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Paper Citation Record · LEDGER

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s

As of 9 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 2 inbound Pith citation observations for arXiv:2506.08529.

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

pith.paper-citation-record.v1
2506.08529 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:14:34.525958Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T15:59:34.754260Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T09:31:03.169272Z

Reference resolution

68 of 68 outbound references displayed

  • verified exact0
  • verified fuzzy26
  • unresolved42
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c76ed59d-4ca7-4c08-94e4-21e50292ba13 · outbound

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

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.244361Z digest=sha256:c1f29d2bc108fecd56fd69ee0ec1cc76050a515dca72ad51ae0052c6cc746073

Observation 4b789f84-6495-496a-ba69-ea7a934f7bd0 · outbound

This paper cites Video Super-Resolution Transformer.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Video Super-Resolution Transformer

Reference 2

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no resolver link, observed 2026-08-07T05:14:34.249123Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:14:34.249123Z digest=sha256:4a59c5061753c3e14d2df4f0f51af4e1d6dc276217d0ea48fdaf0baa1d937376

Observation 8c95482c-fc2f-48ef-be1f-61c02689399b · outbound

This paper cites Basicvsr: The search for essential components in video super-resolution and beyond.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Basicvsr: The search for essential components in video super-resolution and beyond

Reference 3

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raw_fallback, observed 2026-08-07T05:14:35.344606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.254370Z digest=sha256:24de406a506557cc8a4c5dbc40b38e2d7dc7eab6afda113d85ce3094525835f2

Observation 804337dc-0e2c-4147-8d75-9cd22c0b28f5 · outbound

This paper cites Basicvsr++: Improv- ing video super-resolution with enhanced propagation and alignment.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Basicvsr++: Improv- ing video super-resolution with enhanced propagation and alignment

Reference 4

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raw_fallback, observed 2026-08-07T05:14:35.332558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.258261Z digest=sha256:86850eb8c53ff07f5a6793b0253a6a6ae81f8cdc9d3bd23f8237f0757ec95085

Observation 799dfc8e-41ba-4b79-8614-fbf183f98de0 · outbound

This paper cites Investigating tradeoffs in real-world video super-resolution.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Investigating tradeoffs in real-world video super-resolution

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.262754Z digest=sha256:acc904888de40a18832aa89ed3383f617b77cc74578c52b2b1d0416cc57a54c5

Observation 9e4a3ce7-5754-41c4-82a7-c6d273d83471 · outbound

This paper cites Diffusion forcing: Next-token prediction meets full-sequence diffusion.Advances in Neural Information Processing Systems, 37:24081–24125, 2024.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Diffusion forcing: Next-token prediction meets full-sequence diffusion.Advances in Neural Information Processing Systems, 37:24081–24125, 2024

Reference 6

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:14:34.266889Z digest=sha256:32a34eebf364e09e1e99e29e19931e0a186690d03e53c461f1694f125f6fc572

Observation 5b5d6997-33e8-4582-9c22-d54a6034dc19 · outbound

This paper cites PIXART-{\delta}: Fast and Controllable Image Generation with Latent Consistency Models.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s PIXART-{\delta}: Fast and Controllable Image Generation with Latent Consistency Models

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.271509Z digest=sha256:ef7a38769fef8ed262b8b47d0c4e263f28063a25d8a6843ae7158ee997a1df05

Observation 9868468e-6fe0-42f7-9126-e1e766ca8e77 · outbound

This paper cites PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.275537Z digest=sha256:5d947cf82aa428b2ed0ebdb9f2b4ddceac6b3dabcf57c30cc0fe8c780b878531

Observation a5a06b3d-4e3a-4fd6-ae6d-5f3294dad8c4 · outbound

This paper cites FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing

Reference 9

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source=pdf_text observed=2026-08-07T05:14:34.279736Z digest=sha256:332c2ed77f35c44f821b1f133ccace6920caaa211c004d3ec5497006d9488101

Observation 6ded8fce-5149-4939-815e-f27e5a586714 · outbound

This paper cites Deformable convolutional networks.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Deformable convolutional networks

Reference 10

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source=pdf_text observed=2026-08-07T05:14:34.283519Z digest=sha256:48f667166bb6518dc849401086cea2a46de229bd74f9cc52db5ce559e1389814

Observation 53c0e1c3-0820-4e92-b4a5-9139fe07311f · outbound

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

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.287017Z digest=sha256:4788aa6d1b5870cf6e66067750bd85a625a8279344e4375d8ddcbb169fb97596

Observation 382341be-928a-49ef-8c2e-c78819859806 · outbound

This paper cites VEnhancer: Generative Space-Time Enhancement for Video Generation.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s VEnhancer: Generative Space-Time Enhancement for Video Generation

Reference 12

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source=pdf_text observed=2026-08-07T05:14:34.291389Z digest=sha256:9608ae433b6fda3b926e52f9aadd622b58351e1984e5b5cac7bca3477820af37

Observation 10dfdbe4-914e-4e83-bdfa-66ee0c1d1ef9 · outbound

This paper cites Prompt-to-Prompt Image Editing with Cross Attention Control.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Prompt-to-Prompt Image Editing with Cross Attention Control

Reference 13

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:14:34.295772Z digest=sha256:d9eee2fd85f398bd1d7e19f06b3ccd5a6e9622a63ec498d57cf06792a9cecbb7

Observation 2eb57c28-37b9-423b-a8b8-98ac69f18f88 · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.300472Z digest=sha256:8159ce4fe22ef80a3a0daeef19c3078be5c9510ca42efb193fdb8c5c93c3a32f

Observation 5756e8d8-336b-4dd9-8513-23772704fd55 · outbound

This paper cites Video diffusion models.Advances in Neural Information Processing Systems, 35:8633–8646, 2022.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Video diffusion models.Advances in Neural Information Processing Systems, 35:8633–8646, 2022

Reference 15

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:14:34.304183Z digest=sha256:242bff963f2eb8e551e0b180a82a163de091b41eafdfb3d3d78e853da9fad579

Observation fae20e88-139c-4d5e-b6c6-cfec856fef5f · outbound

This paper cites Video super-resolution via bidirectional recurrent convolutional networks.IEEE transactions on pattern analysis and machine intelligence, 40(4):1015–1028, 2017.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Video super-resolution via bidirectional recurrent convolutional networks.IEEE transactions on pattern analysis and machine intelligence, 40(4):1015–1028, 2017

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.309012Z digest=sha256:72e26f1d173c5ba7fea504c33e38416fd3de95fc9869cc3df6b5675980a2126d

Observation 2093db6e-655d-4ebc-a7df-a4bb0e4deee7 · outbound

This paper cites Video super- resolution with recurrent structure-detail network.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Video super- resolution with recurrent structure-detail network

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.313488Z digest=sha256:8d38de6ae7f9b6bd1174041a95328f80b4dec18d232b0ab2e91c84540a28a9e2

Observation e78d8ce5-7349-4ee2-8ce2-37f332e66c19 · outbound

This paper cites Deep video super-resolution network using dynamic upsampling filters without explicit motion compensation.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Deep video super-resolution network using dynamic upsampling filters without explicit motion compensation

Reference 18

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raw_fallback, observed 2026-08-07T05:14:35.264523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.316868Z digest=sha256:812859d03c5de47ea14fb66289ca6ea26841d034ef4e2a2e97ca9ca35e79c641

Observation de0bf5f4-bc12-47f1-97e2-b6c809f586a7 · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s A style-based generator architecture for generative adversarial networks

Reference 19

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source=pdf_text observed=2026-08-07T05:14:34.320650Z digest=sha256:7a386f6474099c777b6e88d19913a4821084382b505851740d4986f56cb2307b

Observation 82e40795-7f73-4e93-9a02-dd8e95604632 · outbound

This paper cites Imagic: Text-based real image editing with diffusion models.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Imagic: Text-based real image editing with diffusion models

Reference 20

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source=pdf_text observed=2026-08-07T05:14:34.324620Z digest=sha256:980a2a13c81da27533f0d35a139989d6e6846c80a9c0b56dea0adce5561d28ea

Observation 91e51ae7-42a4-4d33-ab00-5b6a8f799de5 · outbound

This paper cites Musiq: Multi-scale image quality transformer.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Musiq: Multi-scale image quality transformer

Reference 21

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source=pdf_text observed=2026-08-07T05:14:34.328458Z digest=sha256:de196699e90ca0cfb552b876e8b3c92210a34d35a6d7b4757e9feaeb4870afd7

Observation 8dac9286-8ebd-45b3-92a4-10a51b942ccd · outbound

This paper cites Mucan: Multi-correspondence aggregation network for video super-resolution.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Mucan: Multi-correspondence aggregation network for video super-resolution

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.331830Z digest=sha256:f3a38d0035c29bacc4d345864dedecade42ba0a29eed2bd4faffed30d2e7dbca

Observation df1b1c42-9b8b-42c2-b6b6-04fc4fcd5c65 · outbound

This paper cites DiffVSR: Revealing an Effective Recipe for Taming Robust Video Super-Resolution Against Complex Degradations.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s DiffVSR: Revealing an Effective Recipe for Taming Robust Video Super-Resolution Against Complex Degradations

Reference 23

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source=pdf_text observed=2026-08-07T05:14:34.335250Z digest=sha256:a80c0a23fb89058386d695592c3243df2dce77dfce43f8cd72a0d9bb53d3de1e

Observation bc9caeaa-f1e0-4125-8d50-c5bcfd47b2a7 · outbound

This paper cites Lsdir: A large scale dataset for image restoration.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Lsdir: A large scale dataset for image restoration

Reference 24

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source=pdf_text observed=2026-08-07T05:14:34.339139Z digest=sha256:fbe91121786fd35494c5ce528b343e110f07481b0b3691a050dd4c3f8ac38960

Observation fb9724d2-1ac1-4eeb-8aab-9c74218e3147 · outbound

This paper cites Vrt: A video restoration transformer.IEEE Transactions on Image Processing, 2024.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Vrt: A video restoration transformer.IEEE Transactions on Image Processing, 2024

Reference 25

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raw_fallback, observed 2026-08-07T05:14:35.217089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.343476Z digest=sha256:3c77adc23b441b23071b9e208be1fe2cfa80c5f72045bee6c5a9f360b8ec3f80

Observation da59c639-71d2-421a-b2e7-cd1b37b03231 · outbound

This paper cites Recurrent video restoration transformer with guided deformable attention.Advances in Neural Information Processing Systems, 35:378–393, 2022.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Recurrent video restoration transformer with guided deformable attention.Advances in Neural Information Processing Systems, 35:378–393, 2022

Reference 26

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raw_fallback, observed 2026-08-07T05:14:35.205218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.346812Z digest=sha256:2a9eb5e740887b916d8a1b633e70bc9a90a9ecee95ef18d33879d3de3014b0e9

Observation 565ee97e-c92a-401f-b3d1-48d9bb6094ec · outbound

This paper cites Enhanced deep residual networks for single image super-resolution.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Enhanced deep residual networks for single image super-resolution

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.351185Z digest=sha256:3be29e9c2e6bf8b8e376db94fae699510326bc87641e7f8548fa98a6981c382d

Observation 4a664250-3e2e-47de-9f2b-0715b7d23974 · outbound

This paper cites Diffbir: Toward blind image restoration with generative diffusion prior.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Diffbir: Toward blind image restoration with generative diffusion prior

Reference 28

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source=pdf_text observed=2026-08-07T05:14:34.354493Z digest=sha256:3da7ffe87ba06d5bf526cb5d53b3b0e4d00add25ad49c0b832bcf629c34e7875

Observation 3e8af4c4-b5de-45b2-acfc-b125f3857a79 · outbound

This paper cites Learning trajectory-aware trans- former for video super-resolution.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Learning trajectory-aware trans- former for video super-resolution

Reference 29

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raw_fallback, observed 2026-08-07T05:14:35.181706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.358493Z digest=sha256:4feff8e4ad9fe7d53d35ec86a9cb2defc52e4f140cfbf99a726a3841c912aeb6

Observation 914ca01e-15d3-4a11-9c66-4e53c29c46cc · outbound

This paper cites Video-p2p: Video editing with cross-attention control.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Video-p2p: Video editing with cross-attention control

Reference 30

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source=pdf_text observed=2026-08-07T05:14:34.362080Z digest=sha256:a8388a666d6855d1e7bdddb35d7c4564616c780a5f9e9b92617283e4133c6dc0

Observation 63adb5fa-a844-40ef-8c03-f06533a2e996 · outbound

This paper cites Evalcrafter: Benchmarking and evaluating large video generation models.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Evalcrafter: Benchmarking and evaluating large video generation models

Reference 31

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source=pdf_text observed=2026-08-07T05:14:34.365334Z digest=sha256:656247580ecfa4228a9192257ac35b58e7a83385527cfd5e16ec5e5f85852d7d

Observation 41342b3f-8813-476b-b273-718352b73270 · outbound

This paper cites Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.Advances in Neural Information Processing Systems, 35:5775–5787, 2022.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.Advances in Neural Information Processing Systems, 35:5775–5787, 2022

Reference 32

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.369644Z digest=sha256:c8cba0bc4ca2a167ee92f39be78e0f9ef126f7fb1618812661ded745fd256bfc

Observation ee6ea7ef-32eb-4116-86f7-d130725692c3 · outbound

This paper cites Latte: Latent Diffusion Transformer for Video Generation.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Latte: Latent Diffusion Transformer for Video Generation

Reference 33

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source=pdf_text observed=2026-08-07T05:14:34.373824Z digest=sha256:9abe4f29763497e3a4d07fec7386690045a55fb8036a080d9c8d91970010220f

Observation fd35daac-9868-4cdf-af26-bab68133503b · outbound

This paper cites Ntire 2019 challenge on video deblurring and super-resolution: Dataset and study.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Ntire 2019 challenge on video deblurring and super-resolution: Dataset and study

Reference 34

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raw_fallback, observed 2026-08-07T05:14:35.152991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.378094Z digest=sha256:2c7c9952e23d91ff7f880dc8301f57e0326b0dcd7397a724172228b6e62d7f3b

Observation 3e16e134-656c-432e-bda3-539eba90c7d5 · outbound

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

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation

Reference 35

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source=pdf_text observed=2026-08-07T05:14:34.381705Z digest=sha256:2ff06063ffbcb17b6fa489875274871f45e430b89072bb588e347517c57e8882

Observation 719aff2d-39a8-4622-9457-939439580efe · outbound

This paper cites Scalable diffusion models with transformers.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Scalable diffusion models with transformers

Reference 36

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no resolver link, observed 2026-08-07T05:14:34.385740Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.385740Z digest=sha256:563db5bd15ccae14a1ba8868eec8c85bad8a3e3b23b8a67adb9fea1cfa7a0716

Observation d77ebd67-cb59-4c52-9bf5-82dfeb0e93d8 · outbound

This paper cites Fatezero: Fusing attentions for zero-shot text-based video editing.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Fatezero: Fusing attentions for zero-shot text-based video editing

Reference 37

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.389674Z digest=sha256:5118eb96fc43ef089e6bf7cf7a9f9597116287b560e52e4d737bf02130c23837

Observation 885da697-5666-45e0-bc15-e26172ce5c7d · outbound

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

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s High- resolution image synthesis with latent diffusion models

Reference 38

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source=pdf_text observed=2026-08-07T05:14:34.393207Z digest=sha256:f6ad306b8cae6108ce3cecb4aa511534c10ce33ba1681253c04eb2aa541380ce

Observation 61376603-961d-476b-814e-082895cef0c6 · outbound

This paper cites Frame-recurrent video super- resolution.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Frame-recurrent video super- resolution

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:14:35.122310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.397393Z digest=sha256:d65703d4ac2340aa6ed11eb5bc0983e2074211f5d00faf61f307da141017c633

Observation 7a65a4ff-1df3-4ed1-bcd3-2e5b5d276809 · outbound

This paper cites Denoising Diffusion Implicit Models.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Denoising Diffusion Implicit Models

Reference 40

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no resolver link, observed 2026-08-07T05:14:34.401516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.401516Z digest=sha256:b5da54be69fe2073fd4b6ec6ab930b623dc4394aa6fb97eff1fe04cbd008267f

Observation bbba172e-7e5b-457b-84cc-394ebf6a2d43 · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024

Reference 41

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no resolver link, observed 2026-08-07T05:14:34.405534Z

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source=pdf_text observed=2026-08-07T05:14:34.405534Z digest=sha256:da0c51385af987c0ade846815c9c422495f5b7289b89b3ab601dad1f56e6d32d

Observation 98c59845-36e7-448f-994c-c7ef6cbaa8a8 · outbound

This paper cites Detail-revealing deep video super-resolution.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Detail-revealing deep video super-resolution

Reference 42

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raw_fallback, observed 2026-08-07T05:14:35.103685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.409902Z digest=sha256:48d126dfc6b83e8cce90d6cc5697c273941a259aa44241584594709702ad5639

Observation 16070d1c-b154-43d7-9783-06896cae23f1 · outbound

This paper cites Tdan: Temporally-deformable alignment network for video super-resolution.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Tdan: Temporally-deformable alignment network for video super-resolution

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:14:35.091233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.413955Z digest=sha256:61b638cb947b56a0ce72672fcf482c1d01cac33a42303dd5b060966e56545aa4

Observation aebf7027-e6f0-400e-9327-79fdc8ac8280 · outbound

This paper cites Ntire 2017 challenge on single image super-resolution: Methods and results.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Ntire 2017 challenge on single image super-resolution: Methods and results

Reference 44

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source=pdf_text observed=2026-08-07T05:14:34.417751Z digest=sha256:f44dca1080a4e24238d64f9006fe72a144e5c24ba7b9bc2b26773c395ca5f4dc

Observation 8b81ab2a-3e5d-40f6-8a1c-1dfc32601a09 · outbound

This paper cites Deformable non-local network for video super-resolution.IEEE Access, 7:177734–177744, 2019.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Deformable non-local network for video super-resolution.IEEE Access, 7:177734–177744, 2019

Reference 45

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raw_fallback, observed 2026-08-07T05:14:35.072693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.422328Z digest=sha256:70c954597c426b452672c3fb814ffe0dd40f258936ef7372ad40af7cdc827487

Observation 34240715-ac62-48f9-a9da-f908de70d521 · outbound

This paper cites Exploring clip for assessing the look and feel of images.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Exploring clip for assessing the look and feel of images

Reference 46

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.426245Z digest=sha256:5bed7b24f61e26e569f72737f65e2d66ffd0f1fcfe41c551b06f6439c29100d4

Observation 75eb13e1-e828-4652-8794-2ee5303f3f75 · outbound

This paper cites SeedVR: Seeding Infinity in Diffusion Transformer Towards Generic Video Restoration.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s SeedVR: Seeding Infinity in Diffusion Transformer Towards Generic Video Restoration

Reference 47

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:14:34.430493Z digest=sha256:0b2772a10178dd4c1594cfa256e2a05e3b557279a59cf14fe0327faa63b34c90

Observation 3f35847c-4f91-4691-a373-dc76af9b4120 · outbound

This paper cites Exploiting diffusion prior for real-world image super-resolution.International Journal of Computer Vision, 132(12):5929–5949, 2024.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Exploiting diffusion prior for real-world image super-resolution.International Journal of Computer Vision, 132(12):5929–5949, 2024

Reference 48

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source=pdf_text observed=2026-08-07T05:14:34.434921Z digest=sha256:5b6335e75a4b08822fce7e59b5a84b303c6d75f406fc7ef3aad46037bb5f61cf

Observation 30305726-bf7f-47da-8dd3-10c069bc9d17 · outbound

This paper cites Edvr: Video restoration with enhanced deformable convolutional networks.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Edvr: Video restoration with enhanced deformable convolutional networks

Reference 49

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:14:34.439340Z digest=sha256:e073118b81c85a0d37e48f672639c8f15dd7fee1c9ad668cce3fd73c24d07738

Observation 379338ea-fdca-4d57-9896-6a499c3f6b30 · outbound

This paper cites Real-esrgan: Training real-world blind super-resolution with pure synthetic data.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Real-esrgan: Training real-world blind super-resolution with pure synthetic data

Reference 50

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:14:34.443341Z digest=sha256:c1e92cef76d2ff00f1c91108620be3b825d7f253a8859b2cab45178ba6989392

Observation 97904ae3-6ba1-4064-ac93-4eeaa036d09e · outbound

This paper cites Exploring video quality assessment on user generated contents from aesthetic and technical perspectives.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Exploring video quality assessment on user generated contents from aesthetic and technical perspectives

Reference 51

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no resolver link, observed 2026-08-07T05:14:34.447814Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:14:34.447814Z digest=sha256:b2d54370d04a5114355850876c11b8023ae5dec76da8f4c35bccffdb94d7ac0b

Observation 6b9d2e34-1655-4e09-ab85-730707ef5d52 · outbound

This paper cites Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation

Reference 52

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raw_fallback, observed 2026-08-07T05:14:35.028989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.451910Z digest=sha256:e04d64374088cb6eef13692cc7195f0cc8cb28129c5cfb46344c0bb2cc55b879

Observation 81f99a4d-23d4-4305-93e9-60ef314c29f8 · outbound

This paper cites One-step effective diffusion network for real-world image super-resolution.Advances in Neural Information Processing Systems, 37:92529–92553, 2024.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s One-step effective diffusion network for real-world image super-resolution.Advances in Neural Information Processing Systems, 37:92529–92553, 2024

Reference 53

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raw_fallback, observed 2026-08-07T05:14:35.018151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.456528Z digest=sha256:f45e7a30bca1b03438f75aa36891c188b368bfcf50f2d400ba031821aef51e28

Observation d7904011-d320-47d4-917f-17094510024e · outbound

This paper cites Animesr: Learning real-world super- resolution models for animation videos.Advances in Neural Information Processing Systems, 35:11241–11252, 2022.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Animesr: Learning real-world super- resolution models for animation videos.Advances in Neural Information Processing Systems, 35:11241–11252, 2022

Reference 54

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raw_fallback, observed 2026-08-07T05:14:35.007343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.461000Z digest=sha256:ef44e8b8075d03fe6d0b3e8aa8fa675788293e11624b8e6fe61aa9973b6f225a

Observation 0cfed318-eeba-4040-9bfd-e3265328673a · outbound

This paper cites Diffir: Efficient diffusion model for image restoration.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Diffir: Efficient diffusion model for image restoration

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:14:34.995322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.465435Z digest=sha256:825edf24f9af05a02c8572ca6b822d2c8f2d92a9cf5bcda63157df364e376e23

Observation 8ae9a46f-81e3-4b1a-9ef3-e620afd1251a · outbound

This paper cites STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution

Reference 56

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no resolver link, observed 2026-08-07T05:14:34.469795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.469795Z digest=sha256:5e6978bb3297104e3d9374b36101a5cff9e41819ca5bdd24c05477210dab4630

Observation 6340dd44-c98f-475b-946c-b10c7a0198d9 · outbound

This paper cites Easyanimate: A high-performance long video generation method based on transformer architecture.arXiv preprint arXiv:2405.18991, 2024.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Easyanimate: A high-performance long video generation method based on transformer architecture.arXiv preprint arXiv:2405.18991, 2024

Reference 57

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.474576Z digest=sha256:7d8076fec1cb9f6e024814fab2e01c4e4fc94ecb61f8cc07c3e082db458bea57

Observation ad0fe9b3-eb28-4481-8801-ca1c23dbec34 · outbound

This paper cites Video enhancement with task-oriented flow.International Journal of Computer Vision, 127:1106–1125, 2019.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Video enhancement with task-oriented flow.International Journal of Computer Vision, 127:1106–1125, 2019

Reference 58

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verified fuzzy
raw_fallback, observed 2026-08-07T05:14:34.983828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.479115Z digest=sha256:e1dc3959b464495ba7003f0c0d1796050381511c6de93733d471b56bec22ca6d

Observation 947f9ff3-08c7-47b5-b5f8-3ff2d7f8fee7 · outbound

This paper cites Rerender a video: Zero-shot text-guided video-to-video translation.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Rerender a video: Zero-shot text-guided video-to-video translation

Reference 59

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no resolver link, observed 2026-08-07T05:14:34.484538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.484538Z digest=sha256:7f96bbcbd81b7f2d844b70b7161f7674195a1ff5a519ea198cc3b4d71808406c

Observation eee86b28-8378-407b-9700-76c5cd6a6fac · outbound

This paper cites Motion-guided latent diffusion for temporally consistent real-world video super-resolution.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Motion-guided latent diffusion for temporally consistent real-world video super-resolution

Reference 60

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raw_fallback, observed 2026-08-07T05:14:34.965606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.488794Z digest=sha256:0c1efe28ec698fcc12e6aa56ef20f38e1eefd834779373ffdf86edc484ed8a7d

Observation c71a0c62-3945-4d7a-ae0f-353f56984755 · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 61

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:14:34.493215Z digest=sha256:c233c699655b21c154915c227d406797c975dd5395b9f6a95f32cd06606f0bc5

Observation c2b05cf7-0b8e-4c8d-b715-44a78c224fc4 · outbound

This paper cites Progressive fusion video super-resolution network via exploiting non-local spatio-temporal correlations.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Progressive fusion video super-resolution network via exploiting non-local spatio-temporal correlations

Reference 62

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verified fuzzy
raw_fallback, observed 2026-08-07T05:14:34.953597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.498183Z digest=sha256:8d68ed7217c0f5b617a3c0547adac8b690845ab00decb8b1cddc5afff2885f06

Observation 613710f8-2784-4f20-934c-6f27193c8315 · outbound

This paper cites A feature-enriched completely blind image quality evaluator.IEEE Transactions on Image Processing, 24(8):2579–2591, 2015.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s A feature-enriched completely blind image quality evaluator.IEEE Transactions on Image Processing, 24(8):2579–2591, 2015

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:14:34.940622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.502843Z digest=sha256:f263e215a25d43f90e39f304fad6213ee82eb160cff4357b247a8fc98c493bc3

Observation b9b54d82-a0a0-47c1-af32-6ff45a3a5c9d · outbound

This paper cites The unrea- sonable effectiveness of deep features as a perceptual metric.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s The unrea- sonable effectiveness of deep features as a perceptual metric

Reference 64

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.507372Z digest=sha256:5cc1eefef0c6703091d7e8e2c3fb76def02d9c5ee3860d98eda2d74543015189

Observation 7b12eaa6-c816-467d-b5b6-fc971eb143f8 · outbound

This paper cites I2vgen-xl: High-quality image-to-video synthesis via cascaded diffusion models.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s I2vgen-xl: High-quality image-to-video synthesis via cascaded diffusion models

Reference 65

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verified fuzzy
raw_fallback, observed 2026-08-07T05:14:34.922215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.511849Z digest=sha256:bb41360c7e834e651496a772b04d2a90cb69f38b0ea19bdd40531391b26a46ef

Observation 20aa31d7-4751-42be-8f9e-6b44a38f1ffb · outbound

This paper cites Realviformer: Investigating attention for real-world video super-resolution.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Realviformer: Investigating attention for real-world video super-resolution

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:14:34.910598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.516682Z digest=sha256:281502a91f0e30075e5212abdbc1cde3224c6168587db62b0aa68afc8feb2244

Observation ac740761-24b5-49e1-b7a9-b174762e11c6 · outbound

This paper cites Upscale- a-video: Temporal-consistent diffusion model for real-world video super-resolution.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Upscale- a-video: Temporal-consistent diffusion model for real-world video super-resolution

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:14:34.898930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:14:34.521194Z digest=sha256:17a6fdd79476d08ca76a7b799e3e2926441ec967b272fb25858da11d237dce34

Observation 8253209a-f15b-4109-8aa9-f62985b08e33 · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-07T05:14:34.525958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:34.525958Z digest=sha256:f3e09632b8205f5bdd60d83a0da66c25409cf53f02bbbd2de6c126315da74bac

Pith citing papers

Observation 9713a6bc-b414-4d03-a6d6-007a2a6dbbe7 · inbound

NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models: Datasets, Methods and Results cites this paper.

NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models: Datasets, Methods and Results LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s

Reference 65

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:31:03.174967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T15:59:34.754260Z digest=sha256:ed64aad303621a7cd9cbf43a0bd32a43dcb586284ad826514bde80fb97431b24

Observation 454a408e-0199-4c18-ba13-ae1c39c62372 · inbound

Efficient Video Diffusion Models: Advancements and Challenges cites this paper.

Efficient Video Diffusion Models: Advancements and Challenges LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s

Reference 137

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:03:25.623144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T08:28:29.706249Z digest=sha256:776530484d3c4b63b0034b251853361937b82c2fb0c625c83bb726dab25489c5