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Paper Citation Record · LEDGER

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models

As of 14 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2501.12267.

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

pith.paper-citation-record.v1
2501.12267 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:23:48.613566Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b1c10aad-6afe-468c-aa38-2d1e06f4eebf · outbound

This paper cites Patchmatch: A randomized correspon- dence algorithm for structural image editing.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Patchmatch: A randomized correspon- dence algorithm for structural image editing

Reference 1

Resolution
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Observation 9aa05ff5-8e35-483d-b8e9-602e739f0696 · outbound

This paper cites Navier-stokes, fluid dynamics, and image and video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Navier-stokes, fluid dynamics, and image and video inpainting

Reference 2

Resolution
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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation b7ccbfd5-c7c2-440a-aeb7-5718fbdd9177 · outbound

This paper cites Free-form video inpainting with 3d gated convolution and temporal patchgan.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Free-form video inpainting with 3d gated convolution and temporal patchgan

Reference 3

Resolution
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Observation 60300801-bc4d-43e8-8cc0-d28fe29db9d2 · outbound

This paper cites Learnable gated temporal shift module for deep video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Learnable gated temporal shift module for deep video inpainting

Reference 4

Resolution
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Observation 3aab9678-fc02-4b95-aa10-8d8afa80fb60 · outbound

This paper cites Diffusion pos- terior sampling for general noisy inverse problems.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Diffusion pos- terior sampling for general noisy inverse problems

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation e0d158cd-d973-4d3d-8e6f-0dae8b3575e5 · outbound

This paper cites Diffusion models beat gans on image synthesis.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Diffusion models beat gans on image synthesis

Reference 6

Resolution
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Observation 063b4969-ebac-4c3b-b074-f70058f11ea8 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models An image is worth 16x16 words: Transformers for image recognition at scale

Reference 7

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Source-reported events for the cited work

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Observation e4d22312-37a3-46d5-a273-3723e73b84c7 · outbound

This paper cites Flow-edge guided video completion.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Flow-edge guided video completion

Reference 8

Resolution
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Source-reported events for the cited work

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Observation 5dea3623-f156-4e42-a310-25560876584d · outbound

This paper cites How not to be seen—object removal from videos of crowded scenes.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models How not to be seen—object removal from videos of crowded scenes

Reference 9

Resolution
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Source-reported events for the cited work

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Observation 02f5bcb7-37e1-4c80-b9f6-879ea23bcd0b · outbound

This paper cites Flow-Guided Diffusion for Video Inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Flow-Guided Diffusion for Video Inpainting

Reference 10

Resolution
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Source-reported events for the cited work

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Observation 4864b716-cce3-40ed-a2a2-59e259803aba · outbound

This paper cites Denoising dif- fusion probabilistic models.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Denoising dif- fusion probabilistic models

Reference 11

Resolution
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Source-reported events for the cited work

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Observation fc359b01-5bba-4665-b5de-6971b51d7749 · outbound

This paper cites Proposal-based video com- pletion.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Proposal-based video com- pletion

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 45f02705-dae0-4d7f-ad59-f0d7f0751255 · outbound

This paper cites Temporally coherent completion of dynamic video.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Temporally coherent completion of dynamic video

Reference 13

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation e076da8f-acec-4fb6-8234-e4c63b95458f · outbound

This paper cites Error compensation framework for flow-guided video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Error compensation framework for flow-guided video inpainting

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation b9fcf480-13ca-4bea-8a6e-4b3909f276be · outbound

This paper cites Deep video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Deep video inpainting

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 8fa073c3-92f9-4d14-a63e-480c6d4a1024 · outbound

This paper cites Learning blind video temporal consistency.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Learning blind video temporal consistency

Reference 16

Resolution
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Source-reported events for the cited work

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Observation f5d3dced-b357-4a44-9c9f-9e5ad5dbd91d · outbound

This paper cites Copy-and-paste networks for deep video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Copy-and-paste networks for deep video inpainting

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 96b106a0-3e25-4b7c-8fee-7daae53e7c7b · outbound

This paper cites Short-term and long-term context aggrega- tion network for video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Short-term and long-term context aggrega- tion network for video inpainting

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation a918c130-e58a-47df-96d0-54b3661d835c · outbound

This paper cites Towards an end-to-end framework for flow-guided video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Towards an end-to-end framework for flow-guided video inpainting

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 13f93ca0-b5c0-4f9f-9ea1-3ab746e0c3bb · outbound

This paper cites Fuseformer: Fusing fine-grained information in transformers for video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Fuseformer: Fusing fine-grained information in transformers for video inpainting

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation f945ce65-7eb7-42c0-b64b-61b4acd7ee7d · outbound

This paper cites Repaint: Inpainting using denoising diffusion probabilistic models.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Repaint: Inpainting using denoising diffusion probabilistic models

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 390c5054-0df9-446e-9ab8-abb73302e8a2 · outbound

This paper cites Full-frame video stabilization with motion inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Full-frame video stabilization with motion inpainting

Reference 22

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 937d43d6-e0ef-4542-90f6-60c0d0d12785 · outbound

This paper cites Video inpainting of complex scenes.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Video inpainting of complex scenes

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 546a5f1b-ada7-48c6-8b32-4ff085c4628f · outbound

This paper cites Video inpainting of occluding and occluded ob- jects.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Video inpainting of occluding and occluded ob- jects

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 2f922e7f-1167-46b2-b03b-c30fd1b0f49f · outbound

This paper cites Video inpainting under constrained camera mo- tion.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Video inpainting under constrained camera mo- tion

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation bf7738d2-ed50-4763-9866-8e272e3e87d2 · outbound

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

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models A benchmark dataset and evaluation methodology for video object segmentation

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation be1e5a97-12db-4b02-9ae8-a9a0c554f93c · outbound

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

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models High-resolution image syn- thesis with latent diffusion models

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation c231cb58-c4e1-4d98-85a3-8c86209d77a7 · outbound

This paper cites Deep unsupervised learning using 9 nonequilibrium thermodynamics.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Deep unsupervised learning using 9 nonequilibrium thermodynamics

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 1712329c-10dd-456c-9341-a380a20623aa · outbound

This paper cites Denois- ing diffusion implicit models.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Denois- ing diffusion implicit models

Reference 29

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:23:48.547227Z digest=sha256:99749e567d5ea2380903c4daaa532ac4ea1ad0d1553a949b988264beaafe72ab

Observation d87e30c7-564d-408e-a531-718d8a0283d4 · outbound

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

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Raft: Recurrent all-pairs field transforms for optical flow

Reference 30

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T17:23:48.551329Z digest=sha256:cf1cd50a3332c5abb28f63edb9f127220f6f0bd9f6d9b8bc12ad6848d33af064

Observation 92c42936-ba5e-415e-b09f-635fe87e29e0 · outbound

This paper cites Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, and Tommi S.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, and Tommi S

Reference 31

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation d988f2ca-e9d8-45e1-a14a-b78540ee7799 · outbound

This paper cites Attention is all you need.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Attention is all you need

Reference 32

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation feec1479-66a2-441e-a825-118aeefd90b8 · outbound

This paper cites Video inpainting by jointly learning temporal structure and spatial details.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Video inpainting by jointly learning temporal structure and spatial details

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:23:48.828645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation ac797e2d-2c3b-43e4-857c-720c5db800d8 · outbound

This paper cites Video-to- video synthesis.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Video-to- video synthesis

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:23:48.816226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T17:23:48.566801Z digest=sha256:103b9156e01f5a0690db38b2f59719f3c024939ac507050bdd293a0aa0f2a903

Observation 724ebc6e-cd1a-47d3-9eb4-236967061e14 · outbound

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

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Image quality assessment: from error visibility to structural similarity

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-10T17:23:48.570665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:23:48.570665Z digest=sha256:3824b7f0e238953f0600ce6a605770576f83bfc013f4d2d4c92fb004bd7ccf36

Observation 4f9afa72-2edf-4c4c-b71e-5c1a830a58ad · outbound

This paper cites Space- time completion of video.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Space- time completion of video

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:23:48.797640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T17:23:48.573880Z digest=sha256:396b6847db533f2169b545fc60c1ce523529c46818ff6342571aba01e1077d0f

Observation 2ec35e16-2f5c-49ea-8ce9-846a1fe5b22d · outbound

This paper cites Towards language-driven video inpainting via multimodal large language models.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Towards language-driven video inpainting via multimodal large language models

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:23:48.785927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T17:23:48.577491Z digest=sha256:f8c8ed536819d9f19f6f9ae3cbb3481a88c4bfcba3bbbf0f5e22b7afe270d05f

Observation 047808d8-af22-4c13-808d-3b0445f826ca · outbound

This paper cites Youtube-vos: Sequence-to-sequence video object segmentation.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Youtube-vos: Sequence-to-sequence video object segmentation

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:23:48.775357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T17:23:48.580745Z digest=sha256:3261bccf65b45802e8cfff96688f6b2f9f454fd2cada15db2f36a45e189849ca

Observation 53585af8-4054-4852-af60-4d5eb0853d8b · outbound

This paper cites Deep flow-guided video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Deep flow-guided video inpainting

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:23:48.764179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T17:23:48.583837Z digest=sha256:5b9e3a114bbb1d4634192f0c19092b1c022dd2b7062cc69ae54dd4a180772c03

Observation 5f8ee403-ed27-4dba-b206-362ff3fafc0d · outbound

This paper cites Frequency-aware spatiotemporal transformers for video in- painting detection.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Frequency-aware spatiotemporal transformers for video in- painting detection

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:23:48.752519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T17:23:48.587086Z digest=sha256:a612dcb5d733be2d23605534ddbf224029b9ced0a99d06a28d34ffc9ebf1c25f

Observation b1986eeb-0733-4281-bd9b-8ca67ec5560e · outbound

This paper cites Learning joint spatial-temporal transformations for video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Learning joint spatial-temporal transformations for video inpainting

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:23:48.738676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T17:23:48.590298Z digest=sha256:7fa253184069331123747687b282ec66f5ac959e2fdf76d32678fdec1a986689

Observation 3fa1365d-add7-4ee7-9d11-4a8fd5781dca · outbound

This paper cites Towards coherent image in- painting using denoising diffusion implicit models, 2023.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Towards coherent image in- painting using denoising diffusion implicit models, 2023

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:23:48.725427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T17:23:48.593608Z digest=sha256:2280d960b1496f39d87a3324e54185174fc36d1915953a7b371e61a4614d276e

Observation 05289cdf-ea0c-4b08-802f-7173712687e4 · outbound

This paper cites An internal learning approach to video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models An internal learning approach to video inpainting

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:23:48.712695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T17:23:48.597085Z digest=sha256:b9d92864ec12f5873c859aaf57e785b9b9c7ac73c68ffcb8a16a8772ae753395

Observation e7479aad-9734-446e-bdf4-442beb477ee8 · outbound

This paper cites Flow-guided transformer for video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Flow-guided transformer for video inpainting

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:23:48.699193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T17:23:48.600922Z digest=sha256:ef4a843b5cfd4b3249b5d1d824dae05021153466868b91692bcc801f789fe989

Observation 37663b00-21c8-4bb9-a3d2-407fb9277635 · outbound

This paper cites Exploiting Optical Flow Guidance for Transformer-Based Video Inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models Exploiting Optical Flow Guidance for Transformer-Based Video Inpainting

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T17:23:48.604906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:23:48.604906Z digest=sha256:2dff1975c58e04c9672edab4379da9192d2cd201b1bb90e7faf90924e22127df

Observation ba85eab6-c9f1-4404-a94a-36822eb6baff · outbound

This paper cites AVID: Any-Length Video Inpainting with Diffusion Model.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models AVID: Any-Length Video Inpainting with Diffusion Model

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T17:23:48.609112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:23:48.609112Z digest=sha256:b9280439f28603574601abf3a0936b5adb6b5ef37bff220a317bbe996f72e281

Observation ce78833b-3b95-4d9d-8e85-28417d64dd13 · outbound

This paper cites ProPainter: Improving propagation and transformer for video inpainting.

VipDiff: Towards Coherent and Diverse Video Inpainting via Training-free Denoising Diffusion Models ProPainter: Improving propagation and transformer for video inpainting

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:23:48.685705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T17:23:48.613566Z digest=sha256:570365c31d989b0d26d678c12d6c7e4cca8e9fde62ec20d1cdd16bbbbaf3526e

Pith citing papers

No inbound Pith citation observations are available.