+ 3d objects.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Objaverse-xl: A universe of 10m+ 3d objects

Reference 18

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Observation f94b1905-d285-4a6e-9b12-734f07ec151f · outbound

This paper cites an unresolved cited work.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Unresolved cited work

Reference 19

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Observation 47fc3cc3-eeaf-40f5-a2d6-e3e79b4c7bd0 · outbound

This paper cites Generating natural im- ages with direct patch distributions matching.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Generating natural im- ages with direct patch distributions matching

Reference 20

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Observation e74866d3-79f0-4de4-a267-91ec079e4e6a · outbound

This paper cites Plenoxels: Radiance fields without neural networks.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Plenoxels: Radiance fields without neural networks

Reference 21

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Observation 68677bd4-df0e-4b6d-a43a-6884341e421f · outbound

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

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Get3d: A generative model of high quality 3d tex- tured shapes learned from images

Reference 22

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Observation 5d645d1d-b7b0-465f-adba-b95de950faa7 · outbound

This paper cites Generative adversarial networks.Com- munications of the ACM, 63(11):139–144, 2020.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Generative adversarial networks.Com- munications of the ACM, 63(11):139–144, 2020

Reference 23

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Observation 91890ec6-8316-48ca-9242-6c865d36a348 · outbound

This paper cites Drop the gan: In defense of patches nearest neighbors as single image generative models.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Drop the gan: In defense of patches nearest neighbors as single image generative models

Reference 24

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Observation f2bbf519-a331-437e-b8bb-06d1589c894c · outbound

This paper cites Generating Sequences With Recurrent Neural Networks.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Generating Sequences With Recurrent Neural Networks

Reference 25

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Observation 0a041efc-3d50-4b81-b845-b9ae6d6094c0 · outbound

This paper cites Algebraic point set surfaces.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Algebraic point set surfaces

Reference 26

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Observation f250d9b4-0984-42d6-a25b-b27fcf1fd2ad · outbound

This paper cites 3DGen: Triplane Latent Diffusion for Textured Mesh Generation.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion 3DGen: Triplane Latent Diffusion for Textured Mesh Generation

Reference 27

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Observation c0b01eac-3b77-4022-a965-26239acfc8b0 · outbound

This paper cites Diverse generation from a single video made possible.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Diverse generation from a single video made possible

Reference 28

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Observation c7b94ffa-c692-476a-8195-352214631983 · outbound

This paper cites Multiscale texture synthesis.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Multiscale texture synthesis

Reference 29

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Observation 6c8ad4a7-fb05-4534-8110-1dfc5a57c2ba · outbound

This paper cites Meshcnn: a network with an edge.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Meshcnn: a network with an edge

Reference 30

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Observation 3f68055a-bb8f-4438-807c-ba1e2e16ad11 · outbound

This paper cites Deep geometric texture synthesis.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Deep geometric texture synthesis

Reference 31

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Observation 6504c213-24af-40aa-b5ac-ed5c0c2b2813 · outbound

This paper cites Improved techniques for training single-image gans.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Improved techniques for training single-image gans

Reference 32

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Observation 26b522a6-100b-472a-8f49-3c9dbb077f95 · outbound

This paper cites Denoising dif- fusion probabilistic models.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Denoising dif- fusion probabilistic models

Reference 33

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Observation 12810415-42d0-466c-8bb4-d9c62a387d2f · outbound

This paper cites LRM: Large reconstruction model for single image to 3d.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion LRM: Large reconstruction model for single image to 3d

Reference 34

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Observation eb3a47bc-5e6a-4765-9ac4-4935e1369815 · outbound

This paper cites 2d gaussian splatting for geometrically ac- curate radiance fields.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion 2d gaussian splatting for geometrically ac- curate radiance fields

Reference 35

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Observation 3ea866f7-096f-4e29-a77a-3562f490c2bf · outbound

This paper cites Texgen: Text-guided 3d texture generation with multi-view sampling and resampling.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Texgen: Text-guided 3d texture generation with multi-view sampling and resampling

Reference 36

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Observation b23d5fe2-8568-4011-bb2f-ab14e6eb291c · outbound

This paper cites Fighting pillar.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Fighting pillar

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.635045Z digest=sha256:f3736be0cb8a908677db4a11e62947617b02c34c4f382d24e2a3d8f0ff00a236

Observation 54bb5a53-c38c-4486-8729-0c3d3e22b96c · outbound

This paper cites libigl, 2023.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion libigl, 2023

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.638660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.638660Z digest=sha256:df11b5aaec59b46d10363ae62ca8e8146850983480198825a5406250fbeeab9a

Observation 8e92d572-738e-40c0-8c72-8e847bbe92a4 · outbound

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

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Shap-E: Generating Conditional 3D Implicit Functions

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.642520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.642520Z digest=sha256:91ccffa69a76ea07152248aad361c253932471943968f4457fa1c4e79b4ce795

Observation f49504cb-0298-40c7-a04e-bc3a90e3f987 · outbound

This paper cites Scal- ing up gans for text-to-image synthesis.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Scal- ing up gans for text-to-image synthesis

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.646624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.646624Z digest=sha256:ca1d810156f28cb8881669483c002fd8be714c8c6ab40a57bf07a00eca6aa0a9

Observation e7f0d53e-7418-47f3-9781-6fe162ada1aa · outbound

This paper cites 3ingan: Learning a 3d generative model from images of a self-similar scene.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion 3ingan: Learning a 3d generative model from images of a self-similar scene

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.650391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.650391Z digest=sha256:6ec5ffd810ce2333af2ddf7a0255e2a2cd37ede3a3dbc9b84785545035922c08

Observation c4dc094c-cc75-4cfc-9505-7cdccc8c6077 · outbound

This paper cites Neural 3d mesh renderer.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Neural 3d mesh renderer

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.654644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.654644Z digest=sha256:f953d958b43b13a84cdad6f02bf4cb50db2c937a94ae98bf6e759e9d724c482d

Observation c33e9916-9d45-4d67-be0f-37ae44bbc7cb · outbound

This paper cites Screened poisson surface reconstruction.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Screened poisson surface reconstruction

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.658266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.658266Z digest=sha256:9a649b0a2dface966fdf4e9bcaf3f83dc267bb50c3430884ed25aa67b6a1ad1b

Observation 3dcfcb69-36aa-4f5f-8dbf-29fc26255e02 · outbound

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

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion 3d gaussian splatting for real-time radiance field rendering

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.661960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.661960Z digest=sha256:5df2fc47578bea698902ffa3cd708b05359a82b085e77f4abf378d50d31732ce

Observation 95b051c9-9881-408a-af9f-b70e99582188 · outbound

This paper cites An introduction to variational autoencoders.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion An introduction to variational autoencoders

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.665861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.665861Z digest=sha256:175c73d596cad5413262d9e7a6318eac2393972e6ee2d6a93e3e20b74601bea7

Observation d940b2be-4520-43b8-a57c-a9fdfedc06ed · outbound

This paper cites Sinddm: A single image denoising diffusion model.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Sinddm: A single image denoising diffusion model

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.669552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.669552Z digest=sha256:a9555538592801f98ea0c0b4a9bb0105adde07491782ba888c3672aaedea9b05

Observation 1bcf8cfc-27b0-4036-b2ee-f1498560b268 · outbound

This paper cites Akropolis.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Akropolis

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.673188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.673188Z digest=sha256:9859c156a85e465c91758a0c28bc78209a7417122e40840270c2ba09c3e9b705

Observation f35a109c-c124-4b63-8e22-c075514666bc · outbound

This paper cites Srdiff: Single image super-resolution with diffusion probabilistic models.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Srdiff: Single image super-resolution with diffusion probabilistic models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.676681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.676681Z digest=sha256:678f4b5a45e4bdf5ef75cb0b49d85a5805bef735251634c37768ecfbc22f3451

Observation 32f97a6f-3efe-48f3-8484-1f3dc97f966b · outbound

This paper cites Instant3d: Fast text-to-3d with sparse-view generation and large reconstruction model.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Instant3d: Fast text-to-3d with sparse-view generation and large reconstruction model

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.680053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.680053Z digest=sha256:e6e1ff1b2c572589c0a7803403ec753ad4fb97f70098c151e9a38a5db5ed6b6f

Observation bb898588-9175-41be-b72e-fc568a00d38f · outbound

This paper cites Patch-based 3d natural scene generation from a single ex- ample.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Patch-based 3d natural scene generation from a single ex- ample

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.683953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.683953Z digest=sha256:8bd4a62ee2c4d8d73ac29f804e0d4d54443c7e80ccce74139497367142195e77

Observation 22c6a55e-a6ec-4d6d-aa24-05d3154317d3 · outbound

This paper cites Sweet- dreamer: Aligning geometric priors in 2d diffusion for con- sistent text-to-3d.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Sweet- dreamer: Aligning geometric priors in 2d diffusion for con- sistent text-to-3d

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.687414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.687414Z digest=sha256:e4adc279e4444c8114b6d71769859af2bf7517baa3dc0c2b8aa36f054087cc38

Observation c2a7ef04-7a82-4801-a49f-dbe4d52e12cf · outbound

This paper cites Luciddreamer: Towards high- fidelity text-to-3d generation via interval score matching.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Luciddreamer: Towards high- fidelity text-to-3d generation via interval score matching

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.691036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.691036Z digest=sha256:abbddb558e63d717d14f56648ea54162f69cd0288ec1f22c63468fd2c3b6d58a

Observation a2c1c665-6950-45e9-abf8-bddf7efdc817 · outbound

This paper cites Magic3d: High- resolution text-to-3d content creation.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Magic3d: High- resolution text-to-3d content creation

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.694673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.694673Z digest=sha256:a59ab3b22f7f0242013491cedb2deb916c58e900a6f456f2a0db34fb5aa88b7c

Observation 5b12c6d5-c24c-4cf6-b42e-2a7d46933bcc · outbound

This paper cites One-2-3-45: Any sin- gle image to 3d mesh in 45 seconds without per-shape opti- mization.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion One-2-3-45: Any sin- gle image to 3d mesh in 45 seconds without per-shape opti- mization

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.878151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.698337Z digest=sha256:d88757b8ab3988a7b99ad662c08b87fcc1c14d52c6bd1008efb139fd95204ae5

Observation ee222eeb-2c2d-4147-bce9-89e7e979a603 · outbound

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

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Zero-1-to-3: Zero-shot one image to 3d object

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.865714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.701768Z digest=sha256:f626f060b3ea1bffb79bc4b1d530d1b5bc751c130dd83c1f6332de02977db62f

Observation 88916195-4b41-47bb-af2b-7a1524bcf6c8 · outbound

This paper cites Soft rasterizer: A differentiable renderer for image-based 3d reasoning.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Soft rasterizer: A differentiable renderer for image-based 3d reasoning

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.853421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.705343Z digest=sha256:8ac1b8b079321cfd9c225e5f1beb223bae880f88ccb40acdc64ca76ebcb014f0

Observation 28121c65-536a-42e9-bd7e-415df41397f1 · outbound

This paper cites Syncdreamer: Generating multiview-consistent images from a single-view image.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Syncdreamer: Generating multiview-consistent images from a single-view image

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.840735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.709068Z digest=sha256:581c73b8497d3d7a7034dde25315ee05381033625cb053c6061e088fb3814ffa

Observation bd68a678-49b4-4c8c-afa1-0d25dc78c2b7 · outbound

This paper cites Neural volumes: learning dynamic renderable volumes from im- ages.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Neural volumes: learning dynamic renderable volumes from im- ages

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.827295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.712567Z digest=sha256:88e3177bf5f2b432232d8048cc8c2263b84e29869eeed87ac31086c892c55376

Observation f19bf365-8a5a-4758-aa38-dda046cb168b · outbound

This paper cites Wonder3d: Single image to 3d using cross-domain diffusion.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Wonder3d: Single image to 3d using cross-domain diffusion

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.716008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.716008Z digest=sha256:255f6ab8d1ad3dc636a4eff5b61e2034c77255900398a51cec23022b2e2eeefe

Observation 2649353c-e8cc-4744-80fe-a25ff447da32 · outbound

This paper cites Marching cubes: A high resolution 3d surface construction algorithm.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Marching cubes: A high resolution 3d surface construction algorithm

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.807175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.719682Z digest=sha256:ecc929e5b58f0c456c73e41b9d6b5d2504dabe0dc14997b5dd009be93b6d839a

Observation 391bff2b-74ab-4aa9-bc78-7316edcb9830 · outbound

This paper cites Score Distillation via Reparametrized DDIM.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Score Distillation via Reparametrized DDIM

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.723091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.723091Z digest=sha256:73b442e9581af82743ab43ed3975ff963c9fc63e05a7a3130ca890530af10944

Observation 10352775-2cfd-4c81-b405-17a328be6f24 · outbound

This paper cites Diffusion probabilistic mod- els for 3d point cloud generation.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Diffusion probabilistic mod- els for 3d point cloud generation

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.793896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.726849Z digest=sha256:91e2917e0387cfb1b2b17c849f1e1223f783191920c7f0d0f13f23dd7bb8e7a0

Observation d75a7832-b62b-4d69-83f8-0350472f8009 · outbound

This paper cites Magnific ai: Accelerating scientific research.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Magnific ai: Accelerating scientific research

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.779295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.730237Z digest=sha256:da682430d539ea63f0ec851282a139ff398153a7d91d9d118df4ed1720f70105

Observation 3596204c-ae3b-4a9a-bf01-3a85f64a9a30 · outbound

This paper cites V oroMesh: Learning Wa- tertight Surface Meshes with V oronoi Diagrams.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion V oroMesh: Learning Wa- tertight Surface Meshes with V oronoi Diagrams

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.766067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.733609Z digest=sha256:160abdadbdf7c9a121fc8ba692a2f9408054f6a34c0ff4eb2d8ae2adcd0c1ccc

Observation f01bcf91-0e02-49cb-b96f-cfb8dddf49b6 · outbound

This paper cites PoNQ: A Neural QEM-Based Mesh Representation.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion PoNQ: A Neural QEM-Based Mesh Representation

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.753844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.736953Z digest=sha256:2b53654fb692c604e3d998a938f10b4b131b656531ce942a0e1399c8dd93d1c3

Observation eb4b37ce-b0f3-4262-b856-12ffcb6baee2 · outbound

This paper cites Occupancy net- works: Learning 3d reconstruction in function space.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Occupancy net- works: Learning 3d reconstruction in function space

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.740498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.740730Z digest=sha256:291e3a07e10071f141f24f52f8c44f0244fb3244c67d0f9b5dfa417079650921

Observation ec112e76-b311-46e5-9a6d-c1a155a90bcb · outbound

This paper cites Latent-nerf for shape-guided gen- eration of 3d shapes and textures.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Latent-nerf for shape-guided gen- eration of 3d shapes and textures

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.726768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.744293Z digest=sha256:b9d4dd564889d884d5807d701bb19a54cdf1e04e5e2202803b52d6adc76e0f7b

Observation aef15635-038c-45d9-b24b-4e6fe6df4dec · outbound

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

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Nerf: Representing scenes as neural radiance fields for view syn- thesis

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.747884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.747884Z digest=sha256:7f4f88a137668b9c45d39e3345993150cbd47ab43e1e1c906321a0971a1cff2f

Observation 516a56d8-0b0a-4cc1-abec-89e253457f39 · outbound

This paper cites Mitchel, Carlos Esteves, and Ameesh Makadia.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Mitchel, Carlos Esteves, and Ameesh Makadia

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.706771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.751437Z digest=sha256:60295ca96183271b754e4db503f7a714f2a3231645963fc6aef2de755a74d590

Observation 222c7b34-6f85-4203-bae5-738e869e7661 · outbound

This paper cites Polygen: An autoregressive generative model of 3d meshes.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Polygen: An autoregressive generative model of 3d meshes

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.694300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.755490Z digest=sha256:7c91ae8168fe2bd12223cfae6f54ace9599ab6f1f81d718be4b5d2cdaf660284

Observation 0dc984be-d333-48db-b1cf-2cbae98cec1b · outbound

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

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Point-E: A System for Generating 3D Point Clouds from Complex Prompts

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.759018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.759018Z digest=sha256:774c2ce9cc9c1ecc1e24c50e389ae7971be962fed2a8fd195652004deff8cc21

Observation 3c3aa33b-ae5e-447c-84d0-59d25bed9c4b · outbound

This paper cites Sinfusion: training diffusion models on a single image or video.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Sinfusion: training diffusion models on a single image or video

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.683602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.762527Z digest=sha256:d486bc287d753480039b85a94ae08d32df06b212e83123b8e20f2e2046d56aaa

Observation f8fcf937-e69f-43b4-b9c3-1fd41254f22d · outbound

This paper cites Self-organising textures.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Self-organising textures

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.672210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.765989Z digest=sha256:2f487ad3fe9784b0560ab664c3589d9c3686b37da6ecc7cf65500ec1728bbaf6

Observation 235b4abd-96a2-42d2-9fcd-e4dcb8c96dcc · outbound

This paper cites Deepsdf: Learning continuous signed distance functions for shape represen- tation.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Deepsdf: Learning continuous signed distance functions for shape represen- tation

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.660363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.769724Z digest=sha256:a249b15a61c5f5bb53cc8b54575ba24e2aa2169d6d8027ba2c38272ba84d3d89

Observation 900432fe-bf97-4a19-bbc9-736e4faf7017 · outbound

This paper cites PyTorch: An Im- perative Style, High-Performance Deep Learning Library,.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion PyTorch: An Im- perative Style, High-Performance Deep Learning Library,

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.648595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.773157Z digest=sha256:53f93ae92b9c3bfe875aa696c7e5fe90c9d08786e1b19d06845a773263fb616f

Observation 4a21b1d9-583f-4b76-a74e-73f1bf922cbd · outbound

This paper cites Barron, and Ben Milden- hall.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Barron, and Ben Milden- hall

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.636555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.780669Z digest=sha256:36bc3643c800675ca34eda9c5374d0e664639686d54c91d60c91a66345a749c9

Observation 3ee9a81b-4eaa-4838-a54b-cd9704eb296d · outbound

This paper cites Dynamic Point Fields.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Dynamic Point Fields

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.624578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.784188Z digest=sha256:ad01db9004f2d60715d39c134e2270dd240169f6352ae1b507577c1ade051fa5

Observation 0cd4ffc1-0c21-4fab-b4f4-f4f4f4751d21 · outbound

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

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.612980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.787656Z digest=sha256:660c928725b1ef65b4cf29bba9adc206829c315d716214a35fa99a8f3918d94f

Observation 9a40d925-4162-41a4-88a6-deab41255693 · outbound

This paper cites Richdreamer: A gen- eralizable normal-depth diffusion model for detail richness in text-to-3d.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Richdreamer: A gen- eralizable normal-depth diffusion model for detail richness in text-to-3d

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.600010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.791054Z digest=sha256:8028f8434cd072716fea5bfd1468ab35de82da09705104ec80b826507ac31bfd

Observation 91e60098-56fb-45b2-b2c2-d0410a2e6095 · outbound

This paper cites Accelerating 3D Deep Learning with PyTorch3D.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Accelerating 3D Deep Learning with PyTorch3D

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.794587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.794587Z digest=sha256:87bc835f5f73ea53b606f1ca6af4023165cc55d913ca808c4002df4ed21799ee

Observation 14d766c0-513d-45dd-aea8-3627e6d3abe4 · outbound

This paper cites Xcube: Large-scale 3d generative modeling using sparse voxel hierarchies.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Xcube: Large-scale 3d generative modeling using sparse voxel hierarchies

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.587739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.798452Z digest=sha256:8d2f0fa51e4a12df34491d32419e4b2582632a8419bfbef5696852b79535d075

Observation 28d81c05-1369-41d5-9058-33ea8c45d073 · outbound

This paper cites Scube: Instant large- scale scene reconstruction using voxsplats.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Scube: Instant large- scale scene reconstruction using voxsplats

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.576053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.801842Z digest=sha256:acbf536fa8a725c5dee495409a279d39fc741403c6ffdc9c8292c8d6055cd3de

Observation 63ece84b-3ce7-4354-850e-04ebc7abbd98 · outbound

This paper cites Variational infer- ence with normalizing flows.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Variational infer- ence with normalizing flows

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.563756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.805273Z digest=sha256:ba10a290a3af11c6c4b31a11e33735a77ce555d64f6aa7ed6e40f7402c97c2b5

Observation a96efd09-68bf-47ad-96f4-c0d6f188afbc · outbound

This paper cites Texture: Text-guided texturing of 3d shapes.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Texture: Text-guided texturing of 3d shapes

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.552045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.808813Z digest=sha256:08de3e3b9f50b79bd56e1c5bfcbffa7b31420b98a178d950e37973ebb4dcc79e

Observation b41f0b94-a651-4c07-834a-44343be728c6 · outbound

This paper cites Seamlessgan: Self-supervised synthesis of tileable texture maps.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Seamlessgan: Self-supervised synthesis of tileable texture maps

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.539653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.812261Z digest=sha256:dddb87ffb04998d55ac76227a6375961cce9a1512556b4d4113eb5db8d9fe3a4

Observation e63f8e8b-5ab1-4f3e-b06b-be8030282767 · outbound

This paper cites Graf: Generative radiance fields for 3d-aware im- age synthesis.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Graf: Generative radiance fields for 3d-aware im- age synthesis

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.815703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.815703Z digest=sha256:7c38712dc010d61e3634d847951ed989165338c7a917ad50c721f0905cab0352

Observation 7ead0491-a007-43fe-9d07-4e6d34984ff9 · outbound

This paper cites Sin- gan: Learning a generative model from a single natural im- age.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Sin- gan: Learning a generative model from a single natural im- age

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.520357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.819181Z digest=sha256:e8356616f70571980b320e18f2e4a67dce2d836b3d2e0efae0399269a08f4c2b

Observation 5bcd04f0-0cf7-4100-a757-d8507b12ae5a · outbound

This paper cites MVDream: Multi-view diffusion for 3d generation.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion MVDream: Multi-view diffusion for 3d generation

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.507985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.822578Z digest=sha256:87f19c0235426b5b846568568c1cf13f95cb6becf13ffad1fbb8c5085f7dc2d1

Observation 1c3a1e20-ef95-419c-bb82-f18267758144 · outbound

This paper cites Ingan: Capturing and retargeting the” dna” of a natural im- age.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Ingan: Capturing and retargeting the” dna” of a natural im- age

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.496488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.826488Z digest=sha256:d42afc291f9b0a683439a9d8c3d10eb130468dbd31a0f3fead614baf5fa7cb6b

Observation 979de030-c453-4289-8603-0b35d5d78404 · outbound

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

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Meshgpt: Generating triangle meshes with decoder-only transformers

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.484256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.829851Z digest=sha256:a7cc40d23ad14b00c16e8de26cc20e261e3ad1fe1233328c154745fb349a4461

Observation 846b3f3f-bb9b-4dcd-aa97-614f0fdd9b70 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Deep unsupervised learning using nonequilibrium thermodynamics

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.833556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.833556Z digest=sha256:b43ff4a540f36ba16d02a7aa7a8a54c3dada191fc690f92dd8ce428dc1efc4dd

Observation 8c853e8b-0199-4291-a2c6-c3bc9d5455ec · outbound

This paper cites Singraf: Learning a 3d generative radiance field for a single scene.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Singraf: Learning a 3d generative radiance field for a single scene

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.464788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.837302Z digest=sha256:b09ca76c598ed4a5552ae375fffa971330ed7900a8e3cdd0f8dbe8a28cf0755d

Observation 1e508e18-5434-4c45-9865-4ef9fe68c582 · outbound

This paper cites Denois- ing diffusion implicit models.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Denois- ing diffusion implicit models

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.840954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.840954Z digest=sha256:6ba336e7be586de23dea3cf62cd3fe0af2dcbf581b3978c09ce65de5a0974e69

Observation 138f3d1c-1cb1-454f-8f11-b24b0de0e6c7 · outbound

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

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Lgm: Large multi- view gaussian model for high-resolution 3d content cre- ation

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.445464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.844438Z digest=sha256:f7bac5529d00685184c7ba7cc7cd501cdf7370f069307240ca7a5d87ae9a7325

Observation bd3d783a-1a83-46cc-9e26-fa235a7f0931 · outbound

This paper cites Canyon landscape.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Canyon landscape

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.433648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.847917Z digest=sha256:bca9a8659b0466852237fef7a3a2a08233b5f32117a35066e3f919214b0179c9

Observation 8ac0049e-8278-4b09-8eb8-40ee007c773e · outbound

This paper cites Lion: Latent point diffu- sion models for 3d shape generation.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Lion: Latent point diffu- sion models for 3d shape generation

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.851593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.851593Z digest=sha256:69fc67f4577c4dba0e6c2c2e0040bec5f6d297abe2eee06823abf486f065c50b

Observation 0089c31f-8c48-4f0f-a448-6e9b789bd20c · outbound

This paper cites Pixel recurrent neural networks.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Pixel recurrent neural networks

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.413687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.855206Z digest=sha256:4ddded025d9eb1e07371d8b24f4493fcc6182b9354f49e0510913dd97e7cd64b

Observation a3aa09bd-c091-4e87-928e-e3cd14968394 · outbound

This paper cites Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.858688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.858688Z digest=sha256:269cf549eba806069bf31d1537b2041e50db38c0af9694b657a13740fc56d247

Observation b9cc6320-724e-463f-9352-a7ec8d350bc0 · outbound

This paper cites NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction

Reference 99

Resolution
unresolved
no resolver link, observed 2026-08-09T13:04:50.862057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:04:50.862057Z digest=sha256:2e31ba563386accc58332c90ccca1498d7b007a7f3590aee64bc15654d7af080

Observation 5a9727a7-00db-45d3-a639-285cab2693ae · outbound

This paper cites PF-LRM: Pose-free large reconstruction model for joint pose and shape prediction.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion PF-LRM: Pose-free large reconstruction model for joint pose and shape prediction

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:04:51.393609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-09T13:04:50.865640Z digest=sha256:1065f6e8f7eb6f29855fce8c1d56e031f2f8275bb1ae9af831c0ad28e9fbeab8

Pith citing papers

No inbound Pith citation observations are available.