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Paper Citation Record · LEDGER

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention

As of 22 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2412.00731.

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

pith.paper-citation-record.v1
2412.00731 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:06:58.305988Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

32 of 32 outbound references displayed

  • verified exact10
  • verified fuzzy14
  • unresolved7
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9f94f679-c9f9-42d4-9385-3d4db7d241d8 · outbound

This paper cites Efficient 3D Object Reconstruction using Visual Transformers.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Efficient 3D Object Reconstruction using Visual Transformers

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-12T05:06:58.409842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 6c222bc4-5106-4c54-be44-0a08f16d2cd9 · outbound

This paper cites Attentional Aggregation of Deep Feature Sets for Multi-view 3D Reconstruction.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Attentional Aggregation of Deep Feature Sets for Multi-view 3D Reconstruction

Reference 2

Resolution
verified exact
doi, observed 2026-08-12T05:06:58.388801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 434fff97-7e61-4599-855d-0059dbad9d8c · outbound

This paper cites 3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention 3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction

Reference 3

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 99530d7b-e3ca-4db1-8b49-73794e0ff64a · outbound

This paper cites Learning a Probabilistic Latent Space of Object Shapes via 3D Generative- Adversarial Modeling.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Learning a Probabilistic Latent Space of Object Shapes via 3D Generative- Adversarial Modeling

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 1aa18327-c956-478a-a97f-b20c194fd4ca · outbound

This paper cites Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images

Reference 5

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 2733037a-e1b3-4179-8aee-029eaa220caf · outbound

This paper cites U-Net: Convolutional Net- works for Biomedical Image Segmentation.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention U-Net: Convolutional Net- works for Biomedical Image Segmentation

Reference 6

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 42ffa0bd-5aa2-4b43-9516-2114139c8e20 · outbound

This paper cites Large- Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Large- Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 5378b9c5-8cf1-4ce0-8ded-869478d0ab49 · outbound

This paper cites Beyond PASCAL:A benchmark for 3D object detection in the wild. In W ACV 2014.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Beyond PASCAL:A benchmark for 3D object detection in the wild. In W ACV 2014

Reference 8

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 25d8efd5-233f-4ed8-89f3-dbb00b6f07e1 · outbound

This paper cites A Point Set Generation Network for 3D Object Reconstruction from a Single Image.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention A Point Set Generation Network for 3D Object Reconstruction from a Single Image

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 30c0f9dd-cfa9-4795-8305-c25df215c973 · outbound

This paper cites Dense 3D Point Cloud Reconstruction Using a Deep Pyramid Network.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Dense 3D Point Cloud Reconstruction Using a Deep Pyramid Network

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3cd5dd4b-3bc1-4472-9df6-b016aa329719 · outbound

This paper cites Learning a Multi-View Stereo Machine.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Learning a Multi-View Stereo Machine

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 146572a3-3347-4365-b6b4-21bc20436a25 · outbound

This paper cites MarrNet : 3 D Shape Reconstruction via 2 . 5 D Sketches.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention MarrNet : 3 D Shape Reconstruction via 2 . 5 D Sketches

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation c0256fb6-0154-45bf-a9a9-573373258bf3 · outbound

This paper cites DeepMVS: Learning Multi-view Stereopsis.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention DeepMVS: Learning Multi-view Stereopsis

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:06:58.808098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation c1d5d5fd-873e-4ab7-90fa-9ab3f4cba22f · outbound

This paper cites Past, Present, and Future of Simultaneous Localization and Mapping: To- wards the Robust-Perception Age.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Past, Present, and Future of Simultaneous Localization and Mapping: To- wards the Robust-Perception Age

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d7963b78-c4f2-4c7d-8712-076ece7ba99e · outbound

This paper cites A Survey of Structure from Motion.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention A Survey of Structure from Motion

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 0c47a234-e6e5-4764-9600-7af9991a7063 · outbound

This paper cites 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annota- tion.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annota- tion

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation c1d97388-deb9-42a9-910a-5565aa2d1cc6 · outbound

This paper cites Deep residual learning for image recognition.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Deep residual learning for image recognition

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d2915f09-092c-4ee1-be3e-d80d4043a3b9 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 839bd9e7-154e-4a99-9e9d-79cd30c0bfee · outbound

This paper cites International Conference on Neural Information Processing Systems.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention International Conference on Neural Information Processing Systems

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation c9f553f9-bd2c-48d5-b947-9f0d6e9f0223 · outbound

This paper cites Attention Is All You Need.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Attention Is All You Need

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-12T05:06:58.242946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7c9860e6-7b85-4006-bd3b-31e60039c9b4 · outbound

This paper cites an unresolved cited work.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Unresolved cited work

Reference 21

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 9a255d3a-cf9f-4999-aedf-6e8293ff315d · outbound

This paper cites an unresolved cited work.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Unresolved cited work

Reference 22

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a54f24bb-a1a6-4799-a9f5-408e6429c72c · outbound

This paper cites Improving Computed Tomography (CT) Reconstruction via 3D Shape Induction.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Improving Computed Tomography (CT) Reconstruction via 3D Shape Induction

Reference 23

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d2efa8ea-7b9d-4391-9d79-8cd26a1a0cfe · outbound

This paper cites 3D Building Reconstruction from Monocular Remote Sensing Images with Multi-level Supervisions.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention 3D Building Reconstruction from Monocular Remote Sensing Images with Multi-level Supervisions

Reference 24

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ae6c4fe1-0144-4661-b78e-513d81ba3ccb · outbound

This paper cites Zioga, A.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Zioga, A

Reference 25

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 026fdfde-5ac9-440c-9f3b-9a2517ee4104 · outbound

This paper cites Order Matters: Sequence to sequence for sets.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Order Matters: Sequence to sequence for sets

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-12T05:06:58.277493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 35e7b0c6-28e0-47f0-b0dc-8b339f22df61 · outbound

This paper cites Lowe, Distinctive Image Features from Scale-Invariant Keypoints , Inter- national Journal of Computer Vision, vol.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Lowe, Distinctive Image Features from Scale-Invariant Keypoints , Inter- national Journal of Computer Vision, vol

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-12T05:06:58.282479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1a98d457-36b7-48b4-9637-b59fafc213e9 · outbound

This paper cites 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-12T05:06:58.287267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:06:58.287267Z digest=sha256:960b5246d6d9f061611115f5614c00ec75dd7814c5324d5f925d30e2334652cb

Observation 719ee7bd-2034-40a3-a813-38166109e968 · outbound

This paper cites Hwang and W.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Hwang and W

Reference 30

Resolution
parse uncertain
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 9a8f344f-93cb-4efa-a12a-c23314db7d24 · outbound

This paper cites On the difficulty of training Recurrent Neural Networks.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention On the difficulty of training Recurrent Neural Networks

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T05:06:58.296634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9a47890e-a16c-4df4-9323-c5f9812406ed · outbound

This paper cites Multi-view 3D Reconstruction with Transformer.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention Multi-view 3D Reconstruction with Transformer

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-12T05:06:58.452990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation e250712d-1155-4f77-b7c8-c99d3da91b12 · outbound

This paper cites SilNet : Single- and Multi-View Reconstruction by Learning from Silhouettes.

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention SilNet : Single- and Multi-View Reconstruction by Learning from Silhouettes

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-12T05:06:58.431920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Pith citing papers

No inbound Pith citation observations are available.