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Paper Citation Record · LEDGER

MVBoost: Boost 3D Reconstruction with Multi-View Refinement

As of 13 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2411.17772.

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

pith.paper-citation-record.v1
2411.17772 v2

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:26:14.884114Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

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  • verified fuzzy18
  • unresolved21
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3705bc26-39f0-4df7-9525-162b6d16a8c6 · outbound

This paper cites Multi-garment net: Learning to dress 3d people from images.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Multi-garment net: Learning to dress 3d people from images

Reference 1

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Observation c773cdc1-45fe-468e-b3f7-7ac1da77832f · outbound

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

MVBoost: Boost 3D Reconstruction with Multi-View Refinement ShapeNet: An Information-Rich 3D Model Repository

Reference 2

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Observation 889a7f71-dff8-4ff0-91d3-4c2282c884c4 · outbound

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

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Objaverse: A universe of annotated 3d objects

Reference 3

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Observation b39fd364-c259-4011-94e4-5753c2fbf29e · outbound

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

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Objaverse-xl: A universe of 10m+ 3d objects

Reference 4

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Observation c2b40431-d631-48a2-91ec-9a5815066f24 · outbound

This paper cites Diffusion models beat gans on image synthesis.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Diffusion models beat gans on image synthesis

Reference 5

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source=pdf_text observed=2026-08-12T12:26:14.704637Z digest=sha256:bc499e6d7a4fc7ed8d3c6b48ed27a366015ab887723f9a6fde285514984caddd

Observation e6ad8f03-a5af-41bb-b1d6-a97c20881a75 · outbound

This paper cites McHugh, and Vincent Vanhoucke.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement McHugh, and Vincent Vanhoucke

Reference 6

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 4a3fbe9a-909a-4908-a96f-a77afd0d5311 · outbound

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

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Vfusion3d: Learning scalable 3d generative models from video diffusion models

Reference 7

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Observation 4550d6d9-0b88-4428-a323-7732a1e3b7db · outbound

This paper cites Gancraft: Unsupervised 3d neural rendering of minecraft worlds.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Gancraft: Unsupervised 3d neural rendering of minecraft worlds

Reference 8

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Observation 43edd4e4-c17e-419c-8a06-2e9e720630ff · outbound

This paper cites Denoising dif- fusion probabilistic models.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Denoising dif- fusion probabilistic models

Reference 9

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Observation 5e35bcb3-8e81-4048-b89e-e5805372a172 · outbound

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

MVBoost: Boost 3D Reconstruction with Multi-View Refinement LRM: Large reconstruction model for single image to 3d

Reference 10

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Observation 6f2c683f-e36d-4de1-bb4d-ae3606b296e7 · outbound

This paper cites LoRA: Low-rank adaptation of large language models.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement LoRA: Low-rank adaptation of large language models

Reference 11

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Observation 6a74cd38-7a41-48fc-8a8f-32cb196e2533 · outbound

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

MVBoost: Boost 3D Reconstruction with Multi-View Refinement 3d gaussian splatting for real-time radiance field rendering

Reference 12

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Observation 5bff0b1e-18ef-46d0-9fb1-41e85702f80e · outbound

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

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Instant3d: Fast text-to-3d with sparse-view generation and large reconstruction model

Reference 13

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Observation 376efcbc-84f3-47d0-9379-986d8cdfa9df · outbound

This paper cites Era3D: High-Resolution Multiview Diffusion using Efficient Row-wise Attention.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Era3D: High-Resolution Multiview Diffusion using Efficient Row-wise Attention

Reference 14

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Observation c2b5bcb9-cea9-4d76-ab10-1fd0629379fc · outbound

This paper cites High-fidelity clothed avatar reconstruction from a single image.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement High-fidelity clothed avatar reconstruction from a single image

Reference 15

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Observation 73106855-cfe9-476b-8629-dc410d28e2f3 · outbound

This paper cites One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View Generation and 3D Diffusion.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View Generation and 3D Diffusion

Reference 16

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Observation ab8234bf-f18c-4b96-ac35-35371d0d1f59 · outbound

This paper cites One-2-3-45: Any single image to 3d mesh in 45 seconds without per-shape optimiza- tion.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement One-2-3-45: Any single image to 3d mesh in 45 seconds without per-shape optimiza- tion

Reference 17

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Observation 9972a179-7766-4a4a-b19c-66128e2e6d86 · outbound

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

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Zero-1-to- 3: Zero-shot one image to 3d object

Reference 18

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Observation ad24bd09-e250-4d89-a586-885d032a2205 · outbound

This paper cites Syncdreamer: Gen- erating multiview-consistent images from a single-view im- age.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Syncdreamer: Gen- erating multiview-consistent images from a single-view im- age

Reference 19

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 69751d73-ab41-45c3-881d-c9929959193b · outbound

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

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Wonder3d: Single image to 3d using cross-domain diffusion

Reference 20

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Observation 1f57ed15-99e0-4d0c-b5fb-3fd0c3ab4cb4 · outbound

This paper cites Scaledreamer: Scalable text-to- 3d synthesis with asynchronous score distillation.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Scaledreamer: Scalable text-to- 3d synthesis with asynchronous score distillation

Reference 21

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Observation fb2b6e05-9e16-45f1-ab9e-8577da8962ac · outbound

This paper cites Self-supervised 3d shape and viewpoint estimation from single images for robotics.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Self-supervised 3d shape and viewpoint estimation from single images for robotics

Reference 22

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Observation cadf6c55-305a-4974-8ede-ba4384541d7b · outbound

This paper cites Srinivasan, Matthew Tancik, Jonathan T.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Srinivasan, Matthew Tancik, Jonathan T

Reference 23

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Observation 274b6113-f33f-4454-989f-620135a87b69 · outbound

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

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Nerf: Representing scenes as neural radiance fields for view syn- thesis

Reference 24

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Observation 4a4c8bd9-f6ac-4462-ba8e-a12cf4b3a760 · outbound

This paper cites Barron, and Ben Milden- hall.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Barron, and Ben Milden- hall

Reference 25

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Observation 2d30f41b-3670-4e1a-8b5f-6c6db5ff597c · outbound

This paper cites Flexible isosurface extraction for gradient-based mesh optimization.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Flexible isosurface extraction for gradient-based mesh optimization

Reference 26

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Observation 67c23eea-d251-4a8e-8e0d-c515b9a5afa3 · outbound

This paper cites Zero123++: a single image to consistent multi-view dif- fusion base model, 2023.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Zero123++: a single image to consistent multi-view dif- fusion base model, 2023

Reference 27

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Observation 59db63d5-9f92-4ce9-aa1c-b37a588925e4 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Deep unsupervised learning using nonequilibrium thermodynamics

Reference 28

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Observation cf3d180c-2a51-46ee-b48c-8517bc27ca01 · outbound

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

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Lgm: Large multi-view gaussian model for high-resolution 3d content creation

Reference 29

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raw_fallback, observed 2026-08-12T12:26:15.152707Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation b30c68c3-8159-4d2d-bd41-27c853adea0e · outbound

This paper cites Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation

Reference 30

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Observation 0c4ef78e-265d-420f-aed0-f4b9cdd33755 · outbound

This paper cites Imagedream: Image-prompt multi-view diffusion for 3d generation, 2023.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Imagedream: Image-prompt multi-view diffusion for 3d generation, 2023

Reference 31

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source=pdf_text observed=2026-08-12T12:26:14.840061Z digest=sha256:2fb8ae47dcc3ae5c597a320b9fd0eebb86c5aa1828f04a5745de7b32c35df928

Observation a84da8f3-4158-4118-b582-48edfb52d1fb · outbound

This paper cites Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion

Reference 32

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source=pdf_text observed=2026-08-12T12:26:14.845087Z digest=sha256:6ff7f20f73217aaa380b1426adba5d49b8f08e594b2a47dd210f705f45dc7a5d

Observation 1c12a0b9-3c31-494f-aba6-96ee68fed828 · outbound

This paper cites CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Model.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Model

Reference 33

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source=pdf_text observed=2026-08-12T12:26:14.850124Z digest=sha256:22805d9364ae218c436835caa171611b4c45fb00fab427e52a4672296ec3ba19

Observation f46d4698-cc0f-4c52-9c12-0339e9183fe7 · outbound

This paper cites InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models

Reference 34

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source=pdf_text observed=2026-08-12T12:26:14.855994Z digest=sha256:29474dac0fe24988b32f0e9f4baa36a9cb1ccf026cb0d62fb13e119e0c305cc1

Observation a1245344-bcfc-498b-b167-474a033e475b · outbound

This paper cites GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation

Reference 35

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Unavailable: canonical work link unavailable.

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Observation 3e4355f0-efca-4a10-9669-c38b52be7316 · outbound

This paper cites Triplane Meets Gaussian Splatting: Fast and Generalizable Single-View 3D Reconstruction with Transformers.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement Triplane Meets Gaussian Splatting: Fast and Generalizable Single-View 3D Reconstruction with Transformers

Reference 36

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unresolved
no resolver link, observed 2026-08-12T12:26:14.867041Z

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Observation 9edbe361-c638-45e0-97ea-814845175e40 · outbound

This paper cites In our training process, we use a fixed set of six viewpoints (front, front right, right, back, left, front left) for supervision.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement In our training process, we use a fixed set of six viewpoints (front, front right, right, back, left, front left) for supervision

Reference 37

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verified fuzzy
raw_fallback, observed 2026-08-12T12:26:15.103903Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7395ee34-3876-4933-b382-53f634e1785f · outbound

This paper cites The al- gorithm details are presented in Algorithm 1.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement The al- gorithm details are presented in Algorithm 1

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-12T12:26:15.085958Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation c90dc2cd-8e52-41bb-b151-e50cca6e9444 · outbound

This paper cites To further illustrate the versatility of our approach, we boost OpenLRM with multi-view refinement.

MVBoost: Boost 3D Reconstruction with Multi-View Refinement To further illustrate the versatility of our approach, we boost OpenLRM with multi-view refinement

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:26:15.067397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Pith citing papers

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