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Paper Citation Record · LEDGER

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis

As of 7 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2607.21448.

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

pith.paper-citation-record.v1
2607.21448 v2

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T07:30:39.964357Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

46 of 46 outbound references displayed

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External citation measurements

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Outbound references

Observation 257e0b8b-b95d-4e38-aa79-141117158f6d · outbound

This paper cites Neu- ral 3D Video Synthesis from Multi-view Video,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Neu- ral 3D Video Synthesis from Multi-view Video,

Reference 1

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source=pdf_text observed=2026-08-01T07:30:35.591570Z digest=sha256:584510e3f4065efa1ef6af59001469ce7e53128281d52bf6aaa6248c50e0acd0

Observation 00dd7739-ccc3-4158-bb42-d35a99ed70ed · outbound

This paper cites Real-Time Free Viewpoint Video Synthesis System Based on DIBR and a Depth Estimation Network,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Real-Time Free Viewpoint Video Synthesis System Based on DIBR and a Depth Estimation Network,

Reference 2

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source=pdf_text observed=2026-08-01T07:30:35.665211Z digest=sha256:ab19644a1466c044b20abf93e3b5b4f659702e6efa9117ba35e982e64044dd42

Observation 4fe4e88b-8933-4ec7-b9e4-d7cf2b82bd4a · outbound

This paper cites Advancing Generalizable Occlusion Modeling for Neural Human Radiance Field,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Advancing Generalizable Occlusion Modeling for Neural Human Radiance Field,

Reference 3

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source=pdf_text observed=2026-08-01T07:30:35.732365Z digest=sha256:da9e31d72b796f6e0c2ed8d5b19fc0db2e4cf658cf654cc43f064402abcde51d

Observation ff9bb448-33ab-442d-b3a6-f6fee55437b8 · outbound

This paper cites GS-SFS: Joint Gaussian Splatting and Shape-From-Silhouette for Multiple Human Reconstruction in Large-Scale Sports Scenes,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis GS-SFS: Joint Gaussian Splatting and Shape-From-Silhouette for Multiple Human Reconstruction in Large-Scale Sports Scenes,

Reference 4

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source=pdf_text observed=2026-08-01T07:30:35.810178Z digest=sha256:6d6e085e951fa481d0f35ef2698c7f13ac5a307daf95b796136e589b64170f32

Observation 447c8c21-8502-47d4-b81f-874c803f58ec · outbound

This paper cites Neural V olumetric Video Coding With Hierarchical Coded Representation of Dynamic V olume,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Neural V olumetric Video Coding With Hierarchical Coded Representation of Dynamic V olume,

Reference 5

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source=pdf_text observed=2026-08-01T07:30:35.909010Z digest=sha256:3bd5c372d53c7d571f7f4a1e8e115b5bd1c8746cad5b5e26639d0e5223b0bf85

Observation e45f8233-fa6d-4344-a29d-2f2fc38c8c2d · outbound

This paper cites Neural Body: Implicit Neural Representations with Structured La- tent Codes for Novel View Synthesis of Dynamic Humans,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Neural Body: Implicit Neural Representations with Structured La- tent Codes for Novel View Synthesis of Dynamic Humans,

Reference 6

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source=pdf_text observed=2026-08-01T07:30:35.999722Z digest=sha256:e9bf93d5ab56a2c1face84db534cbffca1f3dc6f665e1f48aa422784a5922624

Observation 70caa553-85a6-4730-94f5-e6103c34d257 · outbound

This paper cites 4K4D: Real-Time 4D View Synthesis at 4K Resolution,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis 4K4D: Real-Time 4D View Synthesis at 4K Resolution,

Reference 7

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source=pdf_text observed=2026-08-01T07:30:36.075550Z digest=sha256:459e2e4cde7aff48141356fd70b20c647b27e14b6a304c9d4907d389d284a8e2

Observation 9e3fdb57-f853-4a45-9f51-38ae1dc7596d · outbound

This paper cites Dynamic Gaussians Mesh: Consistent Mesh Reconstruction from Dynamic Scenes,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Dynamic Gaussians Mesh: Consistent Mesh Reconstruction from Dynamic Scenes,

Reference 8

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source=pdf_text observed=2026-08-01T07:30:36.170254Z digest=sha256:a6aa6c8abecf658e0bfe7e1d283a9935e62eb001afe14aa599979a4a7fb1a0c1

Observation efbd72fd-af1c-43ed-8593-ae8ea63e9223 · outbound

This paper cites Monocular Dynamic View Synthesis: A Reality Check,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Monocular Dynamic View Synthesis: A Reality Check,

Reference 9

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source=pdf_text observed=2026-08-01T07:30:36.247561Z digest=sha256:17859e1e4142a17acbc148248adf3a4e43a5edb6c2e7bbd3ffbb844b19dd2cff

Observation 7ba7854b-c454-4b55-bd52-641062de65e4 · outbound

This paper cites NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis,

Reference 10

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source=pdf_text observed=2026-08-01T07:30:36.337055Z digest=sha256:21684c716f5551bb10ac877263071d2ddce8db79dbc48345e61dc441825f1d5f

Observation dcd4faca-7361-459a-8e62-61cef727d976 · outbound

This paper cites Local light field fusion: practical view synthesis with prescriptive sampling guidelines,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Local light field fusion: practical view synthesis with prescriptive sampling guidelines,

Reference 11

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source=pdf_text observed=2026-08-01T07:30:36.432525Z digest=sha256:fa5820f2002692e5f8d05372b26ea3854e081adaa8c024b5d81db1747a2a9a31

Observation 61bfa54b-a06c-48b6-a136-e3315d3abf5c · outbound

This paper cites CBARF: Cascaded Bundle- Adjusting Neural Radiance Fields From Imperfect Camera Poses,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis CBARF: Cascaded Bundle- Adjusting Neural Radiance Fields From Imperfect Camera Poses,

Reference 12

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source=pdf_text observed=2026-08-01T07:30:36.538955Z digest=sha256:f4953dc76a4d8a8dad2ff5b80f10604ea3ded8dc9e34234742241e5093700149

Observation 787b89db-bb6a-4278-bb39-90cd8c9beca3 · outbound

This paper cites Msa-Splatting: Multi- Scale Adaptive Gaussian Splatting for High-Fidelity View Synthesis,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Msa-Splatting: Multi- Scale Adaptive Gaussian Splatting for High-Fidelity View Synthesis,

Reference 13

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source=pdf_text observed=2026-08-01T07:30:36.638377Z digest=sha256:82fe9702e05ad68eed9defb284a6ec1d7ff7ce535ad638ded58a0ccf3a37f323

Observation e871d5a4-8b27-41bf-87dc-94a7e293904a · outbound

This paper cites Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields,

Reference 14

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source=pdf_text observed=2026-08-01T07:30:36.803054Z digest=sha256:51d16066bf2d8a307a3b5053d5571471ca406c4f91cd2eb9830e295d5c17e1c9

Observation 8885df9b-5adf-4295-b58e-90ed23b8eaa6 · outbound

This paper cites StructGS: Adaptive Spherical Harmon- ics and Rendering Enhancements for Superior 3D Gaussian Splatting,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis StructGS: Adaptive Spherical Harmon- ics and Rendering Enhancements for Superior 3D Gaussian Splatting,

Reference 15

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source=pdf_text observed=2026-08-01T07:30:36.950033Z digest=sha256:0071cfa79e8038aa49f5063fb8ea24b448cb65f55d18436dda61e1592c993ac8

Observation 026f6b66-556e-49ac-a341-b3b307e4bc0e · outbound

This paper cites Nerfies: Deformable Neural Radiance Fields,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Nerfies: Deformable Neural Radiance Fields,

Reference 16

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source=pdf_text observed=2026-08-01T07:30:37.071351Z digest=sha256:c78fb37eabde3684c79c891f391a815c8aa1539e98cd6cef9e40b9b2774b578e

Observation 16b8022e-1de3-49a1-bc6a-a99752fd5c60 · outbound

This paper cites Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes,

Reference 17

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source=pdf_text observed=2026-08-01T07:30:37.200855Z digest=sha256:6c80cc5f0bd5ae2ea8c846396bad304ed98b52de74cccaab7241ae6259f7f8e2

Observation 852b37da-c8d0-4a3a-92aa-60822497e50a · outbound

This paper cites HyperNeRF: a higher-dimensional representation for topologically varying neural radiance fields,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis HyperNeRF: a higher-dimensional representation for topologically varying neural radiance fields,

Reference 18

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source=pdf_text observed=2026-08-01T07:30:37.338887Z digest=sha256:772ce15c80c0ef4db5c479d904da33e355defdb620e28969545145879d7c0c90

Observation ebfb7bc3-3f9d-4c36-a7b4-4daee09fc77e · outbound

This paper cites ATM-NeRF: Accelerating Training for NeRF Rendering on Mobile Devices via Geometric Regu- larization,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis ATM-NeRF: Accelerating Training for NeRF Rendering on Mobile Devices via Geometric Regu- larization,

Reference 19

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source=pdf_text observed=2026-08-01T07:30:37.490783Z digest=sha256:7994db8194bfcfeac0a30ed7d2403fd0e963c626f755a7c197f1363d2dbf644d

Observation 1c90be6e-81e3-4cb7-aeee-28dd33f97846 · outbound

This paper cites Robust Dynamic Radiance Fields,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Robust Dynamic Radiance Fields,

Reference 20

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source=pdf_text observed=2026-08-01T07:30:37.615641Z digest=sha256:c020e010587b38e6ac690eb42cbc0facb624a260985c2aa15d3d33c0cab3436b

Observation 440113bb-2fa6-4ed6-9483-bd2805a3f274 · outbound

This paper cites NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fields,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fields,

Reference 21

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source=pdf_text observed=2026-08-01T07:30:37.742403Z digest=sha256:dba09cbe0a770b2105a8dc831df917724ae6a5526628492fa33843cec92fa0d1

Observation eb12b319-5b15-427a-b4b5-67e65d9add9c · outbound

This paper cites 3D Gaussian Splatting for Real-Time Radiance Field Rendering,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis 3D Gaussian Splatting for Real-Time Radiance Field Rendering,

Reference 22

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source=pdf_text observed=2026-08-01T07:30:37.837512Z digest=sha256:64078c5d52010486d0e6c6f9863203428701098f0ba12f97147e73fe4c129765

Observation 8957e59d-1e3c-4b4f-a299-80a395b9868b · outbound

This paper cites Pulsar: Efficient Sphere-based Neural Rendering,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Pulsar: Efficient Sphere-based Neural Rendering,

Reference 23

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source=pdf_text observed=2026-08-01T07:30:37.914701Z digest=sha256:8bdd49f34b791366fc5ed866ef6d2f548dea9d00eec843b65ca490d4d598a03e

Observation ab01b01f-07c6-4731-8423-a47abd5c1039 · outbound

This paper cites Surface splatting,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Surface splatting,

Reference 24

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source=pdf_text observed=2026-08-01T07:30:37.997187Z digest=sha256:f384fa638ea484a82ef067bcaefa771355fef839da49f565998fb362044cb0bf

Observation a098ec86-b12d-4e13-ba76-a9c3a986bc12 · outbound

This paper cites EW A splatting,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis EW A splatting,

Reference 25

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source=pdf_text observed=2026-08-01T07:30:38.063375Z digest=sha256:c3d7e1e0194279ca517bcef119e21c0990bcde5fdfb5f6d132de44a875692ce0

Observation dc142a24-b6a8-4267-b1ec-e82a3d252a38 · outbound

This paper cites Object Space EW A Surface Splatting: A Hardware Accelerated Approach to High Quality Point Rendering,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Object Space EW A Surface Splatting: A Hardware Accelerated Approach to High Quality Point Rendering,

Reference 26

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source=pdf_text observed=2026-08-01T07:30:38.135083Z digest=sha256:b844be68722fc096270e172a0042a4eba0cffe3979de325a4b32dcc05bcc9180

Observation d1f5e94e-e48c-49d5-b83e-79207ba9b981 · outbound

This paper cites Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis,

Reference 27

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source=pdf_text observed=2026-08-01T07:30:38.224784Z digest=sha256:22540ef8240464ddd5fc5b02dfa87388984513b4a58192a74b8db78147771a40

Observation 905c9865-aa24-455f-82e6-37a7b7600ed0 · outbound

This paper cites Gaussian-Flow: 4D Reconstruction with Dynamic 3D Gaussian Particle,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Gaussian-Flow: 4D Reconstruction with Dynamic 3D Gaussian Particle,

Reference 28

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source=pdf_text observed=2026-08-01T07:30:38.367538Z digest=sha256:1eb487c8b7edbc7999f3b5f2a33c95fe88735ff2b702c246049e86d2677c9fad

Observation 41d127ee-b3a2-4590-acdd-d544ea8d7290 · outbound

This paper cites Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruc- tion,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruc- tion,

Reference 29

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source=pdf_text observed=2026-08-01T07:30:38.451680Z digest=sha256:b1b8604ec67a4f7a21e74a3475472211672f79fe2d1bd0a70a93db14bbbf75e8

Observation 7f1b5574-184f-475a-a8be-aab8852790a4 · outbound

This paper cites 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering,

Reference 30

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source=pdf_text observed=2026-08-01T07:30:38.514245Z digest=sha256:bd80227c0f669c5bc3cc5ddafe1862e4e7b8be4c9ddfd4a263b2b66ca88de4ae

Observation aa0cc6be-d3dd-4f65-9d43-93ca76167dd2 · outbound

This paper cites SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenes,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenes,

Reference 31

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source=pdf_text observed=2026-08-01T07:30:38.605357Z digest=sha256:c14c9688b38db600b49829a7e807ed8f372820063ca70e55da08a05f43ce5ff4

Observation e2b0c4b2-c95f-46c6-a72e-0f92f50f8f8d · outbound

This paper cites Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting,

Reference 32

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source=pdf_text observed=2026-08-01T07:30:38.690724Z digest=sha256:bd98edb629969d255991bd4af6f4ceaf002af79742a4f6021f9d9bf0203922c4

Observation 8b1dde88-aac9-4f5b-abbf-cf30ded05cbd · outbound

This paper cites 4D Scaffold Gaussian Splatting with Dynamic-Aware Anchor Growing for Efficient and High-Fidelity Dynamic Scene Reconstruction,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis 4D Scaffold Gaussian Splatting with Dynamic-Aware Anchor Growing for Efficient and High-Fidelity Dynamic Scene Reconstruction,

Reference 33

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source=pdf_text observed=2026-08-01T07:30:38.775808Z digest=sha256:079139738b325ebac4a15afa688f26a4690b29a2d4b8360336f3ddc2211b5676

Observation da707fb7-6431-4459-b76c-47222cee1346 · outbound

This paper cites MoDec-GS: Global-to-Local Motion Decomposition and Temporal Interval Adjustment for Compact Dynamic 3D Gaussian Splatting,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis MoDec-GS: Global-to-Local Motion Decomposition and Temporal Interval Adjustment for Compact Dynamic 3D Gaussian Splatting,

Reference 34

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source=pdf_text observed=2026-08-01T07:30:38.867474Z digest=sha256:2e6db3eb62549b49640ad6ee3790d5b36dc5565f16c47c2eae1f1f3dc0f5d3a7

Observation d7562a3e-dd13-4d9d-8311-793faa12cf78 · outbound

This paper cites Scaffold- GS: Structured 3D Gaussians for View-Adaptive Rendering,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Scaffold- GS: Structured 3D Gaussians for View-Adaptive Rendering,

Reference 35

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Observation df1d76ce-9782-4d1e-9829-9a92dae57c94 · outbound

This paper cites Octree- GS: Towards Consistent Real-time Rendering with LOD-Structured 3D Gaussians,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Octree- GS: Towards Consistent Real-time Rendering with LOD-Structured 3D Gaussians,

Reference 36

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no resolver link, observed 2026-08-01T07:30:39.067743Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T07:30:39.067743Z digest=sha256:11479c40f744cbd98f762f65a10dd7acf8225b2e9d7fb1a5425ce48988845a1d

Observation 54958a03-5c25-4f3c-a5a5-5065c273365e · outbound

This paper cites D- NeRF: Neural Radiance Fields for Dynamic Scenes,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis D- NeRF: Neural Radiance Fields for Dynamic Scenes,

Reference 37

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unresolved
no resolver link, observed 2026-08-01T07:30:39.159452Z

Source-reported events for the cited work

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Observation 9fdbde47-fe39-4596-b583-43d5403a2c62 · outbound

This paper cites Instant Neural Graphics Primitives with a Multiresolution Hash Encoding,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Instant Neural Graphics Primitives with a Multiresolution Hash Encoding,

Reference 38

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unresolved
no resolver link, observed 2026-08-01T07:30:39.251743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T07:30:39.251743Z digest=sha256:16c45bf381f60a8d9d4f6058b6355fb277d58899ca31de4bad180a5728b9ce23

Observation 2bf941d7-35df-45ac-b72e-f9a5ed5435af · outbound

This paper cites Fast Dynamic Radiance Fields with Time-Aware Neural V oxels,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Fast Dynamic Radiance Fields with Time-Aware Neural V oxels,

Reference 39

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unresolved
no resolver link, observed 2026-08-01T07:30:39.370730Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T07:30:39.370730Z digest=sha256:ff5f726c9c8c9edadc01207e1dc916c738b295d417e1631c64731ea9c1338bd7

Observation 72659304-0d01-40d8-b4b0-f03c92057ea5 · outbound

This paper cites HexPlane: A Fast Representation for Dynamic Scenes,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis HexPlane: A Fast Representation for Dynamic Scenes,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-01T07:30:39.451735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T07:30:39.451735Z digest=sha256:7274214c2d9859000fdbe009f74bf2b88c8bee0c1c944f7c8f3e98a7f9949281

Observation a898ecf6-0a23-40e0-8523-7453fa441b4e · outbound

This paper cites K-Planes: Explicit Radiance Fields in Space, Time, and Appearance,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis K-Planes: Explicit Radiance Fields in Space, Time, and Appearance,

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-01T07:30:39.539203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T07:30:39.539203Z digest=sha256:b71f31c1def8d551f08c6ec0c06cb2dfaacbfa5d8c0eb4c741aba98546862b89

Observation 1939054d-c6ff-457b-9d7b-0796c646df77 · outbound

This paper cites Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting,

Reference 42

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unresolved
no resolver link, observed 2026-08-01T07:30:39.623491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T07:30:39.623491Z digest=sha256:be37b6f313206280238f16610ac5dfa96898aa871fc933fd036b929ebb6151ff

Observation 459884c2-43ac-4bc5-a599-4423a882660d · outbound

This paper cites DynamicFusion: Recon- struction and Tracking of Non-rigid Scenes in Real-Time,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis DynamicFusion: Recon- struction and Tracking of Non-rigid Scenes in Real-Time,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-01T07:30:39.736300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T07:30:39.736300Z digest=sha256:ab28da32ec64120de30dea1674e899f4fc35d92802e45b100c920a3becab39dd

Observation e3b46ede-2da7-44cb-9199-9f688c2deb3c · outbound

This paper cites V olumeDeform: Real-Time V olumetric Non-rigid Reconstruc- tion,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis V olumeDeform: Real-Time V olumetric Non-rigid Reconstruc- tion,

Reference 44

Resolution
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no resolver link, observed 2026-08-01T07:30:39.797136Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T07:30:39.797136Z digest=sha256:f9894aa770f8005dbb8821d61f4dd2a443417f2fb894db9d1c7c7f53b2d9129a

Observation 3b6a240e-e477-4776-8fc1-e8d0e4d32e80 · outbound

This paper cites Fourier Features Let Networks Learn High Frequency Functions in Low Dimen- sional Domains,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Fourier Features Let Networks Learn High Frequency Functions in Low Dimen- sional Domains,

Reference 45

Resolution
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no resolver link, observed 2026-08-01T07:30:39.878367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T07:30:39.878367Z digest=sha256:435375963312082300bd79a05eb1d371ff5de996aae809b86b6826226ae2f921

Observation f4d82deb-50e5-434d-a6e6-7a440f211d37 · outbound

This paper cites Tensor4D: Efficient Neural 4D Decomposition for High-Fidelity Dynamic Recon- struction and Rendering,.

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis Tensor4D: Efficient Neural 4D Decomposition for High-Fidelity Dynamic Recon- struction and Rendering,

Reference 46

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unresolved
no resolver link, observed 2026-08-01T07:30:39.964357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T07:30:39.964357Z digest=sha256:aacb575299c22de05270a1af1187fdbecc0522447d6cd0ae5f37e702842cd047

Pith citing papers

No inbound Pith citation observations are available.