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Paper Citation Record · LEDGER

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos

As of 16 August 2026, this Paper Citation Record lists 100 of 106 outbound references and 6 inbound Pith citation observations for arXiv:2506.09997.

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

pith.paper-citation-record.v1
2506.09997 v1

Coverage vector

measured 100 of 106 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:42:16.038735Z

measured 106 of 106 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T16:46:06.543021Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:48:39.681000Z

Reference resolution

100 of 106 outbound references displayed

  • verified exact0
  • verified fuzzy53
  • unresolved47
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ab225a54-6e68-484d-8599-ecf35fbb9ce5 · outbound

This paper cites Surf: Speeded up robust features.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Surf: Speeded up robust features

Reference 1

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source=pdf_text observed=2026-08-07T04:42:13.842547Z digest=sha256:f231024c4cb1aee07db37e8a267340c5b885ab039beb9b25ee1fe5707faf6dbf

Observation 13171a86-67db-454c-9c2a-dcc4c1677d71 · outbound

This paper cites A framework for the robust estimation of optical flow.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos A framework for the robust estimation of optical flow

Reference 2

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source=pdf_text observed=2026-08-07T04:42:13.947708Z digest=sha256:2dd273976ab3643cc05c0e881fe501e9e452adde99ba4757531449a991b194cb

Observation d3099407-f4bd-45ce-adf7-77300ff09ce2 · outbound

This paper cites Deepdeform: Learning non-rigid rgb-d reconstruction with semi-supervised data.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Deepdeform: Learning non-rigid rgb-d reconstruction with semi-supervised data

Reference 3

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source=pdf_text observed=2026-08-07T04:42:14.106417Z digest=sha256:505efec0663ec43845d17878a8ec7838fef042b39db1cdca4d8cb17534a620c7

Observation f9ea5b5e-4394-43a7-8e99-60ec535a2af5 · outbound

This paper cites Video generation models as world simulators, 2024.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Video generation models as world simulators, 2024

Reference 4

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source=pdf_text observed=2026-08-07T04:42:14.180789Z digest=sha256:8753aff561422e3c5929bc916821dd2e3e4140cb5c30d1052d727584d87e8c54

Observation ec24a009-1fac-463c-af7c-b6a363823752 · outbound

This paper cites High accuracy optical flow estimation based on a theory for warping.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos High accuracy optical flow estimation based on a theory for warping

Reference 5

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source=pdf_text observed=2026-08-07T04:42:14.237452Z digest=sha256:61585803cf9094dc11eb670e53e8a1fb3b46307cc666382e1711a099274f620f

Observation 4da502e8-6244-4c13-b533-5fa74077a90b · outbound

This paper cites Large displacement optical flow.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Large displacement optical flow

Reference 6

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source=pdf_text observed=2026-08-07T04:42:14.353518Z digest=sha256:9257d407a2c467c466296f6e507192a83de73a2b09c1abbe394c1f7f5e5a18dd

Observation 5a0d5e5b-448a-494b-a7b4-17c9b9e092e9 · outbound

This paper cites Immersive light field video with a layered mesh representation.ACM Transactions on Graphics, 39(4):86–1, 2020.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Immersive light field video with a layered mesh representation.ACM Transactions on Graphics, 39(4):86–1, 2020

Reference 7

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source=pdf_text observed=2026-08-07T04:42:14.572630Z digest=sha256:e22424ca4bb2c3df699060a1d04f65aa9c14aea585750f473385ba2fc5e256f1

Observation 3b9d238c-4cb8-4197-8ea6-543e0971ff7b · outbound

This paper cites The 2018 DAVIS Challenge on Video Object Segmentation.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos The 2018 DAVIS Challenge on Video Object Segmentation

Reference 8

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source=pdf_text observed=2026-08-07T04:42:14.688504Z digest=sha256:ef7d0afa9b123e828eeea484bea2fb9b527a4091b5fd788ddfb2e7153c7fceaa

Observation e3a6f2d7-0a1d-44c0-8fff-574afd8180cc · outbound

This paper cites Hexplane: A fast representation for dynamic scenes.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Hexplane: A fast representation for dynamic scenes

Reference 9

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source=pdf_text observed=2026-08-07T04:42:14.821411Z digest=sha256:d35e85025c434e7bd4a6ef0ea4fe2ce7e5aa441cf09060e46d28932d34657756

Observation 50d4e00f-8a1d-4057-ae9a-5008b0311c63 · outbound

This paper cites pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction

Reference 10

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source=pdf_text observed=2026-08-07T04:42:14.981427Z digest=sha256:94ec23be3c2b2136e29475e262c4b7986b029a3dbf03a9a3b2f8f391d4bd8c50

Observation eb9df9c4-aad8-4731-bce9-aaaef4748890 · outbound

This paper cites Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo

Reference 11

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source=pdf_text observed=2026-08-07T04:42:15.102711Z digest=sha256:1b89c4cc2db7e390b42a76ce9b7c2a12ab8d5cba115fd71139f12390c9839efc

Observation a9860db9-f6a9-4c1f-b670-3ef9ad82c527 · outbound

This paper cites Training Deep Nets with Sublinear Memory Cost.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Training Deep Nets with Sublinear Memory Cost

Reference 12

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source=pdf_text observed=2026-08-07T04:42:15.238899Z digest=sha256:38f9ecf57232e01f565ba6ab75c7e612e0ebefa048cac8a808c208e47d515a15

Observation df8a6f06-1951-45af-acde-fbcd906ce6cd · outbound

This paper cites Mvsplat: Efficient 3d gaussian splatting from sparse multi-view images.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Mvsplat: Efficient 3d gaussian splatting from sparse multi-view images

Reference 13

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source=pdf_text observed=2026-08-07T04:42:15.421119Z digest=sha256:65c8ef7c662a25fcb03dd94c0061101fef2716f1a2b55d747d5947a046d1e9cc

Observation 5fc2a026-9fb8-4813-995e-087b80d8dcde · outbound

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

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Objaverse: A universe of annotated 3d objects

Reference 14

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source=pdf_text observed=2026-08-07T04:42:15.507161Z digest=sha256:aa0e741739f1820fc5f44c4b557647f4c4f2fd7c9b378887f8b61bc2c16a8d1e

Observation cad0be56-0e7c-4921-9b3f-44f08797a2c8 · outbound

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

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Objaverse-xl: A universe of 10m+ 3d objects

Reference 15

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source=pdf_text observed=2026-08-07T04:42:15.606946Z digest=sha256:6464f26c9ce6983bf0fbee9659a2934137e752cb3b84c21efa5a15fd02cc7086

Observation a663deab-1eb9-478c-b32c-08e05bbeeb45 · outbound

This paper cites Superpoint: Self-supervised interest point detection and description.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Superpoint: Self-supervised interest point detection and description

Reference 16

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source=pdf_text observed=2026-08-07T04:42:15.732153Z digest=sha256:2dcf94f680b24e50bfec4317ca720af527836716d872bb2203797bbf6ef8c532

Observation aa71bcc1-dd01-4a01-9d7b-67253e0bb5ce · outbound

This paper cites Tapir: Tracking any point with per-frame initialization and temporal refinement.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Tapir: Tracking any point with per-frame initialization and temporal refinement

Reference 17

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source=pdf_text observed=2026-08-07T04:42:15.759446Z digest=sha256:af396edab401b70c3b4ef5b9eace4bc4acb3a935526bda6c61dc7dac2f4e3d0d

Observation c383a991-9c80-473d-a85b-59275db520e7 · outbound

This paper cites Flownet: Learning optical flow with convolutional networks.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Flownet: Learning optical flow with convolutional networks

Reference 18

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source=pdf_text observed=2026-08-07T04:42:15.762559Z digest=sha256:6f572288489ee8fe279ead3879e6547fa0e8447d84df66b7a7b3eed3840d9ba8

Observation 92a487c8-5e32-412c-8479-9fa6c47356af · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 19

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source=pdf_text observed=2026-08-07T04:42:15.766192Z digest=sha256:4963d8aa8724d1c8a9713111cfaea592583442b431649a27eccc6eb97b90add6

Observation d326a9b6-35c3-4e41-acd2-83e5be759565 · outbound

This paper cites Fusion4d: Real-time performance capture of challenging scenes.ACM Transactions on Graphics, 35(4):1–13, 2016.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Fusion4d: Real-time performance capture of challenging scenes.ACM Transactions on Graphics, 35(4):1–13, 2016

Reference 20

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source=pdf_text observed=2026-08-07T04:42:15.769439Z digest=sha256:0f4fc0ef8209c51293cf9cb19a10ba64613f2470c26b99c4d3fef7fcfe7a63b7

Observation 9532f85b-9ae0-4b1a-acb6-943835644647 · outbound

This paper cites The Faiss library.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos The Faiss library

Reference 21

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source=pdf_text observed=2026-08-07T04:42:15.772239Z digest=sha256:1bc80b47d2c27d7f1e3b442359222bde7225dc79b0f4a0a22a795b01144788b3

Observation f04549d3-608a-4320-a8ec-406c99243ab0 · outbound

This paper cites Neural radiance flow for 4d view synthesis and video processing.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Neural radiance flow for 4d view synthesis and video processing

Reference 22

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Observation 862a5eaf-5f25-4bfc-85ba-e3d803e57a45 · outbound

This paper cites 4d-rotor gaussian splatting: towards efficient novel view synthesis for dynamic scenes.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos 4d-rotor gaussian splatting: towards efficient novel view synthesis for dynamic scenes

Reference 23

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source=pdf_text observed=2026-08-07T04:42:15.778382Z digest=sha256:9c16b519f20a8c78692306097911738e25ecfed31749e3d1cb8eeaf4e5b4f0a7

Observation 87615a8c-796b-453f-be78-d48bec70dab3 · outbound

This paper cites K-planes: Explicit radiance fields in space, time, and appearance.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos K-planes: Explicit radiance fields in space, time, and appearance

Reference 24

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source=pdf_text observed=2026-08-07T04:42:15.781509Z digest=sha256:e9d9b662cd2ea1a14ce0266afa962acb0562b464badc4367bf867ca7b07b395e

Observation 46db96d5-ee2d-4e2d-a999-f5b7c37371ca · outbound

This paper cites Dynamic novel-view synthesis: A reality check.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Dynamic novel-view synthesis: A reality check

Reference 25

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Observation 1327777e-1955-4c30-8757-f508b304d3f2 · outbound

This paper cites an unresolved cited work.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Unresolved cited work

Reference 26

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source=pdf_text observed=2026-08-07T04:42:15.787248Z digest=sha256:0019f6a4756831a366499466b99c4d3cadc34169800b78ca05815160c86e9397

Observation 921fb0d3-7228-4865-a94c-b9c86573d2d3 · outbound

This paper cites Hplflownet: Hierarchical permutohedral lattice flownet for scene flow estimation on large-scale point clouds.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Hplflownet: Hierarchical permutohedral lattice flownet for scene flow estimation on large-scale point clouds

Reference 27

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Observation d75c6cb5-4496-4792-83e5-69a375e2c10c · outbound

This paper cites Particle video revisited: Tracking through occlusions using point trajectories.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Particle video revisited: Tracking through occlusions using point trajectories

Reference 28

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source=pdf_text observed=2026-08-07T04:42:15.794136Z digest=sha256:c96a62adf188a4384478e894d7ecad32297ac20bafb718535114ba57d2a005e9

Observation 1f7e1096-3e22-45a5-b437-acf8dda92230 · outbound

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

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos LRM: Large reconstruction model for single image to 3d

Reference 29

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source=pdf_text observed=2026-08-07T04:42:15.797048Z digest=sha256:b03d22fe5e06c91f114c4a83610a4d740fb9dc2e21626a393992092b77c8c601

Observation 4a4c45e1-5b3d-4528-aa8f-98050017060f · outbound

This paper cites Self-supervised monocular scene flow estimation.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Self-supervised monocular scene flow estimation

Reference 30

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source=pdf_text observed=2026-08-07T04:42:15.800139Z digest=sha256:92daefeb7e25afe21c9ba8700111ca4f04b591d43cc94543826d31e1e3d8924b

Observation 132ee939-bc43-40df-b5aa-eea543d09e0a · outbound

This paper cites Flownet 2.0: Evolution of optical flow estimation with deep networks.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Flownet 2.0: Evolution of optical flow estimation with deep networks

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.803961Z digest=sha256:2a5b847bae7c21fde33cc90a3064838db8c356717e3410dba9fb353dc1b07cf0

Observation 75e8d17b-e995-4fb9-8ceb-26a9c76aa119 · outbound

This paper cites V olumedeform: Real-time volumetric non-rigid reconstruction.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos V olumedeform: Real-time volumetric non-rigid reconstruction

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.807333Z digest=sha256:03517c11f74f39514f707d2e4fc1e0ed24f0f649e7714717cabc6b28413366de

Observation 886668fc-0210-4d27-9f50-03900fd5f3c3 · outbound

This paper cites A primal-dual framework for real-time dense rgb-d scene flow.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos A primal-dual framework for real-time dense rgb-d scene flow

Reference 33

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source=pdf_text observed=2026-08-07T04:42:15.810448Z digest=sha256:d57a7fcbd6b4f0a8abee73065671be0a54cdb29ab0594275545d6972649176f1

Observation b2d56254-0792-4b85-99a1-23d0db90a82a · outbound

This paper cites Megasynth: Scaling up 3d scene reconstruction with synthesized data.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Megasynth: Scaling up 3d scene reconstruction with synthesized data

Reference 34

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source=pdf_text observed=2026-08-07T04:42:15.814137Z digest=sha256:c11b500f6782a9e9bf7d65feb5f2403b5b83a73e97220edfabac1b84e9779239

Observation 022694a9-12e2-4e67-8a68-3cca5db51576 · outbound

This paper cites A Study of BFLOAT16 for Deep Learning Training.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos A Study of BFLOAT16 for Deep Learning Training

Reference 35

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source=pdf_text observed=2026-08-07T04:42:15.817792Z digest=sha256:261bb995edd76d6260015c993ad81de53dba5200a151bdc58297be338af8c504

Observation c4722a37-92b9-4aa2-92f1-1d08db3ba728 · outbound

This paper cites Cotracker: It is better to track together.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Cotracker: It is better to track together

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.821039Z digest=sha256:2da00171adc6d48a322454284312d00ed1e6c8027f76fd655165102f2e1ffd23

Observation 4480a6b4-fcf5-4f69-a176-b9c950703109 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics, 42(4):139–1, 2023.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos 3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics, 42(4):139–1, 2023

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:17.136710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.824952Z digest=sha256:cfc4b1186c25f449f711fcef00fa7c56d4c6b2c21114639c87d6a11b69ef6d51

Observation fbc80ce3-9465-49da-8710-70128e1ae95e · outbound

This paper cites Segment anything.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Segment anything

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:15.828220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:15.828220Z digest=sha256:75f3630c04c35ea6529459ea3630d2a3c37dab04a26dccf8e4686727d5bc7960

Observation 5f391c7c-eef9-4dc6-9894-b27cd82676b2 · outbound

This paper cites Robust consistent video depth estimation.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Robust consistent video depth estimation

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:17.117187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.831460Z digest=sha256:5b9f6f959ceb4c8112dd8ea489b6026b5ec875df2cbe021e2e32b1ad7f874a4c

Observation 5c029b03-54ba-4aa5-aa71-c28789b898a0 · outbound

This paper cites xformers: A modular and hackable transformer modelling library.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos xformers: A modular and hackable transformer modelling library

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:17.103969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.834770Z digest=sha256:c4f1ef16928c6c9f0885d8568e2bfe98bd2c072704a2a4fc275304c617811f49

Observation 3fdd8010-3b0c-4d47-b581-d645eb8d4eff · outbound

This paper cites Grounding image matching in 3d with mast3r.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Grounding image matching in 3d with mast3r

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:17.090638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.838002Z digest=sha256:5a31e1e05d72fd45f38eaaea6d8e60984c2efb19e2a0daf03bce15f612461c2a

Observation 4ccaaabc-10db-428f-9e4f-d1d5c6f19896 · outbound

This paper cites Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:15.841215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:15.841215Z digest=sha256:a213fb7b49d30a86c1e67b5015df6eab033f8c9533a69c0784b179e21db251d8

Observation 4b2009fe-06bd-4e1e-ab12-9321dac31a0c · outbound

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

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Neural 3d video synthesis from multi-view video

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:17.078789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.844752Z digest=sha256:ad6b7d42f1c84689b44cade45bcf9913bb08d6d1c21c4314111639103cc4a061

Observation 8d92c401-64b2-454d-a13e-133b38bfbefa · outbound

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

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Neural scene flow fields for space-time view synthesis of dynamic scenes

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:17.066455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.847987Z digest=sha256:565fde12b939f5189f3d6715b670857771d00c53c19e4dafe7a9f4973d1c6e4b

Observation 87bff765-8943-4a17-9113-c33f1b253afa · outbound

This paper cites Dynibar: Neural dynamic image-based rendering.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Dynibar: Neural dynamic image-based rendering

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:17.054631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.851088Z digest=sha256:8f317d16877e6f29572fc5a75715813a9eca103f2e0348dfc6acabba29df0aa6

Observation 6a07a0a4-716a-40b1-a146-f41fe8cfc1b1 · outbound

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

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Spacetime gaussian feature splatting for real-time dynamic view synthesis

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:17.042688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.854388Z digest=sha256:d7120401e1a56a916d9ab131255d3c82229e16c7b40aaf8090a18abf435db001

Observation 8cfd81b2-af94-47ef-b3cc-1fafb5ec44a2 · outbound

This paper cites MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:15.857646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:15.857646Z digest=sha256:32847238fd27fc524ad5da0f2f585d394472555fdd30800a4caf68d0851b32c4

Observation 5fa72b61-27ca-4c73-af6f-f329a22857e0 · outbound

This paper cites Feed-forward bullet-time reconstruction of dynamic scenes from monocular videos.arXiv preprint arXiv:2412.03526, 2024.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Feed-forward bullet-time reconstruction of dynamic scenes from monocular videos.arXiv preprint arXiv:2412.03526, 2024

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:15.861297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:15.861297Z digest=sha256:5c18c705a72526760f0df9244c2e350657115e23b420269661de0588dddb9612

Observation b39c5175-8869-4770-a6e8-af981a4e2d88 · outbound

This paper cites Flownet3d: Learning scene flow in 3d point clouds.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Flownet3d: Learning scene flow in 3d point clouds

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:15.864490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:15.864490Z digest=sha256:c3d937fa5f64cfe9db3331c56a8a68a930027242458ef3726b63cf7a00140551

Observation d7aa7d68-a585-4af7-9772-3e825a80f4be · outbound

This paper cites Robust dynamic radiance fields.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Robust dynamic radiance fields

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:17.022926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.867393Z digest=sha256:5490d16559e55031ffb6d14cf6363bfc0fab97ae1f8296c29d5170f1f8f9b98e

Observation 376f6ffa-a795-49cc-8cf9-e4abdbf00575 · outbound

This paper cites Neural Volumes: Learning Dynamic Renderable Volumes from Images.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Neural Volumes: Learning Dynamic Renderable Volumes from Images

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:15.871938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:15.871938Z digest=sha256:ffea670a5dfa560906c632c55d754023ddeebf6e82de7f5aa9d1983c2eff2cf3

Observation dae0c944-55d1-4639-b87d-7d2e829027dd · outbound

This paper cites Distinctive image features from scale-invariant keypoints.IJCV, 60:91–110, 2004.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Distinctive image features from scale-invariant keypoints.IJCV, 60:91–110, 2004

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:17.010291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.875321Z digest=sha256:7e6d341da0aef41397e54d0a0ce9518667f737e8024fd3bdca02f8a925da25f7

Observation 6e546a88-65a1-4932-ab88-75e2825c2604 · outbound

This paper cites Consistent video depth estimation.ACM Transactions on Graphics, 39(4):71–1, 2020.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Consistent video depth estimation.ACM Transactions on Graphics, 39(4):71–1, 2020

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.998148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.878633Z digest=sha256:55862de03f6179f0f11a25e091175ae670eeb4aee2bef34463311d9402f64bac

Observation 76838b18-5fde-4305-b194-e88e9f47c425 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis.Communications of the ACM, 65(1):99–106, 2021.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Nerf: Representing scenes as neural radiance fields for view synthesis.Communications of the ACM, 65(1):99–106, 2021

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:15.882056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:15.882056Z digest=sha256:8ba330ddcc7d9b90d4f1e9ce674a897d8818816219cc37094abfa99dcf02126c

Observation ad8fadf1-39e7-4a9a-95d7-6329a10c607c · outbound

This paper cites Mft: Long-term tracking of every pixel.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Mft: Long-term tracking of every pixel

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.978906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.885065Z digest=sha256:367cd96d2c8569210e991cefe1bf153efaee562541963cd9515e803d3d48f96c

Observation 7e0f9868-6fb1-414e-9f22-5df631dc00c6 · outbound

This paper cites Dynamicfusion: Reconstruction and tracking of non-rigid scenes in real-time.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Dynamicfusion: Reconstruction and tracking of non-rigid scenes in real-time

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.966927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.888122Z digest=sha256:005a1bbf751bdce3432a9642cf621aeb2759f7a350f7ffabd5ea5a7f48887d91

Observation 67f58d89-ba45-43ed-a969-63935dee43e7 · outbound

This paper cites Nerfies: Deformable neural radiance fields.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Nerfies: Deformable neural radiance fields

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.954518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.891261Z digest=sha256:d90aea03eb6614994466b5e6e92566c83923692340e11bf43c389ce5d708628e

Observation 5f586fa0-d56b-408c-860b-16607570e812 · outbound

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

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:15.895098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:15.895098Z digest=sha256:881bdd28eb5fcef9726160a57070955179dd1e4e4257774c2ee3e908a2d535b7

Observation db3d4237-256d-4b8c-8023-e3fe7bca6ac5 · outbound

This paper cites A benchmark dataset and evaluation methodology for video object segmentation.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos A benchmark dataset and evaluation methodology for video object segmentation

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.942529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.898724Z digest=sha256:73b784d4cd41fe1df7d8879cedbb173e67f7c9e4864c1cc097f9c5c6a917a28f

Observation 397e22b9-2fc7-4947-91aa-b506b563be7c · outbound

This paper cites Unidepth: Universal monocular metric depth estimation.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Unidepth: Universal monocular metric depth estimation

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.930790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.901928Z digest=sha256:c8b82a37bc4c10d445f9380ef8832473e5333d48b85efda32c6dcb7c401fb3b4

Observation 7df72e48-6d52-4182-8d22-6ade3cf4e40d · outbound

This paper cites Sampson, Shikai Li, Simone Parmeggiani, Steve Fine, Tara Fowler, Vladan Petrovic, and Yuming Du.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Sampson, Shikai Li, Simone Parmeggiani, Steve Fine, Tara Fowler, Vladan Petrovic, and Yuming Du

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.919680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.905007Z digest=sha256:603a86db51a980398c1adedd715e521e3ae743817c49576c6e8dbc6db5f3827e

Observation dc59a457-3e92-4677-9602-ab75b32942bb · outbound

This paper cites Flot: Scene flow on point clouds guided by optimal transport.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Flot: Scene flow on point clouds guided by optimal transport

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.908278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.908366Z digest=sha256:6261971edf479e3aa98eb6df8d496928838012b4e974547c7364f8a684e364d8

Observation 7957e879-a0ed-42f7-bd03-b29ec659cef0 · outbound

This paper cites Dense semi-rigid scene flow estimation from rgbd images.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Dense semi-rigid scene flow estimation from rgbd images

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.896536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.911472Z digest=sha256:c87b4791f86612a6a81e7c938fe16c7f73607d036e7d3ee60a417fe609515cb6

Observation cc19d154-95e8-461c-b692-25a6f8504df7 · outbound

This paper cites Improving language understanding by generative pre-training, 2018.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Improving language understanding by generative pre-training, 2018

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.885683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.914541Z digest=sha256:98de9c093d8918da7c6d646559a2dffd60b2c9885c4b57443a158b91ddc990c1

Observation 1148bf14-06b2-455e-ad88-fa05f65572a5 · outbound

This paper cites Vision transformers for dense prediction.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Vision transformers for dense prediction

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.874352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.918481Z digest=sha256:62ba00dc2fdc8e68f8a130e2b48d8eebdcc9bf483983008c69dc29db870060db

Observation 3dde424b-4b66-4c19-9b7b-46a830079459 · outbound

This paper cites L4gm: Large 4d gaussian reconstruction model.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos L4gm: Large 4d gaussian reconstruction model

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.862485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.922481Z digest=sha256:2865d183141306b5a696603df35539fba49aae24a37e14661d7a548702f66063

Observation 021a455f-f3cf-4e57-93ac-6f90dfa1c97d · outbound

This paper cites Towards longer long-range motion trajectories.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Towards longer long-range motion trajectories

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.850917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.925845Z digest=sha256:beab427a170c5cc0bcff7343d0fed2cf1af10a79e7a8f6c36305df6045b4d48c

Observation babb91a7-cc45-44a8-a600-854db1cca2e4 · outbound

This paper cites Orb: An efficient alternative to sift or surf.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Orb: An efficient alternative to sift or surf

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.840746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.929373Z digest=sha256:41a5c02e0d3356f7ff627f591df0639beea86270e17fab7ae6134b5d89126b16

Observation 47bc4597-fa52-4f48-a680-d0c31b8c9f36 · outbound

This paper cites Weight normalization: A simple reparameterization to accelerate training of deep neural networks.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Weight normalization: A simple reparameterization to accelerate training of deep neural networks

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.830860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.932482Z digest=sha256:2883833d0498ba0a31a70ae4bdfbf570d1c7edc4bae8dae3a368c159dabf1308

Observation 5f650fb3-092c-4b6a-8306-a36a70bdf7d3 · outbound

This paper cites Particle video: Long-range motion estimation using point trajectories.IJCV, 80:72–91, 2008.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Particle video: Long-range motion estimation using point trajectories.IJCV, 80:72–91, 2008

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.820905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.935626Z digest=sha256:60c2579db307407d064b253e77c3529ec1f27261050841dee7c7c95b627a749a

Observation fffb110d-4e2a-42d6-8a9e-6cd80652481e · outbound

This paper cites Nerfplayer: A streamable dynamic scene representation with decomposed neural radiance fields.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Nerfplayer: A streamable dynamic scene representation with decomposed neural radiance fields

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.811076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.938828Z digest=sha256:8b4ae21e8099d1a86fb37835ddbb3d0b0b2578b4041e5e23ee07ade28df93585

Observation a6b15eae-9ed5-4691-bd7e-3588f22eb95a · outbound

This paper cites View and time interpolation in image space.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos View and time interpolation in image space

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.800955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.941977Z digest=sha256:c5150090cd2c0219f5c16583ac958b0f52f5ebc4c3698b08797b0c667469c148

Observation 0cf78514-f97f-41ac-ad16-6de01990895b · outbound

This paper cites Layered rgbd scene flow estimation.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Layered rgbd scene flow estimation

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.790440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.945142Z digest=sha256:9b17d53bee8dfb5eceaeaca4bbce8f7a369b8d8e8a181be31483f2f4a646c787

Observation 5672836a-b395-4a19-ba30-2744f3602e82 · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Raft: Recurrent all-pairs field transforms for optical flow

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.779389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.948359Z digest=sha256:33a31ff1af9d537be4e3bda90f0f656ba2cd7b664d5471c08eb03e78620d299e

Observation 97642336-45ed-4889-8071-433401c74afe · outbound

This paper cites Raft-3d: Scene flow using rigid-motion embeddings.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Raft-3d: Scene flow using rigid-motion embeddings

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.767598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.951764Z digest=sha256:e744011afc05dda1e3cf9f2bcc12c1ee57368e9bf92178228df35a3e5f97936c

Observation 2c436e1a-a275-4523-ab5f-9a1790c53b41 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.757000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.954867Z digest=sha256:ba7b04e6f057a22a953db132889e324d86eb3aec5664e089198625b0f91fd53b

Observation 3431f7dc-3ee8-4f3b-820b-7fcdff5079fd · outbound

This paper cites Neural Trajectory Fields for Dynamic Novel View Synthesis.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Neural Trajectory Fields for Dynamic Novel View Synthesis

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:15.958630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:15.958630Z digest=sha256:283b7c108eaa523d9d26ddc95aa34d25421c4503b755a3510e2b8a7bff18b49a

Observation ec40d852-aa02-44d2-b30d-8e01fc348788 · outbound

This paper cites Fourier plenoctrees for dynamic radiance field rendering in real-time.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Fourier plenoctrees for dynamic radiance field rendering in real-time

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.746204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.962081Z digest=sha256:c3ecdc7e436f4909d988e8ce54cf788fc854a355e658203e59f8a7f93b0e9912

Observation 2c901fa8-1ca2-4fcd-89ec-80510cc4312c · outbound

This paper cites PF-LRM: Pose-Free Large Reconstruction Model for Joint Pose and Shape Prediction.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos PF-LRM: Pose-Free Large Reconstruction Model for Joint Pose and Shape Prediction

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:15.965396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:15.965396Z digest=sha256:0cf510d06f8dcbb22c0b3b661238ee575e9d0d5bfd9b25b1339c79a47a3f859a

Observation 76a3d19d-272d-49e4-ae2c-88394e8fd0d0 · outbound

This paper cites Ibrnet: Learning multi-view image- based rendering.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Ibrnet: Learning multi-view image- based rendering

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.735840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.969109Z digest=sha256:8f19fce351f40b5690b1e1c190d4fe11b99eb2532bd4e8d93ee6cc4f4965a8e1

Observation 8d86129c-aa82-406a-b781-43a41153c3d2 · outbound

This paper cites Tracking everything everywhere all at once.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Tracking everything everywhere all at once

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.725413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.972481Z digest=sha256:30e4f188bc42ae1417405d9ec6e3238e81d334b5120d0343809a7feb1bbacac7

Observation b15cde57-83d4-42e0-8498-da52c06a0e69 · outbound

This paper cites Shape of motion: 4d reconstruction from a single video.arXiv preprint arXiv:2407.13764, 2024.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Shape of motion: 4d reconstruction from a single video.arXiv preprint arXiv:2407.13764, 2024

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:15.975845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:15.975845Z digest=sha256:dca2dc9ad1ff23d7e2d6fe23e511cc82f315dc6b305d889d858f4ae3d5372a30

Observation 066c9f55-38cc-4876-a719-23ec4a372ea3 · outbound

This paper cites Efros, and Angjoo Kanazawa.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Efros, and Angjoo Kanazawa

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.715270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.979440Z digest=sha256:7b83d3970a279b5fea956a77812b8d4a9a7cc76aeec6a49b61e26d76704fc5cf

Observation 27c5270c-69ea-4a85-b53b-e1b1e2dd2b67 · outbound

This paper cites Dust3r: Geometric 3d vision made easy.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Dust3r: Geometric 3d vision made easy

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.705678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.982989Z digest=sha256:9a06179fd87bd51360e671eb708b1ad3217fff53ca5d9ff1a9d8ac8f76c126c5

Observation 5784b46b-ee7d-4961-b988-83e88a5e5407 · outbound

This paper cites Flownet3d++: Geometric losses for deep scene flow estimation.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Flownet3d++: Geometric losses for deep scene flow estimation

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.696136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.986391Z digest=sha256:647ac88b77028899dbb5395f154f18e552b93d497dca63228ba31bf2ef1090cf

Observation 567576da-42cd-4bcf-ad4e-2fadbfb89057 · outbound

This paper cites MeshLRM: Large Reconstruction Model for High-Quality Meshes.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos MeshLRM: Large Reconstruction Model for High-Quality Meshes

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:15.989707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:15.989707Z digest=sha256:ea7ffe8448bd573a268c5a5ad1866469ea44a03a32f810d0318a015458f2a08c

Observation 8b3b2099-c62a-4247-b7ef-08b6c190937a · outbound

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

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos 4d gaussian splatting for real-time dynamic scene rendering

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.686464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.993209Z digest=sha256:45ceebbebddb5c60455b69bb43215bac388f6cdb8e3f694c10ed00b57f952f1d

Observation 5679aee6-0d5b-44e6-9176-e3ade584e1bd · outbound

This paper cites Space-time neural irradiance fields for free-viewpoint video.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Space-time neural irradiance fields for free-viewpoint video

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.676542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:15.996780Z digest=sha256:f434726a94186fc8449804e33bd9239899a791c90141bc0648dc373fa4649c1c

Observation 05282c33-36df-4ebc-b9c5-3607f08fb346 · outbound

This paper cites Spatialtracker: Tracking any 2d pixels in 3d space.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Spatialtracker: Tracking any 2d pixels in 3d space

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.664962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:16.000359Z digest=sha256:cc172afe2e3303d6c81f78f70a6c424b65f9dc00d63273ac7e7a44a04fb51038

Observation ecda378e-9e80-452d-af78-6e2fc70d2a08 · outbound

This paper cites LRM-Zero: Training Large Reconstruction Models with Synthesized Data.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos LRM-Zero: Training Large Reconstruction Models with Synthesized Data

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:16.003964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:16.003964Z digest=sha256:d974bbcb43561cf149ba6d606b825d53e6fdc1a15a5ed319d63c0d951b843bb5

Observation a0127930-4c4d-48d8-8ef2-757fbc1ec554 · outbound

This paper cites Point-nerf: Point-based neural radiance fields.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Point-nerf: Point-based neural radiance fields

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.653250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:16.007804Z digest=sha256:701a9a5a7b63b831b77f4d339f6ebf1a0686fe74779780239f2ad0a077dea777

Observation 5411be26-bfc2-413b-82a3-1067da10fec9 · outbound

This paper cites DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Model.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Model

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:16.010993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:16.010993Z digest=sha256:186def87660a2a83f0d60e8d774c8c2639ef23ba2c0cf1c01ac5fd1ba8b09b70

Observation 01b3f640-8b92-483d-92a6-003e36c784ee · outbound

This paper cites Grm: Large gaussian reconstruction model for efficient 3d reconstruction and generation.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Grm: Large gaussian reconstruction model for efficient 3d reconstruction and generation

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.641475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:16.014609Z digest=sha256:f2c25df1b15e92ca72031a266d16cc170c3d851dee627ad16420beebbcc3ccce

Observation 9bad3c79-3c8d-434f-a4cb-cdb1b6b8fe3e · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Depth anything: Unleashing the power of large-scale unlabeled data

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.628687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:16.017857Z digest=sha256:da952081c8a20224222f322133f283f0b2514a7685429b8d9902fd59f2d7c3c6

Observation ff3adc9e-28d6-4642-8778-b5203859dd33 · outbound

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

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:16.021103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:16.021103Z digest=sha256:5db6ea8ce1286a253f89076d2337a7346e43abbf4613f5d4a8ee89f5732a9d5f

Observation 90f69fb7-05e4-4f0d-99c9-4ab67204325f · outbound

This paper cites Deformable 3d gaussians for high-fidelity monocular dynamic scene reconstruction.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Deformable 3d gaussians for high-fidelity monocular dynamic scene reconstruction

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.618083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:16.024596Z digest=sha256:b55c38b9045cf78eb5a738b173124de6715f06f454364785f30914fd7e05dcf1

Observation 0ed5bfad-4ea5-4c25-80af-0bf9845c663e · outbound

This paper cites pixelnerf: Neural radiance fields from one or few images.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos pixelnerf: Neural radiance fields from one or few images

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.607909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:16.027889Z digest=sha256:929142f1d665e151cf1533ec2978411eb96006996a22cff2988da7d892cbf0e0

Observation 6e3b3bf7-ae0a-4fca-b188-3904563418e1 · outbound

This paper cites MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motion.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motion

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:16.031126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:16.031126Z digest=sha256:c058070b3a32da95e7821d7d2368335e8b61ddb69ea233ef4dfdf878ff0c1860

Observation 56f5ca32-321e-47d5-8989-f69fa252e633 · outbound

This paper cites Arf: Artistic radiance fields.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Arf: Artistic radiance fields

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.597892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:16.035467Z digest=sha256:63ee5aaa9ff2653022e829484c718e76066c327364d9f31bf8fba7f61cd30055

Observation afa00340-20ad-437b-a9c2-453ad9e67de5 · outbound

This paper cites Gs-lrm: Large reconstruction model for 3d gaussian splatting.

DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos Gs-lrm: Large reconstruction model for 3d gaussian splatting

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:42:16.587291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:42:16.038735Z digest=sha256:4d65d5648161f314a41b3ce3cba0602255c8ff6d7211e52ba33742fbd34d90f5

Pith citing papers

Observation 495dd445-341e-4aa7-881d-a38cafd58be1 · inbound

LSRM: High-Fidelity Object-Centric Reconstruction via Scaled Context Windows cites this paper.

LSRM: High-Fidelity Object-Centric Reconstruction via Scaled Context Windows DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:50:49.627839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T19:32:20.565326Z digest=sha256:d66addd88bf62ca3aea4fc9b254961499143d6551e6912bda0c55aa75e824a5e

Observation c425b57c-bab4-4f9d-87df-1752179307cc · inbound

LSRM: High-Fidelity Object-Centric Reconstruction via Scaled Context Windows cites this paper.

LSRM: High-Fidelity Object-Centric Reconstruction via Scaled Context Windows DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos

Reference 46

Resolution
unresolved
no resolver link, observed 2026-07-13T09:33:39.204257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T09:33:39.204257Z digest=sha256:e6cc8933357468b58325342b2b0c9b410d0ee91e18ab26c267bac93bf285ac15

Observation 76c53341-7ea4-458b-9970-73276957e071 · inbound

LSRM: High-Fidelity Object-Centric Reconstruction via Scaled Context Windows cites this paper.

LSRM: High-Fidelity Object-Centric Reconstruction via Scaled Context Windows DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-02T16:46:06.543021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:46:06.543021Z digest=sha256:bc9179adf549d5ae041012f49418a1418ca866a44eef05f663ff2c69d6d6c8bb

Observation f80d094a-5bf8-4d66-9d79-5e94ad5bb2da · inbound

Feed-Forward 3D Scene Modeling: A Problem-Driven Perspective cites this paper.

Feed-Forward 3D Scene Modeling: A Problem-Driven Perspective DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos

Reference 183

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:20:25.961373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T13:13:42.052386Z digest=sha256:348cadc988498f4d282995f92b420a6d9987d00c0323320b4120a9005cce264e

Observation 4bd01ae8-aee6-4aaa-8ad3-81fbc898ee92 · inbound

Learning Global Motion with Compact Gaussians for Feed-Forward 4D Reconstruction cites this paper.

Learning Global Motion with Compact Gaussians for Feed-Forward 4D Reconstruction DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-06-28T23:12:47.197239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-28T23:07:50.491677Z digest=sha256:e47c2bea5a9c3a8970ba9b6f1e11dfc2f9e5458f54fc75e116b292742048ad80

Observation cc3a5a6b-f895-4517-b54c-aae9f941da5c · inbound

Unified Panoramic-Gaussian Representation for Monocular 4D Scene Synthesis cites this paper.

Unified Panoramic-Gaussian Representation for Monocular 4D Scene Synthesis DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:48:39.682247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-03T16:39:30.320307Z digest=sha256:895771b64c3feefd53d52e8f4b5b457e6a39b3fd739ca53fde5e5f505035be6c