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Paper Citation Record · LEDGER

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features

As of 8 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 3 inbound Pith citation observations for arXiv:2502.08377.

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

pith.paper-citation-record.v1
2502.08377 v3

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:22:20.020565Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T06:23:50.361291Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T06:09:49.428709Z

Reference resolution

59 of 59 outbound references displayed

  • verified exact0
  • verified fuzzy25
  • unresolved34
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b4b7684-b4b9-4bff-b997-f77367cc36fc · outbound

This paper cites STAG4D: Spatial-Temporal Anchored Generative 4D Gaussians.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features STAG4D: Spatial-Temporal Anchored Generative 4D Gaussians

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.812148Z digest=sha256:bc9692c01528fd887f1dbf1f2b3ee48f66c9082fdc389c9adc94201c727f3593

Observation bdce4c5a-5f71-4681-94a6-10fe4e983977 · outbound

This paper cites Neural 3d video synthesis from multi-view video.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Neural 3d video synthesis from multi-view video

Reference 2

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.816723Z digest=sha256:f6c13ec3f2be88923535d161c9c18af837cff95ce33b174039f5be02891f5520

Observation add9fc38-d4fa-44ab-9731-20927e483b92 · outbound

This paper cites Tensor4d: Efficient neural 4d decomposition for high-fidelity dynamic reconstruction and rendering.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Tensor4d: Efficient neural 4d decomposition for high-fidelity dynamic reconstruction and rendering

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.820709Z digest=sha256:32a9ff9f04f40d22d4e8421db120c0375b0735df1e940c067933ab3786d32a76

Observation 7f2d6c78-7e25-4749-bf89-cb68d47737e2 · outbound

This paper cites Neural scene flow fields for space-time view synthesis of dy- namic scenes.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Neural scene flow fields for space-time view synthesis of dy- namic scenes

Reference 4

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raw_fallback, observed 2026-08-08T05:22:20.596616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.824476Z digest=sha256:eb8cb2e7a35d5900327672eb0e55af5d92d7d631c3a474bc147fb0f9d2aa5ea3

Observation e6c99647-079e-4cd6-b6b9-2f7b979a535f · outbound

This paper cites D-nerf: Neural radiance fields for dynamic scenes.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features D-nerf: Neural radiance fields for dynamic scenes

Reference 5

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raw_fallback, observed 2026-08-08T05:22:20.585535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.828044Z digest=sha256:7afdea9a2bdaf7052ab80c8760c97076470c0ab82ccb0e4eec3743b2ba55d9f3

Observation 262a2936-f0ce-4c9f-a775-aa7675eea4e1 · outbound

This paper cites HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields

Reference 6

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no resolver link, observed 2026-08-08T05:22:19.831492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.831492Z digest=sha256:5d82e926053246541a008f4d3ab0cfb593b2d3b19b1111565b22a87d3d058fcb

Observation 902e9d17-b59d-447a-a642-a4b28c2e507e · outbound

This paper cites Monocular dynamic view synthesis: A reality check.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Monocular dynamic view synthesis: A reality check

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.835301Z digest=sha256:2149f56e532d263e329e472bc464f3d4c1896cd5f1ebb801807314df26bef765

Observation 61f8ade1-3d74-4f97-a27f-718feb89e810 · outbound

This paper cites Dreammesh4d: Video-to-4d generation with sparse-controlled gaussian- mesh hybrid representation.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Dreammesh4d: Video-to-4d generation with sparse-controlled gaussian- mesh hybrid representation

Reference 8

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raw_fallback, observed 2026-08-08T05:22:20.568236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.838646Z digest=sha256:0c8d237d2e92a98644ca6c2f10edab9ec72170d702b42f7269d2614a1424e60b

Observation 9a401431-df1d-4509-a96f-4d0e90d713a4 · outbound

This paper cites 4d gaussian splatting for real-time dynamic scene rendering.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features 4d gaussian splatting for real-time dynamic scene rendering

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.842108Z digest=sha256:ee4a06bb01c5e3c9b61875a6e379851f8fe2abe0228adfd96b3a78b679f7eb77

Observation 7c28ef61-6622-4711-a337-820f49b50467 · outbound

This paper cites SV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View Consistency.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features SV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View Consistency

Reference 10

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.846162Z digest=sha256:d9c2d2056a89ff446bd606cfbbbf9efb697206745deefcde1803abe6ab14fbdc

Observation 38898a85-4842-4207-b21a-2c241d71625f · outbound

This paper cites 4Diffusion: Multi-view Video Diffusion Model for 4D Generation.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features 4Diffusion: Multi-view Video Diffusion Model for 4D Generation

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.849793Z digest=sha256:d7b784ff8194419b7221e279f7c5b076f928b26ee0ea8902ef351444a1b839c4

Observation 89e2dfcf-212f-4974-a971-725d59d6a150 · outbound

This paper cites L4GM: Large 4D Gaussian Reconstruction Model.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features L4GM: Large 4D Gaussian Reconstruction Model

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.853511Z digest=sha256:bf34c2ba3f0f10032aec36200362f76668cd70dc8a67442579211778cbc6384d

Observation 6005e28b-9005-4e45-98da-249e36ae5ff3 · outbound

This paper cites Diffusion4D: Fast Spatial-temporal Consistent 4D Generation via Video Diffusion Models.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Diffusion4D: Fast Spatial-temporal Consistent 4D Generation via Video Diffusion Models

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.857184Z digest=sha256:7dfb39b5f09891a624ee8eeb4697af8d977186d3ff8a0446b2476c4483c5dde9

Observation e6cdf301-c546-4612-b0c8-dfa6f3ef08fa · outbound

This paper cites Text-To-4D Dynamic Scene Generation.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Text-To-4D Dynamic Scene Generation

Reference 14

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no resolver link, observed 2026-08-08T05:22:19.860922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.860922Z digest=sha256:42a1d15329ad3880bacdd5465edd282ab05fdf430b1e930a176f89c0acf469bd

Observation 64d6f9d6-208c-472d-a94d-8828c08185d8 · outbound

This paper cites 4DGen: Grounded 4D Content Generation with Spatial-temporal Consistency.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features 4DGen: Grounded 4D Content Generation with Spatial-temporal Consistency

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.864341Z digest=sha256:99cde10529757106e3082e5cfd5660a6640a8a73b5a6e55807ef25db462c4e13

Observation 3b4fd678-f051-4e56-b182-efcd2d52ce49 · outbound

This paper cites SC4D: Sparse-Controlled Video-to-4D Generation and Motion Transfer.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features SC4D: Sparse-Controlled Video-to-4D Generation and Motion Transfer

Reference 16

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no resolver link, observed 2026-08-08T05:22:19.868173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.868173Z digest=sha256:65ce5f4387c1220d41690eae64f99a91a8b87d0df0750df5f42f9b94af6165f0

Observation 04422840-f9b3-4a8e-98ae-5a58574d23d7 · outbound

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

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Zero-1-to- 3: Zero-shot one image to 3d object

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.872015Z digest=sha256:0b4c70e4213963d500ec80d7bdc54cd97045a46c6348e3380e73ae92a8fc4553

Observation e1efdae6-7283-4e77-885c-c4fd682b9f3d · outbound

This paper cites Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.875783Z digest=sha256:2ca5595f38639ebc11c535007d682571bbdb1cefd4980670bdce7ced56419dcc

Observation 3ae84c24-15ef-4d83-88fb-310c1700c5cd · outbound

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

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models

Reference 19

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.879641Z digest=sha256:b35bd6e5463933bbf88018c63abdb410c48b575622f4f1d755097552d5ba381b

Observation 98be6be9-4828-4b85-b496-ec55c4d4a766 · outbound

This paper cites Consistent4d: Consistent 360° dynamic object gen- eration from monocular video.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Consistent4d: Consistent 360° dynamic object gen- eration from monocular video

Reference 20

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raw_fallback, observed 2026-08-08T05:22:20.539075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.883354Z digest=sha256:76c40940bc5e278c282d62520740186bf8b50d32c82dfffb6ed1d7d9323aca4c

Observation 9004fff0-eb68-49dc-9210-1913b5b19c5b · outbound

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

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Objaverse: A universe of annotated 3d objects

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.886773Z digest=sha256:c10e1492efebbbb82fde74554cc941b267090776a9571162ccc471ea1ca35cdc

Observation 48ea874d-4510-478b-8ed2-64ae6f9fefac · outbound

This paper cites 3d-r2n2: A unified approach for single and multi-view 3d object reconstruction.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features 3d-r2n2: A unified approach for single and multi-view 3d object reconstruction

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.890056Z digest=sha256:28f8cec878014ff99bacc0158d73028c213fb8d84744c9936a7a385dd1d2e7fa

Observation 85a0968a-346c-41b5-8e3b-73a7cf929d55 · outbound

This paper cites Pix2vox++: Multi-scale context- aware 3d object reconstruction from single and multi- ple images.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Pix2vox++: Multi-scale context- aware 3d object reconstruction from single and multi- ple images

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.509724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.893420Z digest=sha256:cf9f0c3b7231b95c4011527f855379ce16c5e3c66d947b570bc025add0b5f1fd

Observation 31b9070d-db93-49a8-a268-ec3b22b4a1f6 · outbound

This paper cites Umiformer: Mining the correlations between similar tokens for multi-view 3d reconstruction.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Umiformer: Mining the correlations between similar tokens for multi-view 3d reconstruction

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.498938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.896832Z digest=sha256:36d63eb2b877a88c6c45c2662a4c080d3ab37fa5f1178bea7577a7d8b4d298c2

Observation 29b18473-b2a4-4883-9c09-3e3755cde6bc · outbound

This paper cites Long-range grouping transformer for multi- view 3d reconstruction.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Long-range grouping transformer for multi- view 3d reconstruction

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.488177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.900199Z digest=sha256:2f29b60575a325904cbb708490fe87ae877fe722505558eee71050108179b884

Observation 18297970-06b6-458a-82bd-442639e2f67b · outbound

This paper cites Pixel2mesh: Generating 3d mesh models from single rgb images.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Pixel2mesh: Generating 3d mesh models from single rgb images

Reference 26

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no resolver link, observed 2026-08-08T05:22:19.903868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.903868Z digest=sha256:f7720ad5a975626c5339b2dfb7d8eeb905e9d71193a8d1a832c627889d26faef

Observation 85f6f5cb-786a-4843-bf4e-7858961264f1 · outbound

This paper cites Differentiable volumetric rendering: Learn- ing implicit 3d representations without 3d supervision.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Differentiable volumetric rendering: Learn- ing implicit 3d representations without 3d supervision

Reference 27

Resolution
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raw_fallback, observed 2026-08-08T05:22:20.470820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.907374Z digest=sha256:75aa3d9b7353bbd8751aacf7f243b7491517b0ae6e32379c741e891b8e57cdd5

Observation 6229bf7e-a941-40af-b1e9-7a8823a3f902 · outbound

This paper cites Pixel2mesh++: 3d mesh generation and refinement from multi-view images.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Pixel2mesh++: 3d mesh generation and refinement from multi-view images

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.459317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.910883Z digest=sha256:5b753156e7a580aa8c9265e1b841855ec40d94463e3d29e637dc1d1d3448626c

Observation d7140bed-99f4-459a-9990-7f20a257bf0c · outbound

This paper cites Multires- olution tree networks for 3d point cloud processing.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Multires- olution tree networks for 3d point cloud processing

Reference 29

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raw_fallback, observed 2026-08-08T05:22:20.448682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.914310Z digest=sha256:b813c710d95ed0d3cbd618e9a9ddcc943d1f9ddefffb2658edf001f925973158

Observation e79b394a-e495-4f45-8d49-e776a9b99f6d · outbound

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

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Learning representations and generative models for 3d point clouds

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.436815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.917687Z digest=sha256:0c00f91e8193a4423be01db2bef1023e81792663f574fa2a141f73e758adc769

Observation ca5a21d0-02ee-4d3b-9fe6-ff9bed54e20c · outbound

This paper cites Diffusion probabilistic models for 3d point cloud generation.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Diffusion probabilistic models for 3d point cloud generation

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.920986Z digest=sha256:4d43bd5fdad5775a0bc35e479641346f8b89f1223e65021070fe196b0b5fdbff

Observation 931b7c39-320a-42b9-8035-3a0fa784245f · outbound

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

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Nerf: Representing scenes as neural radiance fields for view syn- thesis

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.420001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.924306Z digest=sha256:a7623360a0b9fe58eb57ac2b229005b9d9b01b5c1b65bda14947453beb7d999c

Observation 21c36e20-3779-4dff-9d63-7e5d7f89d4ab · outbound

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

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Instant neural graphics primitives with a mul- tiresolution hash encoding

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.927575Z digest=sha256:f991e0c783dbf8a81ee2fbb85f36477175de4affd653f7ca471550872ffe53ef

Observation a9dcfbe1-99c9-49b4-9a6e-d6d410c56ea7 · outbound

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

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features 3d gaussian splatting for real-time radiance field rendering

Reference 34

Resolution
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no resolver link, observed 2026-08-08T05:22:19.931104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.931104Z digest=sha256:55bbf5d1af8c769c3c4d39e9936c78fe4cc32d0fe94d9b31c78243b238cb4cff

Observation 12c63243-4b8f-44bd-b6ca-d850c49f7953 · outbound

This paper cites Mip-splatting: Alias-free 3d gaussian splat- ting.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Mip-splatting: Alias-free 3d gaussian splat- ting

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.394592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.934394Z digest=sha256:8a769fa4ee982034cbeba9042bdd97de410854f41b3f531103b533329427869d

Observation 631ea694-9b05-4537-ab95-1d57b5935efa · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Photorealistic text-to-image diffusion models with deep language understanding

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:19.937944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.937944Z digest=sha256:fc3338db7588dca4e3337a16f005e642086f1cc51670c94c89dd827b0a8d43e5

Observation dacc9d42-9f0f-4d1c-84e0-0948e18648b9 · outbound

This paper cites Barron, and Ben Milden- hall.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Barron, and Ben Milden- hall

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.377194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.941622Z digest=sha256:e77ab0665c8788378f88a2bddfceef548efaad2b6903ae8c3754b65d59b9c2fa

Observation 47483615-f7f2-4e14-878e-dd9189e0d846 · outbound

This paper cites Dreamgaussian: Generative gaussian splatting for ef- ficient 3d content creation.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Dreamgaussian: Generative gaussian splatting for ef- ficient 3d content creation

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.366007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.944929Z digest=sha256:42c62be65a0ca376c8559b9c4de1935cea50c31960aa9620633a91c5932d11b2

Observation 871735d2-ecb0-4f23-ae3a-04a0bea8c897 · outbound

This paper cites Nerfies: Deformable neural radiance fields.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Nerfies: Deformable neural radiance fields

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:19.948163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.948163Z digest=sha256:14fcde87c1767739410608bc19e3c83ca476bcbb891ec7023e0044f8b0edf200

Observation 5dbdfd3e-3121-4c1f-bb50-3b5d1a0da445 · outbound

This paper cites Non- rigid neural radiance fields: Reconstruction and novel view synthesis of a dynamic scene from monocular video.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Non- rigid neural radiance fields: Reconstruction and novel view synthesis of a dynamic scene from monocular video

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:19.951456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.951456Z digest=sha256:2ccfc18f90bf44ab782d64feb013e40c422f791e8174f49b82d10029fa2a547e

Observation 3d0ec004-917e-4509-bf55-a52b457eaf0c · outbound

This paper cites Dˆ 2nerf: Self-supervised decoupling of dynamic and static objects from a monocular video.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Dˆ 2nerf: Self-supervised decoupling of dynamic and static objects from a monocular video

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.341912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.954874Z digest=sha256:5a55f148387983557531cbac9f227aca49f7078bb6b153e0e2091f7e59a72d0f

Observation 18277545-88cb-4734-bb24-1b47ebdfe571 · outbound

This paper cites Fast dynamic radiance fields with time-aware neural vox- els.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Fast dynamic radiance fields with time-aware neural vox- els

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.330364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.958393Z digest=sha256:b57d89df2478507ef0e90fed1ffbc58b77dd9042194add37108e91050f38e4fc

Observation 02b90a69-e4b8-47a1-b03d-35154b1ae058 · outbound

This paper cites Spacetime gaus- sian feature splatting for real-time dynamic view synthesis.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Spacetime gaus- sian feature splatting for real-time dynamic view synthesis

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.318346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.961690Z digest=sha256:e6734e4f3eaa548330102655f920b38a708dace2fd58a487a91994789923a144

Observation 9793b4ea-05cb-451d-a281-a9093192dfc0 · outbound

This paper cites GauFRe: Gaussian Deformation Fields for Real-time Dynamic Novel View Synthesis.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features GauFRe: Gaussian Deformation Fields for Real-time Dynamic Novel View Synthesis

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:19.964927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.964927Z digest=sha256:ed88fd8b46dd9338af2fb6e36f08edea4c8230be833bf8496398e1cbeeef37d1

Observation 001a5a89-9cc6-4ae8-b9ba-fe7544635f1f · outbound

This paper cites Dynamic 3d gaussians: Tracking by per- sistent dynamic view synthesis.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Dynamic 3d gaussians: Tracking by per- sistent dynamic view synthesis

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.307470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.968390Z digest=sha256:fe799db52b7bede49e188b249aa12871d741a8bf54d3e945532d2eb1f9c672a3

Observation 0bcdd9bd-fa39-4581-a7ce-5c6d243a473e · outbound

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

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:19.971917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.971917Z digest=sha256:9f66b5673f7fcc89793b20b8b6fdb248630d2801dacd7cab2697244653856c18

Observation 26908055-01e2-4745-b8d8-ba49e8e4d7ce · outbound

This paper cites DreamGaussian4D: Generative 4D Gaussian Splatting.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features DreamGaussian4D: Generative 4D Gaussian Splatting

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:19.975547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.975547Z digest=sha256:41d41a8ee1ed317670fd76a328ff3a54760dd9b0cf209d353492539c760504d7

Observation 2ebe33e0-d819-4072-92f2-db6e09bcbbff · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features DINOv2: Learning Robust Visual Features without Supervision

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:19.979022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.979022Z digest=sha256:d7c358ec98b270f49b5afce0cfdbe020e3c98a8e1639ce2906b2bf30f2aabbf4

Observation 0d380227-2994-431e-9e68-44ca9bcf0587 · outbound

This paper cites Pc2: Projection-conditioned point cloud diffu- sion for single-image 3d reconstruction.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Pc2: Projection-conditioned point cloud diffu- sion for single-image 3d reconstruction

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.296122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.982592Z digest=sha256:4c63c5f0158e36bdd859ae15841cc16b275a60b9f67e00a1db099308828123fd

Observation bdf43da6-0a96-40f5-9a3d-cac84ef9454c · outbound

This paper cites Hexplane: A fast representa- tion for dynamic scenes.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Hexplane: A fast representa- tion for dynamic scenes

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.284622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.986321Z digest=sha256:d3cc062a55db09225497779cf633597c57cd4f1acaa2dd72bf496651d7d646b5

Observation b6303f90-b497-4413-ae30-626a8a29b82f · outbound

This paper cites LRM: Large Reconstruction Model for Single Image to 3D.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features LRM: Large Reconstruction Model for Single Image to 3D

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:19.989819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.989819Z digest=sha256:534138259e1345b61db71522dd2d7d46bd8de5f4baaacbdd555b625775998501

Observation 0c7fd3c7-0241-4ea9-8ba7-42a21f35d554 · outbound

This paper cites Triplane meets gaussian splatting: Fast and generalizable single-view 3d reconstruction with transformers.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Triplane meets gaussian splatting: Fast and generalizable single-view 3d reconstruction with transformers

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:22:20.272528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T05:22:19.993725Z digest=sha256:d19aaaca28a61e371c920b56d90b942de7c864892fe179e659069dae7b56f759

Observation 0dd6cbb4-a211-4efd-a9b7-60d2e00f5dcf · outbound

This paper cites DepthSplat: Connecting Gaussian Splatting and Depth.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features DepthSplat: Connecting Gaussian Splatting and Depth

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:19.997096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:19.997096Z digest=sha256:92f9a0e0369a8b479ff2c6f744242bdd687ac6c6ae06b4414b30bcb386504c3c

Observation 7cae38f1-1d4a-4f6b-bfa4-c160e0550b9d · outbound

This paper cites Depth Anything V2.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Depth Anything V2

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:20.000920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:20.000920Z digest=sha256:36d6a4044b71f01d14be8cb06a4fd92c3c45d858da59af59f7356789934a0a5b

Observation 4fe74010-2bc5-41ad-bb23-ff6122d38737 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features The unreasonable effectiveness of deep features as a perceptual metric

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:20.005486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:20.005486Z digest=sha256:601d1ba08a7fe2c05e4da689678b14375158c468e41a8438b1900a408d4b4b5c

Observation e3f75822-c5d7-4fc7-bd74-a5845475cd24 · outbound

This paper cites DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:20.009165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:20.009165Z digest=sha256:cb8c31c27d0cffb01f1e750b12b851896798abfe41ed0eca3adc312f6ff7a792

Observation dff7a798-0de9-47af-a116-2f62a3568adc · outbound

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

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:20.012991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:20.012991Z digest=sha256:e548fbed4be6c3a5c65a8ffdccf77ab4c64df58f9824f1f4dd073d319a16ad9c

Observation cd7b152f-0f7e-4b07-a57c-e6365ea7a45e · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:20.016729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:20.016729Z digest=sha256:3889b34e861c0b4feec35cabfac217b33506c0d4830fa255e89d10c802c133eb

Observation 6e8aaf2d-26f9-4ad7-a5cc-8258ecd41986 · outbound

This paper cites ImageDream: Image-Prompt Multi-view Diffusion for 3D Generation.

Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features ImageDream: Image-Prompt Multi-view Diffusion for 3D Generation

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-08T05:22:20.020565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:22:20.020565Z digest=sha256:3d36adc5322419d43dfbf7f2eca3374d6c4edf36e45ddb75441583dd09b812df

Pith citing papers

Observation 2d089f24-f718-4f01-a862-e351e345c1cd · inbound

R-DMesh: Video-Guided 3D Animation via Rectified Dynamic Mesh Flow cites this paper.

R-DMesh: Video-Guided 3D Animation via Rectified Dynamic Mesh Flow Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features

Reference 126

Resolution
verified exact
arxiv_id, observed 2026-05-14T19:09:23.567511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-14T19:07:53.671769Z digest=sha256:4456f94657c97e9ae46b319b232ccf7efb97943e0a53aea7df11ccfd9eb9cd62

Observation e53baca4-33ab-4ca5-a693-ee5978cfaf4f · inbound

R-DMesh: Video-Guided 3D Animation via Rectified Dynamic Mesh Flow cites this paper.

R-DMesh: Video-Guided 3D Animation via Rectified Dynamic Mesh Flow Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features

Reference 126

Resolution
verified exact
arxiv_id, observed 2026-05-15T06:09:49.432070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-15T06:08:52.321351Z digest=sha256:403503107952744fe8680ef24d4b3069f7464719e984f60255a2de473d1735a0

Observation b73c1ccb-a818-4d28-aacb-92a06da7460d · inbound

Hallo4D: Multi-Modal Hallucination Mitigation for Consistent Spatio-Temporal Generation cites this paper.

Hallo4D: Multi-Modal Hallucination Mitigation for Consistent Spatio-Temporal Generation Not All Frame Features Are Equal: Video-to-4D Generation via Decoupling Dynamic-Static Features

Reference 233

Resolution
unresolved
no resolver link, observed 2026-08-02T06:23:50.361291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T06:23:50.361291Z digest=sha256:27842766be7347e3b2dd68ecd75164fa4412b37ef524e7cde6d56825e17c7a01