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Paper Citation Record · LEDGER

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction

As of 17 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2412.05179.

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

pith.paper-citation-record.v1
2412.05179 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:54:54.900007Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

27 of 27 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3bcc17fd-8d69-4f43-99a2-06101c8c65ad · outbound

This paper cites Large-scale data for multiple-view stereopsis.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Large-scale data for multiple-view stereopsis

Reference 1

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Observation 8ae17b42-cf6a-418f-af3d-5c91e7c589f4 · outbound

This paper cites Shape reconstruction by learn- ing differentiable surface representations.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Shape reconstruction by learn- ing differentiable surface representations

Reference 2

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Observation 826c2d04-d452-4bd2-929f-fcdd1e366e68 · outbound

This paper cites Accurate, dense, and robust multiview stereopsis.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Accurate, dense, and robust multiview stereopsis

Reference 3

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Observation 4b55b0cb-c5bb-433f-a8fc-14d651f025da · outbound

This paper cites Implicit Geometric Regularization for Learning Shapes.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Implicit Geometric Regularization for Learning Shapes

Reference 4

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Source-reported events for the cited work

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Observation 833f5494-869c-4e50-b55e-42efbf52172e · outbound

This paper cites A papier-m ˆach´e ap- proach to learning 3d surface generation.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction A papier-m ˆach´e ap- proach to learning 3d surface generation

Reference 5

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Source-reported events for the cited work

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Observation 5fe81296-47cb-4fc9-8db9-244a73d3adc2 · outbound

This paper cites Multiscale tensor decomposition and rendering equation encoding for view synthesis.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Multiscale tensor decomposition and rendering equation encoding for view synthesis

Reference 6

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Observation 4f3a144e-44a1-4479-ae82-dfa0e921d099 · outbound

This paper cites Sape: Spatially-adaptive progressive encoding for neural optimization.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Sape: Spatially-adaptive progressive encoding for neural optimization

Reference 7

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Observation ece091ec-de6d-4b30-8034-210b7e5dd874 · outbound

This paper cites Tanks and temples: Benchmarking large-scale scene reconstruction.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Tanks and temples: Benchmarking large-scale scene reconstruction

Reference 8

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Observation 8b2fabe4-4de0-4b39-8564-2368f0d80bf6 · outbound

This paper cites Neuralangelo: High-fidelity neural surface reconstruction.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Neuralangelo: High-fidelity neural surface reconstruction

Reference 9

Resolution
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Observation 3c5d1afd-b13e-4118-bfc9-9fa37b543be7 · outbound

This paper cites Neural sparse voxel fields.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Neural sparse voxel fields

Reference 10

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Source-reported events for the cited work

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Observation 640bb592-3019-46ab-84c3-1ef2df5576c6 · outbound

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

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Nerf: Representing scenes as neural radiance fields for view syn- thesis

Reference 11

Resolution
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Source-reported events for the cited work

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Observation 0681bbf4-a875-4ffe-8dfa-3269abc9bde2 · outbound

This paper cites Instant neural graphics primitives with a mul- tiresolution hash encoding.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Instant neural graphics primitives with a mul- tiresolution hash encoding

Reference 12

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b4f59a2a-fbf5-4ea6-8c1e-52887a9ab33e · outbound

This paper cites Instant neural graphics primitives with a multires- olution hash encoding.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Instant neural graphics primitives with a multires- olution hash encoding

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation e18ba31f-a5a4-48a1-8c1a-d3c7ead7736d · outbound

This paper cites Rectified linear units im- prove restricted boltzmann machines.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Rectified linear units im- prove restricted boltzmann machines

Reference 14

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Source-reported events for the cited work

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Observation ec49ae11-d2e3-49dc-95eb-a540697f8308 · outbound

This paper cites Structure-from-motion revisited.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Structure-from-motion revisited

Reference 15

Resolution
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Source-reported events for the cited work

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Observation 52ccedd6-5d27-4c8d-9667-df50a2cd0fc0 · outbound

This paper cites Photo tourism: exploring photo collections in 3d.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Photo tourism: exploring photo collections in 3d

Reference 16

Resolution
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Source-reported events for the cited work

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Observation e2fe23c0-e574-42a3-a396-2bb32ee961a8 · outbound

This paper cites Neural geometric level of detail: Real-time rendering with implicit 3D shapes.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Neural geometric level of detail: Real-time rendering with implicit 3D shapes

Reference 17

Resolution
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Observation ff7570c8-5207-472c-8ce7-9e2a48d67a68 · outbound

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

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Fourier features let networks learn high frequency functions in low dimen- sional domains

Reference 18

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Source-reported events for the cited work

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Observation 5bc3e8f7-9bda-4414-859f-97b074fb1a74 · outbound

This paper cites Attention is all you need.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Attention is all you need

Reference 19

Resolution
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Source-reported events for the cited work

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Observation e37d0e14-c266-4f26-8269-fe359ef1a089 · outbound

This paper cites Ref-nerf: Struc- tured view-dependent appearance for neural radiance fields.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Ref-nerf: Struc- tured view-dependent appearance for neural radiance fields

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 41259113-27c0-4df5-bd72-9c196fdbaa97 · outbound

This paper cites Explicit Neural Surfaces: Learning Continuous Geometry With Deformation Fields.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Explicit Neural Surfaces: Learning Continuous Geometry With Deformation Fields

Reference 21

Resolution
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Source-reported events for the cited work

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Observation 4fbd1f15-45c7-4ab3-9fdd-f95940e05be4 · outbound

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

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction,

Reference 22

Resolution
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Source-reported events for the cited work

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Observation 8ef0dce2-52d4-4b7a-be22-613b2bbad662 · outbound

This paper cites Hf-neus: Improved surface reconstruction using high-frequency de- tails.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Hf-neus: Improved surface reconstruction using high-frequency de- tails

Reference 23

Resolution
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Source-reported events for the cited work

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Observation 5c6cc18f-a6f9-4727-96cb-bfae36012220 · outbound

This paper cites Deep geomet- ric prior for surface reconstruction.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Deep geomet- ric prior for surface reconstruction

Reference 24

Resolution
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Source-reported events for the cited work

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Observation 8445af64-bf04-4a26-acd7-cdc2bee0821f · outbound

This paper cites Hollownerf: Pruning hashgrid-based nerfs with trainable collision mitigation, 2023.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Hollownerf: Pruning hashgrid-based nerfs with trainable collision mitigation, 2023

Reference 25

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Source-reported events for the cited work

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Observation 1903e151-ec7a-4ab4-875e-076fc4c330ac · outbound

This paper cites V ol- ume rendering of neural implicit surfaces.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction V ol- ume rendering of neural implicit surfaces

Reference 26

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Source-reported events for the cited work

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Observation 07cce199-d516-47bc-907c-06fd28ec2d93 · outbound

This paper cites Improving deep neural networks using softplus units.

Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction Improving deep neural networks using softplus units

Reference 27

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Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.