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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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Reference resolution

100 of 123 outbound references displayed

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  • 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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source=pdf_text observed=2026-08-06T18:39:25.848067Z digest=sha256:63637265f678861dfc19aced19976ac589128afabc1f3437be26ffe009d78a13

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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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:d00350542c91b95750770e0a86203ae26a4bf640f5451238a777b8bdad001753

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:c87be408519ceaac968ca3dd73372eb68796dd63e7afe215585aa63cbae1dd9b

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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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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source=pdf_text observed=2026-08-06T18:39:27.938002Z digest=sha256:69bc90afdb44ec3bd869c0417ddd7351fccf568b100b3e6b5df769540aa7e6b4

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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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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source=pdf_text observed=2026-08-06T18:39:28.289068Z digest=sha256:6baa544a04bfb4a3bcfa1f356f1bf1fbb85c02afb2607015d155950427f46b35

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:d70aef28e86a0704630e5ed80fae199e413905d25749bb849e7d83fd76a8ccbb

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=sha256:0e1b99d2e9d22ba51889ac557284195ce0a7a009b31d157159e6fb73aad0bf1e

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=sha256:87f813f6e7176976e2af5fa63ddaf1cc9095808b7ca0bc989b0024c326099e7a

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=sha256:3edc62329d579339f7ff9f05b98ca7a44b1b9ba24a5c4bb80f9c99e7026b1b35

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=sha256:16c4d46130e96fe97cf5b62ba1db338a20e1876ddcd8ca00fa1744ed74b4c5f9

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=sha256:2573467f8edbf8a9793f5c5299b42d6a6eb31fe0e5fecf7476f37edd6d21f026

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=sha256:3e2207d3a3f1e500da6f54aeb62793112feb378fba688b54601d30d5d3679346

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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source=pdf_text observed=2026-08-06T18:39:29.174331Z digest=sha256:4306de7288ebff2275db865a6602e9cf4929ddaa3f723700721857f2e4ad20cc

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=sha256:96f38f42273a18527811d8aea20a067e7fa8af3ec7d0ae769ce0fbe0ec9d8f41

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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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T18:39:29.317516Z digest=sha256:ce00a32da1df52289eed0efc29db638771e2bfba667bd1a1e659bb6f83982964

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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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T18:39:29.378999Z digest=sha256:02aa43663c3b2e1e3a299616a062798c1457b5e27e7c6f04602d6850cbc83aff

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:29.458323Z digest=sha256:2898a820d66fa1771f4a99ca48e993e73e67f5ef63ff13607677ae660476dcc6

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:ddc104f76ed92b30a1537259677ddec6750fd0cd764881ba627bdf8381076d88

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:29.636927Z digest=sha256:6586212456ffa00c2f77af1207ef3f4cff154ae08a5baa2aa46b9469bb5a4bdb

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:29.722061Z digest=sha256:81fc8f341a3c73df1f1c12865521e59fe835aaa17497e46d1734a71d2bb9bbb8

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=sha256:78099e2a08a483617252998ce07a997f3c342d72c53a9fd6760c8971b0ae5be2

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:29.925434Z digest=sha256:91333d53ca9242a39d0d2b8acc8ce537aba91bb57b2447eac83557f5e51b9d1e

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:30.003579Z digest=sha256:61df85790eba48cfeb339651933f6f304d02199dd66294c6d2426fc17a1f7237

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:c3510794208e783be56eb73bc502c67e8919907a494afb6cb1913c297fc00bb4

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:30.164403Z digest=sha256:d6c1dbc701299b933a57ed2fda13a367c7c2fe215095698594a5737779618d95

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:30.234553Z digest=sha256:989813b77f049d081da8d9464b30b1abf075036959e3f93548e4e0c3156eb067

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:a38dcdc8090da81319676b60a19c9b472ba65d69b6e75abb71c69dbca80ef6ff

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=sha256:7265bd36838fea26c32b7bede78bad30e3a005120382080da7b820217f42eaf9

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:d0c4ccb02fb9981f989d4318866cf6fdba1794d89b1468c809960a1beda71e20

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:c6b0924a604256822682b47e5f2746e2ca39e97919386e85f8d58ff3a7a4077f

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=sha256:973b78eda24f2f7de09feeec10057b5b38c3c33232f455f1d4d56a6f7ba6b10a

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=sha256:4fbcd30c476091ad9bdd6c2e5a2fc8f9fe98dc1e57c49a034280033295c7a05b

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:faa58a96f95ad775a2c89d283792dc734533df18b88137d1aadcd6b7900f5f59

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:d0e4d88ad01b689097c36860246cfc0fcded30f9e134ffd5df12c098da655eca

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

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source=pdf_text observed=2026-08-06T18:39:30.868075Z digest=sha256:06648c20c46afd35559be667c09ad377f0b880ec7e363eee7bf0ee47bad1a6d1

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=sha256:93f346b7e599f4b6ab4e9e3a624796cc063dc0e4387972f781b19ae0122e5720

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=sha256:83b70fcaa38b17be6fd49f5f605020e543a7dc18c90d13be080bb0274dfeb668

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:a8b4eb07c6fb4d4faa0be899092dc8151f769e52ce107e934bf42ac35392006e

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:d283e0dc964035dd15189c3058eedefc6ef6b5f37f26aaad16d09710c2db86e9

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=sha256:0b77f54a0ae1b4521343e22dbc28561356beaabfc437fdf8f91989a66a6496aa

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

Resolution
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=sha256:8b8bc1c4ce1144a0e52a3642803dc332643b68fa6a63571e29323240db843501

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=sha256:4ee1dc9ebd411d95944e6cf1b1a36ef75ee8398c7ae122182ebfb5ff40c3cb1a

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:31.563419Z digest=sha256:f0421b36c68ba1f448a664477e6eca0968211a4478313444854fe059366c5965

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=sha256:2a78e3c175bdff702ae75e621e2a61d8458defb98aab74d8b8b5f54ba8933e1f

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:dd76f350fc2397006993bdce52eab2e7e2d0daf48a79cc8536042d89b28e5897

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=sha256:0d166e50f5f7be515435a6b73a4192e091a8cadd1ee5ab5cc03618cbef25d94b

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=sha256:2cff55da3ff3bed671e0153d4391acc716641a443bfc5afd0961fa19e7267977

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=sha256:485870b2844d8b06b07a93c040fee6a1877e8a252435e27ed57d8a5b61d0102b

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=sha256:79cc249b1528ce01abf77268159a1b8beec49fa0b8d236d2797fa714bc0fb13f

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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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=sha256:01e28e613501e6c6af9e24dedd73dfc707513926e7e0c54ee3aefe39cfd29f32

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=sha256:0eb05a76f132107422d79cd913b558e6b42706cf4eab15e05f48f272a8cd1c68

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=sha256:2f6831a660c029dbbc30d58150ee7199b14051234079de631cdab593c25fea56

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=sha256:9fe5d27b2bee5b70e1052d3272c159888c6d6408fed09895a91003f46a1ea838

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=sha256:17e32f2ab854da78a02cb7f643365725a9750bbb77be9eae004b2858edd37dae

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:c07b91171d5e9a79a5b71d6a45d6549f80e6af5c11da2dbcee67d8570cbaa0ef

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=sha256:3b08432c0a7a511469ce82f105fe4df3d9c5da509ee4f2af4e59ce7542497905

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=sha256:79f369af10ac02217d8a849a3ca00b2ff178071163ecaaa24ea3a83429a09519

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

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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=sha256:3466ea765d6b3345208599829c0b1faff97152f84064f8899010db4bab3fddd3

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=sha256:96739338f7a6a9c4a267ccbf84541bfad85add39eb063ebba89fb75539c6e73f

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=sha256:7fc30b6c77752266fd5de84a5d978d61a761d7394d795b730f5a8a27b4647c08

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:a82e66e856290e29ae4f19e127504538f535d34da6652899d002626d3db3a663

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=sha256:25cf09cca4da459b8f92c30e2cd317bdfcc2f2149720c0941f4bf34aaf1048d6

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=sha256:352a0c3d8de43eaea357eb0aac80bff275993754c97805f51071bbef09a019d3

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:ef8d209b70f137a4be54ba67da448b860aae28784bdfa588b80b4380241b6f0e

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:f675c0712304ee12d3ef5c7e6966cfe299772ce3da041024dbaa3f11e26d4e91

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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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=sha256:91fb8ea65451730a2a887a5b627d84543b816e9a5c82d618cd036a0896f43a58

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=sha256:95d7358e3fccd760ac7db3477327e5890a5f9e8b27198bf127c6f3ab76a2e821

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=sha256:5a783a67580f579171291a470a8bae5178bc12bbb5cd343fae527f77b901b6eb

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=sha256:011e3328ea7f5396da71d4ab13981b5d0392349dd4acbb907b9b0a0f71a23a64

Pith citing papers

No inbound Pith citation observations are available.