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Paper Citation Record · LEDGER

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models

As of 7 August 2026, this Paper Citation Record lists 100 of 123 outbound references and 0 inbound Pith citation observations for arXiv:2608.04701.

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

pith.paper-citation-record.v1
2608.04701 v1

Coverage vector

measured 100 of 123 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:39:33.523972Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

100 of 123 outbound references displayed

  • verified exact0
  • verified fuzzy24
  • unresolved76
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  • malformed identifier0
  • metadata mismatch0

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Outbound references

Observation 769d24f3-4276-47ab-bf58-0a41c1a8b5b5 · outbound

This paper cites HyperReel: High-fidelity 6-DoF video with ray-conditioned sampling.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models HyperReel: High-fidelity 6-DoF video with ray-conditioned sampling

Reference 1

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Observation 8fe0dbfc-1477-45e3-8e98-c7ff9caec63f · outbound

This paper cites Vd3d: Taming large video diffusion transformers for 3d camera control.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Vd3d: Taming large video diffusion transformers for 3d camera control

Reference 2

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Observation 58fffe63-7d21-4a44-940a-2446f34cd810 · outbound

This paper cites Recammaster: Camera-controlled generative rendering from a single video.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Recammaster: Camera-controlled generative rendering from a single video

Reference 3

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Observation 2d13d07f-fc27-4ad6-a401-44441acef3f1 · outbound

This paper cites Syncammaster: Synchronizing multi-camera video generation from diverse viewpoints.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Syncammaster: Synchronizing multi-camera video generation from diverse viewpoints

Reference 4

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Observation c850955e-a832-4f73-b448-a4c2c64ee766 · outbound

This paper cites Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields

Reference 5

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Observation 4c37c0fe-f8ea-425e-adac-7c4a6c747565 · outbound

This paper cites Mip-nerf 360: Unbounded anti-aliased neural radiance fields.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Mip-nerf 360: Unbounded anti-aliased neural radiance fields

Reference 6

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Observation dee55b3a-b20b-4ba0-9a50-e50b47f54f1c · outbound

This paper cites Zip-nerf: Anti-aliased grid-based neural radiance fields.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Zip-nerf: Anti-aliased grid-based neural radiance fields

Reference 7

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Observation 86ae3955-174c-4a0e-bc92-fa54fda7bed9 · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 8

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Observation 468aa9ce-c49d-4f7f-9434-4c9d4327bc47 · outbound

This paper cites Align your latents: High-resolution video synthesis with latent diffusion models.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Align your latents: High-resolution video synthesis with latent diffusion models

Reference 9

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Observation 451a9d82-aa24-47e3-ad7d-324be47c485b · outbound

This paper cites Video generation models as world simulators.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Video generation models as world simulators

Reference 10

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Observation a81e46f1-751d-4f63-96af-00b4be64830e · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Hexplane: A fast representation for dynamic scenes

Reference 11

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source=pdf_text observed=2026-08-06T18:39:26.241951Z digest=sha256:c442fc7940d31d6614258bcddd0292e341a86758f3733ec9870cf0e9c432ab09

Observation 486d6bec-ffb2-4397-ab75-b1cce53f4cf2 · outbound

This paper cites Uni3c: Unifying precisely 3d-enhanced camera and human motion controls for video generation.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Uni3c: Unifying precisely 3d-enhanced camera and human motion controls for video generation

Reference 12

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Observation 44c6ad67-89e9-49b5-ba45-6af6318db70c · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo

Reference 13

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Observation 1c8e4d68-a0a9-4c4e-ae54-9eec7c072e7c · outbound

This paper cites VideoCrafter1: Open Diffusion Models for High-Quality Video Generation.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models VideoCrafter1: Open Diffusion Models for High-Quality Video Generation

Reference 14

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Observation a1ac38ed-ec1a-4c70-8835-a89107fa843d · outbound

This paper cites Video Depth Anything: Consistent Depth Estimation for Super-Long Videos.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Video Depth Anything: Consistent Depth Estimation for Super-Long Videos

Reference 15

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source=pdf_text observed=2026-08-06T18:39:26.592889Z digest=sha256:c0ae3a768df0eabd2eac1c19faf6405f003fd4b106db03a664844d52c01780ce

Observation 7cf94cf7-c846-47ac-8e08-cd2af6e452af · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Mvsplat: Efficient 3d gaussian splatting from sparse multi-view images

Reference 16

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Observation 8d44ce30-75cb-4e4a-b669-84c568b04b99 · outbound

This paper cites LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenes.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenes

Reference 17

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Observation a933a4d4-0003-489d-acf4-7743de4756e2 · outbound

This paper cites Cogvideox-fun, 2024.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Cogvideox-fun, 2024

Reference 18

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Observation 90bb4576-bd9d-46b2-8aab-4ccf285eef67 · outbound

This paper cites Meva: A large-scale multiview, multimodal video dataset for activity detection.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Meva: A large-scale multiview, multimodal video dataset for activity detection

Reference 19

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Observation 00ce304d-bf9e-4c9a-b0fa-fc9ad0599a1e · outbound

This paper cites InstantSplat: Sparse-view Gaussian Splatting in Seconds.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models InstantSplat: Sparse-view Gaussian Splatting in Seconds

Reference 20

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Observation 161ed4e1-fdca-4013-bc31-0ea89dae746a · outbound

This paper cites Ae-nerf: Augmenting event-based neural radiance fields for non-ideal conditions and larger scene.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Ae-nerf: Augmenting event-based neural radiance fields for non-ideal conditions and larger scene

Reference 21

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Observation 8255a259-f316-408d-9a78-1a950ac137d0 · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models K-planes: Explicit radiance fields in space, time, and appearance

Reference 22

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Observation 2f952cd2-4d11-4e74-bea3-b380794aefb1 · outbound

This paper cites Dynamic view synthesis from dynamic monocular video.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Dynamic view synthesis from dynamic monocular video

Reference 23

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Observation 79747d4e-60ed-4b31-817b-2d46dbad912d · outbound

This paper cites GaussianFlow: Splatting Gaussian Dynamics for 4D Content Creation.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models GaussianFlow: Splatting Gaussian Dynamics for 4D Content Creation

Reference 24

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source=pdf_text observed=2026-08-06T18:39:27.524488Z digest=sha256:b32648953adaaca4068abf75e599d4157b02397bfb2225090ba3e599d207d2a8

Observation fd5358de-745a-4376-b3f2-5d97d80925c5 · outbound

This paper cites CAT3D: Create Anything in 3D with Multi-View Diffusion Models.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models CAT3D: Create Anything in 3D with Multi-View Diffusion Models

Reference 25

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Observation ee03573d-c21c-445c-93a3-0a3de8f2b8d1 · outbound

This paper cites Fastnerf: High-fidelity neural rendering at 200fps.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Fastnerf: High-fidelity neural rendering at 200fps

Reference 26

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source=pdf_text observed=2026-08-06T18:39:27.763840Z digest=sha256:cf48e2ad89863047ef987fcbef6fb39b8e9e5357e7f7f1ae6f6cabbde8cefafa

Observation b1c86394-00d8-475e-a719-fc6abb078946 · outbound

This paper cites Ego4d: Around the world in 3,000 hours of egocentric video.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Ego4d: Around the world in 3,000 hours of egocentric video

Reference 27

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Observation 9a2efdd7-a369-45fe-ba12-4790379f3794 · outbound

This paper cites Kubric: A scalable dataset generator.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Kubric: A scalable dataset generator

Reference 28

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Observation cb473ccd-7ebf-4a5e-a291-2f8bb1472d1e · outbound

This paper cites Diffusion as shader: 3d-aware video diffusion for versatile video generation control.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Diffusion as shader: 3d-aware video diffusion for versatile video generation control

Reference 29

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Observation 998a7fb4-e8c5-4c4a-8ba6-19a0a77069be · outbound

This paper cites Sparsenerf: Distilling depth ranking for few-shot novel view synthesis.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Sparsenerf: Distilling depth ranking for few-shot novel view synthesis

Reference 30

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Observation e0cce43d-e7ad-4f7d-8894-8a3bd9897fa5 · outbound

This paper cites Cameractrl: Enabling camera control for text-to-video generation.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Cameractrl: Enabling camera control for text-to-video generation

Reference 31

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source=pdf_text observed=2026-08-06T18:39:28.183868Z digest=sha256:e175f43ba15240dfef108e56c73ef8379e26a3ff0530d11b33f143ce6eeafcc3

Observation d0f11b97-3e74-40db-9aca-165df33a9c41 · outbound

This paper cites Denoising diffusion probabilistic models.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Denoising diffusion probabilistic models

Reference 32

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Observation 5980f02b-83ce-4f61-a2cf-f164a8e98b76 · outbound

This paper cites Tri-miprf: Tri-mip representation for efficient anti-aliasing neural radiance fields.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Tri-miprf: Tri-mip representation for efficient anti-aliasing neural radiance fields

Reference 33

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Observation ce60f8a1-2a92-48d5-a927-09230e65782c · outbound

This paper cites DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videos.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videos

Reference 34

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Observation dc20168e-7ce9-4952-a3ef-a3f10fd3146e · outbound

This paper cites ViPE: Video Pose Engine for 3D Geometric Perception.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models ViPE: Video Pose Engine for 3D Geometric Perception

Reference 35

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Observation ec05a56c-969e-45a1-b196-578961dfac91 · outbound

This paper cites Roompainter: View-integrated diffusion for consistent indoor scene texturing.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Roompainter: View-integrated diffusion for consistent indoor scene texturing

Reference 36

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Observation 2bf6148f-3857-4b32-a54b-a66be40d8854 · outbound

This paper cites Vace: All-in-one video creation and editing.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Vace: All-in-one video creation and editing

Reference 37

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source=pdf_text observed=2026-08-06T18:39:28.705252Z digest=sha256:a13f552235407abac49edb596c774597e274c6161bbceab75633de05a2297838

Observation 0555b1df-885b-42be-ac8b-ab0ad77a673f · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.ACM TOG, 2023.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models 3d gaussian splatting for real-time radiance field rendering.ACM TOG, 2023

Reference 38

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source=pdf_text observed=2026-08-06T18:39:28.773560Z digest=sha256:f020a8a5dd838c91e42bc2678c275fe5c129750ddee47855d8bbbf415cac7104

Observation 90a4c676-3bfd-465c-84b0-1b9015642161 · outbound

This paper cites STream3R: Scalable Sequential 3D Reconstruction with Causal Transformer.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models STream3R: Scalable Sequential 3D Reconstruction with Causal Transformer

Reference 39

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source=pdf_text observed=2026-08-06T18:39:28.822177Z digest=sha256:afab1bb1c4f95c1c50875dfb633cbb542d6190bf526870f2d12b978a19abe5f2

Observation 5fca4c42-65e5-45a4-b0b3-32f07d719eb8 · outbound

This paper cites Fast view synthesis of casual videos with soup-of-planes.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Fast view synthesis of casual videos with soup-of-planes

Reference 40

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source=pdf_text observed=2026-08-06T18:39:28.884751Z digest=sha256:194ccc3a61dc996bf0a64923921104958a7fc657e51e235f74e7ee46cdab74d3

Observation 573b54e6-2e2a-43be-b343-6e1b6f32cf32 · outbound

This paper cites MoSca: Dynamic Gaussian Fusion from Casual Videos via 4D Motion Scaffolds.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models MoSca: Dynamic Gaussian Fusion from Casual Videos via 4D Motion Scaffolds

Reference 41

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source=pdf_text observed=2026-08-06T18:39:28.956722Z digest=sha256:2ab3191f54615040f9c499626a77ee32fe87e41c51da3734e1e5b98069d77945

Observation 5a9eb8fe-c915-44b6-99c6-0cf89181d094 · outbound

This paper cites NerfAcc: A General NeRF Acceleration Toolbox.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models NerfAcc: A General NeRF Acceleration Toolbox

Reference 42

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source=pdf_text observed=2026-08-06T18:39:29.042224Z digest=sha256:551337f4368e173cff7660b4b5df1970624aa079bea1515da94726b34ca32546

Observation 58e8a04a-9c18-4b99-bf68-209b9d030735 · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Spacetime gaussian feature splatting for real-time dynamic view synthesis

Reference 43

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T18:39:29.111731Z digest=sha256:9cd27ef2f649ed884a718e6d466f7bc98b64e35fcb9b8b282b43a28ba1813c87

Observation 0f407144-8978-430f-99e2-7af2060853b1 · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Neural scene flow fields for space-time view synthesis of dynamic scenes

Reference 44

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no resolver link, observed 2026-08-06T18:39:29.174331Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:29.174331Z digest=sha256:8527c91bb48e0e132a9bc18255fd1ecafe7ebb2c0f43ce2ad9f21c6473a85246

Observation da13ffca-f908-4bb7-805c-07c98691cfb8 · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Dynibar: Neural dynamic image-based rendering

Reference 45

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no resolver link, observed 2026-08-06T18:39:29.237316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:29.237316Z digest=sha256:890a9425ea3b57bf84de0c87c8d0879c9569f708ce8bdf3f4cfc9a79d1ab81df

Observation 54c225c0-d606-4085-8c50-408b800a7ada · outbound

This paper cites Wonderland: Navigating 3D Scenes from a Single Image.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Wonderland: Navigating 3D Scenes from a Single Image

Reference 46

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no resolver link, observed 2026-08-06T18:39:29.317516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:29.317516Z digest=sha256:b04ee02a61d6c7b1a461cf7947590c9567af3d190a309f6db345374a61a6eed0

Observation 53003682-e36b-4b5f-b7b3-d4371a895f8c · outbound

This paper cites Analytic-splatting: Anti-aliased 3d gaussian splatting via analytic integration.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Analytic-splatting: Anti-aliased 3d gaussian splatting via analytic integration

Reference 47

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:29.378999Z digest=sha256:45f7347fdfd804666f4ca16c4c1613f1831096baa81e80315e5fac636c38fc11

Observation 76d42315-5f7e-4a08-8361-bb61bc3572d4 · outbound

This paper cites Open-Sora Plan: Open-Source Large Video Generation Model.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Open-Sora Plan: Open-Source Large Video Generation Model

Reference 48

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no resolver link, observed 2026-08-06T18:39:29.458323Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:29.458323Z digest=sha256:f899260654679c13622f237f9cb3807285250867bf7f70fe09e6a9167c55d8f9

Observation 1e61ebbd-26fe-43ac-bfc5-0d7335376999 · outbound

This paper cites Barf: Bundle-adjusting neural radiance fields.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Barf: Bundle-adjusting neural radiance fields

Reference 49

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no resolver link, observed 2026-08-06T18:39:29.557805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:29.557805Z digest=sha256:3f937b5167aacc8d5ea6187850042d69115ed7102ea26ef00b9d7d15d8985fd6

Observation 81e622cb-5d58-4905-a9af-07bb2ec38caf · outbound

This paper cites Dl3dv-10k: A large-scale scene dataset for deep learning-based 3d vision.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Dl3dv-10k: A large-scale scene dataset for deep learning-based 3d vision

Reference 50

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no resolver link, observed 2026-08-06T18:39:29.636927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:29.636927Z digest=sha256:f5cf2ae1b7dd7935ec471ff6b1fdba86913756dd8ea74e7307aa46fcf1f0c227

Observation 9e4e74a2-3e56-420b-b332-2567a524535a · outbound

This paper cites Rip-nerf: Anti-aliasing radiance fields with ripmap-encoded platonic solids.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Rip-nerf: Anti-aliasing radiance fields with ripmap-encoded platonic solids

Reference 51

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T18:39:29.722061Z digest=sha256:bf609cb275e344d5a085c70dd8ea444ebd97e1f7e329642c50bba9da6bc2e55b

Observation 637e9292-1f90-4598-aa7c-4bf05c4f7eed · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Zero-1-to-3: Zero-shot one image to 3d object

Reference 52

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no resolver link, observed 2026-08-06T18:39:29.816185Z

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source=pdf_text observed=2026-08-06T18:39:29.816185Z digest=sha256:f9fd7c58d23bafedf15d7397cec6a5fb938f77918ecf33ccb5b4d2729230ccef

Observation a8d59a42-a799-4d22-92f7-b7d5b78e6c1c · outbound

This paper cites Free4D: Tuning-free 4D Scene Generation with Spatial-Temporal Consistency.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Free4D: Tuning-free 4D Scene Generation with Spatial-Temporal Consistency

Reference 53

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no resolver link, observed 2026-08-06T18:39:29.925434Z

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source=pdf_text observed=2026-08-06T18:39:29.925434Z digest=sha256:32c41871f25f58edf9667677d6676faf6d6551bd5b22de5159285f21360133b8

Observation 78cdc685-08e7-4f49-a465-f0cf0d440e35 · outbound

This paper cites See4d: Pose-free 4d generation via auto-regressive video inpainting.arXiv preprint arXiv:2510.26796, 2025.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models See4d: Pose-free 4d generation via auto-regressive video inpainting.arXiv preprint arXiv:2510.26796, 2025

Reference 54

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:30.003579Z digest=sha256:fa113a8fcd7c3dee16a008938d4d65e955d336ff0eb38df695cea052442166c8

Observation bbef90e0-4b4d-4de1-b902-fc6c16a76d2e · outbound

This paper cites You see it, you got it: Learning 3d creation on pose-free videos at scale.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models You see it, you got it: Learning 3d creation on pose-free videos at scale

Reference 55

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no resolver link, observed 2026-08-06T18:39:30.094528Z

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source=pdf_text observed=2026-08-06T18:39:30.094528Z digest=sha256:117c63a3de539ce343ff415800bc4e896d3bbfa268676fdd5aa0156820a3b920

Observation 8c614ffc-41a7-401a-8fa4-e5a0cf4c670b · outbound

This paper cites ROSE: Remove Objects with Side Effects in Videos.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models ROSE: Remove Objects with Side Effects in Videos

Reference 56

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no resolver link, observed 2026-08-06T18:39:30.164403Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T18:39:30.164403Z digest=sha256:67ef6a0ed8e9b58c4bed230d77dcef7ba414f7929a242e3fe6165134086083e7

Observation 5615a911-6bbd-495b-8cb6-1355093eec02 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Nerf: Representing scenes as neural radiance fields for view synthesis

Reference 57

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no resolver link, observed 2026-08-06T18:39:30.234553Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T18:39:30.234553Z digest=sha256:ad803309cdaccece4b87881bd17e72e8a15cba0cd68aec690f61795895cf7a0a

Observation 607840ad-6bc8-4ecb-9ed2-15cbba771280 · outbound

This paper cites Multidiff: Consistent novel view synthesis from a single image.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Multidiff: Consistent novel view synthesis from a single image

Reference 58

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source=pdf_text observed=2026-08-06T18:39:30.311305Z digest=sha256:2b7cb62804ef687d90ee6101f904a14c17f08658bd899e3956f228254206723a

Observation 38a5225e-3015-436a-a1df-0f87dd53f666 · outbound

This paper cites Instant neural graphics primitives with a multiresolution hash encoding.ACM Transactions on Graphics (ToG), 41(4):1–15, 2022.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Instant neural graphics primitives with a multiresolution hash encoding.ACM Transactions on Graphics (ToG), 41(4):1–15, 2022

Reference 59

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source=pdf_text observed=2026-08-06T18:39:30.355482Z digest=sha256:6960b2a5eefefa781a96d69846b4f652340058cce560839eae69ef65c5821ad2

Observation 42a0f179-6c15-4652-8d0a-7daaf41cea4a · outbound

This paper cites OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation

Reference 60

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source=pdf_text observed=2026-08-06T18:39:30.410302Z digest=sha256:5d4fbdea2e0fad5652063e5bb72e1967b87b8ccb82f40255d32d16b7a7286b3b

Observation e14ab24b-6e45-41ba-9598-040a6e20fe55 · outbound

This paper cites Carvekit: Image background remove tool.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Carvekit: Image background remove tool

Reference 61

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raw_fallback, observed 2026-08-06T18:39:40.207550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:30.480062Z digest=sha256:66a47b837914a75493ee5a50b716e78e9fda9d2e6de08bfc9ab8e68eaf0efcc3

Observation ea532d81-ceda-409d-a327-0015772a5721 · outbound

This paper cites Bridging implicit and explicit geometric transformation for single-image view synthesis.IEEE TPAMI, 2024.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Bridging implicit and explicit geometric transformation for single-image view synthesis.IEEE TPAMI, 2024

Reference 62

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raw_fallback, observed 2026-08-06T18:39:40.062476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:30.562642Z digest=sha256:d7cb98dfe9bdd354186525d969b4142945af997806a997e204e8be291e7a36ca

Observation 7e7457d6-64d8-4bb6-a1db-f4fad87223ad · outbound

This paper cites Barron, Sofien Bouaziz, Dan B Goldman, Steven M.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Barron, Sofien Bouaziz, Dan B Goldman, Steven M

Reference 63

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raw_fallback, observed 2026-08-06T18:39:39.911562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:30.640281Z digest=sha256:551e092414b20d2a2c46c4d1e83fe92014281140617ab63452c25d0fac1685f1

Observation 8442c808-db44-4d7e-b770-dd0fec475cb8 · outbound

This paper cites Scalable diffusion models with transformers.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Scalable diffusion models with transformers

Reference 64

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T18:39:30.721102Z digest=sha256:d9fb3ce6fe2f6f727af0c54b930cf8c2ad041d793a6f70d3ae281fbcb72368ec

Observation feb2ec6d-3315-4216-a0ea-def88a583fb0 · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models D-nerf: Neural radiance fields for dynamic scenes

Reference 65

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verified fuzzy
raw_fallback, observed 2026-08-06T18:39:39.781278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:30.785657Z digest=sha256:c70306e365de723e389e9ba7fab979a49b58eef6a08f49122831ba6973792d31

Observation c4f282a9-0b37-4334-91c8-b31142020280 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models SAM 2: Segment Anything in Images and Videos

Reference 66

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no resolver link, observed 2026-08-06T18:39:30.868075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:30.868075Z digest=sha256:84a011a0704c940eac57988eb980d9e25be4d4fda0481125127cdea1e9efe9d6

Observation bbeac3e7-74c6-4c29-a40a-ddf5e8c531c9 · outbound

This paper cites Common objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Common objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction

Reference 67

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verified fuzzy
raw_fallback, observed 2026-08-06T18:39:39.648751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:30.950795Z digest=sha256:eb920936516706447dcc9c3eb07dd65586fcb58aae6909af1d0daba83a5254b3

Observation 4a35d1f9-6542-4280-a6c0-8bfcbb170e11 · outbound

This paper cites Gen3c: 3d-informed world-consistent video generation with precise camera control.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Gen3c: 3d-informed world-consistent video generation with precise camera control

Reference 68

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verified fuzzy
raw_fallback, observed 2026-08-06T18:39:39.511183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:31.048960Z digest=sha256:b9afd746f0a4d6ca6637b494e34eec3edd076a1f06be8c974b8cf9739a6fffc3

Observation 42486f41-3f6a-4b39-ae85-6015230db3ce · outbound

This paper cites Pixelsynth: Generating a 3d-consistent experience from a single image.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Pixelsynth: Generating a 3d-consistent experience from a single image

Reference 69

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verified fuzzy
raw_fallback, observed 2026-08-06T18:39:39.371500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:31.164464Z digest=sha256:8d02ca0d79ca352d2dfb14889966ce0af1f1b7b99132b4344644519326299574

Observation ca39ca71-b0f8-44cb-926b-73c4aac9dace · outbound

This paper cites Geometry-free view synthesis: Transformers and no 3d priors.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Geometry-free view synthesis: Transformers and no 3d priors

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:39:39.251737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:31.271266Z digest=sha256:2f808df8e6b2d39b5d96e191681f4be35a163f4be8534f41a85caabda0762b01

Observation ac180335-7e63-4534-ba1c-b1edb707dbe2 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models High-resolution image synthesis with latent diffusion models

Reference 71

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no resolver link, observed 2026-08-06T18:39:31.396493Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T18:39:31.396493Z digest=sha256:b8950600fbf024edcaf24d7e548ce04b961d639389bbf73417a12e0679f14850

Observation 94518c4c-15d8-40fa-b881-88ea086f478c · outbound

This paper cites ZeroNVS: Zero-shot 360-degree view synthesis from a single real image.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models ZeroNVS: Zero-shot 360-degree view synthesis from a single real image

Reference 72

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verified fuzzy
raw_fallback, observed 2026-08-06T18:39:39.148856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:31.444560Z digest=sha256:3a943adc09cd17bd62dbe9293c13b02e31e58b2adf3e99ed6023da8cae051ead

Observation 2433159d-a042-4701-8bae-10f9be7b9c14 · outbound

This paper cites Assembly101: A large-scale multi-view video dataset for understanding procedural activities.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Assembly101: A large-scale multi-view video dataset for understanding procedural activities

Reference 73

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verified fuzzy
raw_fallback, observed 2026-08-06T18:39:39.020544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:31.511295Z digest=sha256:b8928c27fc09d8e7b122933f62f9979563ff64b1ee4121d93117dc93d58bf57d

Observation 9cb29a50-6b55-4c01-a23b-8676093c2838 · outbound

This paper cites RealmDreamer: Text-Driven 3D Scene Generation with Inpainting and Depth Diffusion.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models RealmDreamer: Text-Driven 3D Scene Generation with Inpainting and Depth Diffusion

Reference 74

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no resolver link, observed 2026-08-06T18:39:31.563419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:31.563419Z digest=sha256:cef01833caad5d99566de357709d0ad6a1bc7595db779f9554c1949502651a9e

Observation 8f6d3d5f-2128-4f2a-8477-5e23fe345789 · outbound

This paper cites Denoising diffusion implicit models.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Denoising diffusion implicit models

Reference 75

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no resolver link, observed 2026-08-06T18:39:31.646693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:31.646693Z digest=sha256:2ec61277526828d5ea7dfd1aa63cf6039e46b90c1f5211a8082cbc0f167d7042

Observation 20382936-777c-4be5-8b5f-b43c0f843c52 · outbound

This paper cites Nerfplayer: A streamable dynamic scene representation with decomposed neural radiance fields.IEEE TVCG, 2023.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Nerfplayer: A streamable dynamic scene representation with decomposed neural radiance fields.IEEE TVCG, 2023

Reference 76

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verified fuzzy
raw_fallback, observed 2026-08-06T18:39:38.877071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:31.711019Z digest=sha256:fccac001d2ee5ca1c0882bf90e854b1f523f4c3a5647521ec24774ce1f482cbb

Observation 0a13f126-ef5b-4111-910d-fa6ef9ae3870 · outbound

This paper cites Dynamic gaussian marbles for novel view synthesis of casual monocular videos.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Dynamic gaussian marbles for novel view synthesis of casual monocular videos

Reference 77

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verified fuzzy
raw_fallback, observed 2026-08-06T18:39:38.725859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:31.793781Z digest=sha256:f2d983ec3e2ac92608eee8aa4105996b419273fb279e046605cbf9c91317152c

Observation 6da1b104-eadc-4a4e-b66f-74ad57cc3554 · outbound

This paper cites DimensionX: Create Any 3D and 4D Scenes from a Single Image with Controllable Video Diffusion.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models DimensionX: Create Any 3D and 4D Scenes from a Single Image with Controllable Video Diffusion

Reference 78

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no resolver link, observed 2026-08-06T18:39:31.932292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:31.932292Z digest=sha256:679bdd973b7daa2fd442d435d50bd08c05a03bb7a1a00766fcbde0eeb2134030

Observation d4bf4861-3905-45e3-80fe-254b180a0a7f · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Non-rigid neural radiance fields: Reconstruction and novel view synthesis of a dynamic scene from monocular video

Reference 79

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verified fuzzy
raw_fallback, observed 2026-08-06T18:39:38.573027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:32.033471Z digest=sha256:e5c079a6b68c12132c98e464a120a1b102552624db7cd2b38ac43b87431383e2

Observation 9c78607c-fb80-4bde-a3a7-9b8502b783aa · outbound

This paper cites Megascenes: Scene-level view synthesis at scale.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Megascenes: Scene-level view synthesis at scale

Reference 80

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verified fuzzy
raw_fallback, observed 2026-08-06T18:39:38.444883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:32.143686Z digest=sha256:bbf11964a6417b8aa800f9f395b0f15f7afc55e981f178388b5f4b7f505b6ec3

Observation 878e1383-d026-4cfc-899b-e75395707de4 · outbound

This paper cites Generative camera dolly: Extreme monocular dynamic novel view synthesis.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Generative camera dolly: Extreme monocular dynamic novel view synthesis

Reference 81

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unresolved
no resolver link, observed 2026-08-06T18:39:32.254366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:32.254366Z digest=sha256:2dd5905b239b33128c4fd307c89d2663044d69a61fc6544eae30fb2c6b0e533c

Observation 310624c9-b6e8-45c4-b2b1-1c4bca5447c4 · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Ref-nerf: Structured view-dependent appearance for neural radiance fields

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:39:38.297448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:32.326764Z digest=sha256:f912fe1873b5f764acae9983afcd69def2dbf4c041fa6cf38bfdf290218712b8

Observation 25c811b3-865c-470a-929b-1b7a5e1b8344 · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Wan: Open and Advanced Large-Scale Video Generative Models

Reference 83

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unresolved
no resolver link, observed 2026-08-06T18:39:32.420823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:32.420823Z digest=sha256:a851238b9823d6c377cae3e61d7826c02afcd7c9016919a880c5c0ab3b67b6be

Observation 54a68a29-d1f5-4842-b201-de036712bbdf · outbound

This paper cites Vistadream: Sampling multiview consistent images for single-view scene reconstruction.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Vistadream: Sampling multiview consistent images for single-view scene reconstruction

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:39:38.160737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:32.518945Z digest=sha256:f1e31f426f81e64daab548d56bd8e19e3cb5de3cdc0baf88701ec15c3d6c77bf

Observation ec1af565-83d8-4062-bd30-3ca606e98cfc · outbound

This paper cites Videoscene: Distilling video diffusion model to generate 3d scenes in one step.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Videoscene: Distilling video diffusion model to generate 3d scenes in one step

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:39:38.016938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:32.620533Z digest=sha256:86ca77bfcc49c1080408053b3f26e294646c1120bb3dbbeaec6599d937468b26

Observation ed6e699c-8b3d-40dc-8273-e4cb7455d116 · outbound

This paper cites Vggt: Visual geometry grounded transformer.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Vggt: Visual geometry grounded transformer

Reference 86

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no resolver link, observed 2026-08-06T18:39:32.703246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:32.703246Z digest=sha256:374ee92d17d5ee01c2beead14315e9a302264f320d5160406bcc1c26256a1ec8

Observation 002ffc1e-7d16-4376-aba4-55eed83c317a · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Shape of motion: 4d reconstruction from a single video.arXiv preprint arXiv:2407.13764, 2024

Reference 87

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no resolver link, observed 2026-08-06T18:39:32.758157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:32.758157Z digest=sha256:5c567ce60c0f89300e126d7da89aa26e7c57d3673ac0263c39ddc379a2e7a4ae

Observation 2cfec30c-8885-4f1e-9795-80022a519882 · outbound

This paper cites Moge: Unlocking accurate monocular geometry estimation for open-domain images with optimal training supervision.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Moge: Unlocking accurate monocular geometry estimation for open-domain images with optimal training supervision

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:39:37.873305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:32.837122Z digest=sha256:50b3d929b696e5002188602b8b1d37c4f78eacdcb55485b692bc491322fef791

Observation 8fb4c8fc-23f7-4444-bd5c-0a6e6d8664a0 · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Dust3r: Geometric 3d vision made easy

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-06T18:39:32.893325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:32.893325Z digest=sha256:402fcbe12a88ba8a68ac80e268aa665045cac946c9c8ec6e4e2d0e44ec6a6e4e

Observation c59d133f-8754-4a71-ba87-ccecfaafd207 · outbound

This paper cites Motionctrl: A unified and flexible motion controller for video generation.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Motionctrl: A unified and flexible motion controller for video generation

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:39:37.752001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:32.953301Z digest=sha256:63fe7f54cf599b83f94a71a05dff96bdd9e54a4d95f6f74fc34149bec5713720

Observation 81eb40c6-fe82-4380-a418-25c825292155 · outbound

This paper cites Synsin: End-to-end view synthesis from a single image.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Synsin: End-to-end view synthesis from a single image

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:39:37.631562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:33.003635Z digest=sha256:032e3ac16d1006e4f9a8481855ce9ac63809a3d616ed1f2a1c3abcdbf67a9154

Observation 388544a4-58ca-4e63-920c-2740ca78c2c9 · outbound

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

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models 4d gaussian splatting for real-time dynamic scene rendering

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:39:37.518304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:33.050247Z digest=sha256:4bda13d15fdbe498233393953fb63d482e88ee960064407596fa039632a5e7bb

Observation 299962af-bbae-44b6-9d78-830c227f65fa · outbound

This paper cites CAT4D: Create Anything in 4D with Multi-View Video Diffusion Models.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models CAT4D: Create Anything in 4D with Multi-View Video Diffusion Models

Reference 93

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unresolved
no resolver link, observed 2026-08-06T18:39:33.106709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:33.106709Z digest=sha256:05a627d1e91920917f662ebece16f8734c8ed8272a12ef8d7883118b4421f0bf

Observation 4aed8aae-d666-438a-bad9-9a7d4618e0f3 · outbound

This paper cites Reconfusion: 3d reconstruction with diffusion priors.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Reconfusion: 3d reconstruction with diffusion priors

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:39:37.386498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:33.163955Z digest=sha256:f261fd55c126c65ba21f5e0efe31cc9afd1da066c4f5d8c8910606e179115076

Observation 712d0dc5-e496-44f1-8268-7226da6a36a3 · outbound

This paper cites Trajectory attention for fine-grained video motion control.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Trajectory attention for fine-grained video motion control

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:39:37.266916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:33.206882Z digest=sha256:85f3ef5aec62995de512b355ee451cc1e485ac3ee8e1c2b3f390b5d42c14d842

Observation ab944705-912c-41cb-a689-3907f113dd6c · outbound

This paper cites DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors

Reference 96

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unresolved
no resolver link, observed 2026-08-06T18:39:33.283876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:33.283876Z digest=sha256:e6c0f46cc5700405b82b8da23f4aa5cb3cdeea82f1bc5de3a65446e1df91504a

Observation 67b4f520-4868-4ab3-9192-88f64021211e · outbound

This paper cites CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generation.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generation

Reference 97

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unresolved
no resolver link, observed 2026-08-06T18:39:33.351341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:33.351341Z digest=sha256:c60b348d8f85d5c1703e3f381a523e69af232aea4b35da4f0e790ba6ec68ae8a

Observation e01e58e9-c511-467f-aeae-196e39679f86 · outbound

This paper cites 4dgt: Learning a 4d gaussian transformer using real-world monocular videos.arXiv preprint arXiv:2506.08015, 2025.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models 4dgt: Learning a 4d gaussian transformer using real-world monocular videos.arXiv preprint arXiv:2506.08015, 2025

Reference 98

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unresolved
no resolver link, observed 2026-08-06T18:39:33.405744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:33.405744Z digest=sha256:45e91065fa83e25b5037c62571010f1dbff583deb3348cf57bfeae056035216b

Observation 186a31ad-6fa6-41e0-ab33-aced6f7c7dbc · outbound

This paper cites Depth Anything V2.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Depth Anything V2

Reference 99

Resolution
unresolved
no resolver link, observed 2026-08-06T18:39:33.462649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:33.462649Z digest=sha256:9f2578d4b16c219fa22de41d448c91c1456a068aa630644c31b835cd28bd4586

Observation c90e8d97-0adc-4b54-8dd1-c1e308933ae4 · outbound

This paper cites Real-time photorealistic dynamic scene representation and rendering with 4d gaussian splatting.

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models Real-time photorealistic dynamic scene representation and rendering with 4d gaussian splatting

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:39:37.144279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:39:33.523972Z digest=sha256:2d30d9b2fdd81510dd8df343b8f137b6b0e4592ec428c46b6f4bf47578be7352

Pith citing papers

No inbound Pith citation observations are available.