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Paper Citation Record · LEDGER

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images

As of 15 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2412.03517.

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

pith.paper-citation-record.v1
2412.03517 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:22:03.942597Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:28:11.898552Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T13:28:16.336820Z

Reference resolution

47 of 47 outbound references displayed

  • verified exact0
  • verified fuzzy16
  • unresolved31
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 27e71c43-362d-4814-bd33-65e155686682 · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 1

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Observation f94105c3-1b8f-4900-8eb8-1a9228d34d6b · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Align your latents: High-resolution video synthesis with la- tent diffusion models

Reference 2

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Observation a25729f6-d3e1-4521-a66d-728ad0a41168 · outbound

This paper cites Generative novel view synthesis with 3d-aware diffusion models.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Generative novel view synthesis with 3d-aware diffusion models

Reference 3

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Observation 3cff81b3-0a11-49b7-a653-4dfd5261e82f · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Objaverse: A universe of annotated 3d objects

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 25b70fb5-541e-40b8-a45f-8adbe16c7c83 · outbound

This paper cites Image quality assessment: Unifying structure and texture similarity.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Image quality assessment: Unifying structure and texture similarity

Reference 5

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Observation cb6dcca1-dba5-4892-be15-59dc0284bc2e · outbound

This paper cites Structure and content-guided video synthesis with diffusion models.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Structure and content-guided video synthesis with diffusion models

Reference 6

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Observation 4c555108-1bdf-40ba-9d0c-394df0af1b92 · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images CAT3D: Create Anything in 3D with Multi-View Diffusion Models

Reference 7

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source=pdf_text observed=2026-08-11T22:22:03.760753Z digest=sha256:61ffa5e8b2750f39fead9987a845caed84c889be514dc408a58cf5e8b357078b

Observation 5dae9127-0e82-4b3c-982a-342f4cfacd1f · outbound

This paper cites AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

Reference 8

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Observation 7f74e477-4d8f-4a9c-9262-5dd7d46e9eb5 · outbound

This paper cites CameraCtrl: Enabling Camera Control for Text-to-Video Generation.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images CameraCtrl: Enabling Camera Control for Text-to-Video Generation

Reference 9

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source=pdf_text observed=2026-08-11T22:22:03.770390Z digest=sha256:dec6a6cdd53d5ea4b1ba59a999bc9945b495eb980df95604366c0c2892c6ac3c

Observation 1f917c63-63bd-43a5-ad3c-b5bb23be2940 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 10

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source=pdf_text observed=2026-08-11T22:22:03.775289Z digest=sha256:7b971da650fffc6aaa59b75c753f7323b8a53012ce05082abbaeb8914d133870

Observation 9ec1eb4e-8e75-40c3-8ddd-fd886037980d · outbound

This paper cites Denoising dif- fusion probabilistic models.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Denoising dif- fusion probabilistic models

Reference 11

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source=pdf_text observed=2026-08-11T22:22:03.780106Z digest=sha256:3f90a88408eefc0bdf2dfd09c7858b8b9126083275af70b99c0baefbc3a53100

Observation e9d72127-397b-45c4-a07f-e13fa924aa2d · outbound

This paper cites Video dif- fusion models.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Video dif- fusion models

Reference 12

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source=pdf_text observed=2026-08-11T22:22:03.784394Z digest=sha256:06b5cf6011c8967a22be80cc3c7e7ac03e97c395b555ffc05099e42be57c933c

Observation 9de9231c-ecb4-4cea-b7f3-f8b9a974811a · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images LoRA: Low-Rank Adaptation of Large Language Models

Reference 13

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source=pdf_text observed=2026-08-11T22:22:03.788763Z digest=sha256:b8334185c013beb72bdb0d2a728bb738e6cc3370dd16065ccafda2fbd5e3bd06

Observation f53093e4-6021-4003-9279-a5fb25bd0a82 · outbound

This paper cites Spad: Spatially aware multi-view diffusers.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Spad: Spatially aware multi-view diffusers

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.793185Z digest=sha256:f914a70dfb51a7f8f62d667cf374804eaf814cb1fe9376cc2e2bfca87c044cca

Observation 6e9b4655-1888-4ec9-b48d-ec53383bda0c · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images 3d gaussian splatting for real-time radiance field rendering

Reference 15

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source=pdf_text observed=2026-08-11T22:22:03.797593Z digest=sha256:1948452a670dc1f5c7d78977c3ca63fe171f1da0dda2853e20c75e9c0d11d177

Observation 97de97d6-108a-44c3-b89e-e71260e80de8 · outbound

This paper cites Grounding Image Matching in 3D with MASt3R.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Grounding Image Matching in 3D with MASt3R

Reference 16

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source=pdf_text observed=2026-08-11T22:22:03.802151Z digest=sha256:ff6525d9b5c181387f3a5a766e5e771afd4700e02fec4a1f9c6841c0ba51ccc1

Observation ce8592b2-cd58-4da3-b082-e255f60644b9 · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 17

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Observation fc099590-5406-4ccd-90c3-06b05d6bd77c · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Dl3dv-10k: A large-scale scene dataset for deep learning-based 3d vision

Reference 18

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 0019d001-57bc-421f-99be-e2da14051ffa · outbound

This paper cites ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model

Reference 19

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source=pdf_text observed=2026-08-11T22:22:03.815789Z digest=sha256:0a0440497ba466791d3c80783e8ca22dc2400c305e880e9cea51b444a727cb29

Observation 960a3ad1-8eaf-4490-bb32-ea4f2d576fb8 · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Zero-1-to- 3: Zero-shot one image to 3d object

Reference 20

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.820515Z digest=sha256:a94e7c59191dda036c0857f67ad9a4e27516cd04a268aff1b272beaebff3a48b

Observation 8cdff78c-4453-4049-be7d-749f8fa9f804 · outbound

This paper cites Wonder3d: Sin- gle image to 3d using cross-domain diffusion.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Wonder3d: Sin- gle image to 3d using cross-domain diffusion

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.824816Z digest=sha256:29a0a84a31efefaaa472cf0d8e3fe377b4fd481b1e9067b1e59be6d9472dbc51

Observation f4d5f141-6167-4bb2-8c2d-be88c85fdde8 · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Nerf: Representing scenes as neural radiance fields for view syn- thesis

Reference 22

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Observation 3ea686ce-09ba-4c55-8e33-599ba938c6e1 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Learning transferable visual models from natural language supervi- sion

Reference 23

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.833213Z digest=sha256:b6eda44ddf748ca89976d6557c7f8f2c5cc54b03a83b2c61679a44e1f86721a7

Observation ce34a411-2a3f-47d8-8250-d265a1111e03 · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Com- mon objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction

Reference 24

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.837759Z digest=sha256:4ea824cd87b0460adac61a536c128fd155a114d795ca5e505dbda6b25a2d5167

Observation ebf9f476-f159-46ed-8884-f5d763bbba36 · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Pixel- synth: Generating a 3d-consistent experience from a single image

Reference 25

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.842320Z digest=sha256:744d6148708ccb5c91b1b446219c7f8bfd6dffc09861b3f9ac355511bfb43526

Observation c2f80667-efe2-4438-83e9-36afb9a88f8a · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images High-resolution image synthesis with latent diffusion models

Reference 26

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source=pdf_text observed=2026-08-11T22:22:03.846704Z digest=sha256:7cad584d8ecb74b7bfa8e7c56f0996457a96302cfe074e76eab3fc053d75a1f0

Observation fbfdc388-b2b4-482b-9aa1-0bde7f4a40f8 · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model

Reference 27

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Observation ff62c0e0-80cd-4905-85d5-efb3f5e7f6a8 · outbound

This paper cites Light field networks: Neu- ral scene representations with single-evaluation rendering.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Light field networks: Neu- ral scene representations with single-evaluation rendering

Reference 28

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source=pdf_text observed=2026-08-11T22:22:03.855882Z digest=sha256:713e9ad4d456952d599075c13f17d6df40bddffbf23b6bdcc65f47c3e551fb1d

Observation f3170b0e-2f6e-4d69-886c-efc199066279 · outbound

This paper cites Denoising Diffusion Implicit Models.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Denoising Diffusion Implicit Models

Reference 29

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source=pdf_text observed=2026-08-11T22:22:03.860755Z digest=sha256:a0df5bf5553ef3aab465b5bfa0a8afc40b09af5f5b30a905c3f191c7586cfc8b

Observation 24adad0a-db5b-41c9-8e93-f950a27243a9 · outbound

This paper cites Single-view view synthe- sis with multiplane images.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Single-view view synthe- sis with multiplane images

Reference 30

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source=pdf_text observed=2026-08-11T22:22:03.865165Z digest=sha256:3df938ddad816c18f55e5c9ea1b02c31f72d0cd9b2eb7e7649a1aa5084724210

Observation 500541ea-aa06-4764-98e3-9028ea06cad3 · outbound

This paper cites Towards Accurate Generative Models of Video: A New Metric & Challenges.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 31

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Observation 186ec288-d23d-4dab-9471-e14e21824c5a · outbound

This paper cites Sv3d: Novel multi-view syn- thesis and 3d generation from a single image using latent video diffusion.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Sv3d: Novel multi-view syn- thesis and 3d generation from a single image using latent video diffusion

Reference 32

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raw_fallback, observed 2026-08-11T22:22:04.317310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation d61857cd-cf22-4bad-9580-3f4d4d13d87f · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Ibr- net: Learning multi-view image-based rendering

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.879000Z digest=sha256:15f5e883b8deb9aa8b8f307534784ca2a1f6ffc4fb6acfc94add20c59ab833d1

Observation ab273754-7416-4632-a551-c61b33b70f4d · outbound

This paper cites Dust3r: Geometric 3d vi- sion made easy.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Dust3r: Geometric 3d vi- sion made easy

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.883439Z digest=sha256:6b7957f2509ad942b1359d52885ddfca6a4f55f52075951c11cb003a52d99e6a

Observation 76f46eea-5dcb-45be-9d8c-1d02a8a0bbb6 · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Image quality assessment: from error visibility to structural similarity

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:22:03.888367Z digest=sha256:2d9aac2f20b2915547057842593f25080772f6b190c71d6b1c145ad4e59287db

Observation ca361dd2-8cff-41c0-9e12-220f5d023a0c · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Motionctrl: A unified and flexible motion controller for video generation

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:22:04.263660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.892920Z digest=sha256:c1a4beca8abf50c2726fe3f51f44b949e0023885e2a4541b7967d1bb9dce4ea4

Observation a14c86e2-5492-417a-b523-29ced914f0a5 · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Synsin: End-to-end view synthesis from a sin- gle image

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T22:22:03.897475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:22:03.897475Z digest=sha256:a21ba9f11e9ca49382dcd4d47c635eac981db7f699eedf984ed267323dffde1c

Observation 39d53e22-371b-45c6-8563-efa81cce81a9 · outbound

This paper cites iFusion: Inverting Diffusion for Pose-Free Reconstruction from Sparse Views.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images iFusion: Inverting Diffusion for Pose-Free Reconstruction from Sparse Views

Reference 38

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unresolved
no resolver link, observed 2026-08-11T22:22:03.901953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:22:03.901953Z digest=sha256:7871e184c91b4868c5c42fa08429c9733632685f5956ebce79be584515310d2f

Observation 83a200c8-3148-454f-8ddd-975280eb72c2 · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Reconfusion: 3d reconstruction with diffusion priors

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:22:04.240908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.906398Z digest=sha256:9462e101572c60ff820df451f2e22444ba24664f2f548cfae29d93ba76e98c68

Observation 784e562b-1dcc-4bbe-ac30-19e431a2d629 · outbound

This paper cites Dynamicrafter: Animating open-domain images with video diffusion priors.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Dynamicrafter: Animating open-domain images with video diffusion priors

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:22:04.226537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.910893Z digest=sha256:433372f46130a9a2430f12a58428cbdf23901ad477a33cba9cda5076a702d18e

Observation 2e315db8-ce16-45a6-b612-974feb2a0e9b · outbound

This paper cites Sparp: Fast 3d object reconstruction and pose estimation from sparse views.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Sparp: Fast 3d object reconstruction and pose estimation from sparse views

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:22:04.212301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.915266Z digest=sha256:00c96465af4cd5a75320dee8d2b917ce469c148638ee5261340281ea2f51219a

Observation 421fe8ef-4ed7-4c21-a314-5b7e14930b20 · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images pixelnerf: Neural radiance fields from one or few images

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-11T22:22:03.919414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:22:03.919414Z digest=sha256:647609011e5252a8e9ce8ad4a6bb78dd9a4baab5c9ee2e9e48caabd9b2bec7e5

Observation 8ade66cb-e5c5-40a7-880b-45dbfa155a6a · outbound

This paper cites ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-11T22:22:03.923958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:22:03.923958Z digest=sha256:e47805ee82744516b1121f1d3b1914a6ea4586c534d0e06c832f1b5725d0ee80

Observation fa391b69-40c2-4a6b-aeb1-778a8bb1cd11 · outbound

This paper cites ReCapture: Generative Video Camera Controls for User-Provided Videos using Masked Video Fine-Tuning.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images ReCapture: Generative Video Camera Controls for User-Provided Videos using Masked Video Fine-Tuning

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T22:22:03.928625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:22:03.928625Z digest=sha256:f001eb6b826b547d43d4b59c8a722b7ece722e36890d90111509a360e82ae2f2

Observation 88459cbb-f5e4-4f0e-8857-4053f6ca1f7b · outbound

This paper cites Cameras as Rays: Pose Estimation via Ray Diffusion.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Cameras as Rays: Pose Estimation via Ray Diffusion

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-11T22:22:03.933727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:22:03.933727Z digest=sha256:417a472e425810168ec368a85109da9c6f432cd00e5947abd3fe6b5858e8dbf6

Observation 8fc6da66-a652-4ed7-a1e9-c5be771441c0 · outbound

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

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images The unreasonable effectiveness of deep features as a perceptual metric

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T22:22:03.938151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:22:03.938151Z digest=sha256:ea4cec28204eb79baea2334f55061c701e8c2fc388a1bc66b36d029ad0431f09

Observation cf27923b-d460-4f75-a9b6-dbb5b05f87ef · outbound

This paper cites Stereo magnification: Learning view 10 synthesis using multiplane images.

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images Stereo magnification: Learning view 10 synthesis using multiplane images

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:22:04.178145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T22:22:03.942597Z digest=sha256:a16afa6bc917e2d1807711841365ad0f0445c050a24dbdd18d647d5fe6b02c9a

Pith citing papers

Observation a00e6002-1a75-4618-a282-b7e31e57db56 · inbound

EPiC: Efficient Video Camera Control Learning with Precise Anchor-Video Guidance cites this paper.

EPiC: Efficient Video Camera Control Learning with Precise Anchor-Video Guidance NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:28:16.416705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T13:28:11.898552Z digest=sha256:a213d2d711ac0f2b9378f686ede0a2b5b8f8de51d278e0edf44b5bf151a2ed44