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Paper Citation Record · LEDGER

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution

As of 18 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2504.15649.

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

pith.paper-citation-record.v1
2504.15649 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:25:39.394007Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

36 of 36 outbound references displayed

  • verified exact0
  • verified fuzzy34
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fec21d05-8022-4742-8b3a-fb5728663e2b · outbound

This paper cites Ai benchmark: All about deep learning on smartphones in 2019.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Ai benchmark: All about deep learning on smartphones in 2019

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.978750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.230645Z digest=sha256:5aa57652ae5004e553e5e02d1ef5a340a76ed0741a89d73e25acdf29c27eb289

Observation 4bd2c3ab-0afe-46f0-9a64-989f5b06240c · outbound

This paper cites Ai benchmark: Running deep neural networks on android smartphones.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Ai benchmark: Running deep neural networks on android smartphones

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.963087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.235956Z digest=sha256:0be41c1fee35fe0916158f8c04f90d88eca194be93e30f2e259974ba7cfffff2

Observation 53a40ac0-59f7-450a-8e3e-1919bb6cc7a7 · outbound

This paper cites Fast, accurate, and lightweight super-resolution with cascading residual network.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Fast, accurate, and lightweight super-resolution with cascading residual network

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.947904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.240766Z digest=sha256:1ae2a9df1e8f4fa12bc30b7ad1d910b4acae92f851c2999518d240b3ef94a5fc

Observation 8be58f28-35ec-4030-8732-c149036681d1 · outbound

This paper cites Fast and memory-efficient network to- wards efficient image super-resolution.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Fast and memory-efficient network to- wards efficient image super-resolution

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.930367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.245426Z digest=sha256:78c0f956e91c4d3c512bd7189bc4eec1fd60989bf28ed395d6f555a759bbd9b7

Observation 79f8175b-4037-4b81-b946-6040a3827c5e · outbound

This paper cites Feature distillation interac- tion weighting network for lightweight image super- resolution.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Feature distillation interac- tion weighting network for lightweight image super- resolution

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.914678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.250364Z digest=sha256:d63a22be19d9e12439426d3da8ee14a71eb3418116a7e1a8288b343b468e2306

Observation 9d083639-9837-4aa6-b104-21dec1429385 · outbound

This paper cites Lightweight image super-resolution with in- formation multi-distillation network.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Lightweight image super-resolution with in- formation multi-distillation network

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.898796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.255334Z digest=sha256:57748dd6d01532720c81625e2f3084f92c666521091a2bc26213d83c4fa3e83f

Observation e0c41fd5-0f79-45e4-b463-30c51206170a · outbound

This paper cites C.; He K.; Dong, C.; Loy and X.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution C.; He K.; Dong, C.; Loy and X

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.882263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.260114Z digest=sha256:f654f65483157b7580640a426556289cd68d7c7eb1ceaa8ed438028517709eb2

Observation 53a46f6d-a965-4665-a975-a0e3f2a8e75a · outbound

This paper cites Ac- celerating the super-resolution convolutional neural network.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Ac- celerating the super-resolution convolutional neural network

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.867371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.265096Z digest=sha256:579af89ff81d15f283aed3ba9eacf4475087e3651f01d5ade90db81165212121

Observation 4be1f1a7-752e-4b5a-a129-7b34106854e1 · outbound

This paper cites Deeply-recursive convolutional network for image super-resolution.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Deeply-recursive convolutional network for image super-resolution

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.852308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.269470Z digest=sha256:f4e0fdb9ea4818b9d2f51ed37f7880ebc4a48019c97c61437247709700134ca6

Observation 52ddb942-78af-42b7-b3c7-fdb2e06ad14e · outbound

This paper cites Image super- resolution via deep recursive residual network.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Image super- resolution via deep recursive residual network

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.837262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.274660Z digest=sha256:a8fa3575d708cac2d799e3c8978bd1d8b9022906ef73489af1304239f732e1c1

Observation dfe13309-3790-4232-bc5f-c6d861609eb2 · outbound

This paper cites Fast and accurate single image super-resolution via information distillation network.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Fast and accurate single image super-resolution via information distillation network

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.822374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.279384Z digest=sha256:d7f37989c7b99408310c23f1d52e358e1abdc7b439cb5454492196d751b907ae

Observation 0c09f306-175a-498d-90b8-bf13dd95be3b · outbound

This paper cites Lightweight image super-resolution with in- formation multi-distillation network.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Lightweight image super-resolution with in- formation multi-distillation network

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.806413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.284473Z digest=sha256:bb79451a81857af4db17611287b37e7b0c90a653e086b6d77d2c5bd08759a2b9

Observation cb37f0ab-9fc5-4f9b-8a53-0990ba105349 · outbound

This paper cites Residual fea- ture distillation network for lightweight image super- resolution.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Residual fea- ture distillation network for lightweight image super- resolution

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.791905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.289590Z digest=sha256:7c8fb997208eafe377b81f329430b6210375bc928ef14d97aa8728c68b05791e

Observation 06be0932-654e-4f0b-b448-46bdb16f057b · outbound

This paper cites Ef- ficient long-range attention network for image super- resolution.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Ef- ficient long-range attention network for image super- resolution

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.776678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.294348Z digest=sha256:db3e73a9c34f5c97538c6ca852654a00ac7ff6d5171c8443d931c8bde95e131c

Observation 2506010b-65cf-43ce-9425-74be6f5ca7b6 · outbound

This paper cites Swinfir:revisiting the swinir with fast fourier convolution and improved training for image super-resolution.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Swinfir:revisiting the swinir with fast fourier convolution and improved training for image super-resolution

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.761476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.299010Z digest=sha256:fa7ff678e4b7e24b6248aacc203067b8bb715cd213cbafc4d567957231f495dc

Observation cf74be69-a661-4c04-8ad7-6d31956d9715 · outbound

This paper cites Lu, Zhisheng.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Lu, Zhisheng

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.746082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.303979Z digest=sha256:6d62e831276b607275dd25e1eebcac48ca6ad2980694da5cec47b1a6ee3c9f17

Observation aa1fd134-7b3d-4e63-8fc9-4f7217a1bdc6 · outbound

This paper cites Recurrent back-projection network for video superresolution.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Recurrent back-projection network for video superresolution

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.731570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.308636Z digest=sha256:c7367dad2f937d02f636c82e875a4c577025845417f7fb12e6e5bbcbd0a17748

Observation 5c666ecf-de91-45d7-a962-9254926c2cfa · outbound

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

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Tdan: Temporally deformable alignment network for video super-resolution

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.715583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.313236Z digest=sha256:34d58ac083397298f7f35581c019bab2bccad913468b4a3b37f818b231e4bb36

Observation 2ed3b4d7-83df-4bc4-b3ac-597099834c9b · outbound

This paper cites Chan and Chen Change Loy.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Chan and Chen Change Loy

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.700259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.318095Z digest=sha256:40207a6b8c840f084a404e839b515083ee3edd9bff6ceaec27b5128a3d16bd20

Observation 732f9c1f-a38c-4455-8876-58df2ba08c54 · outbound

This paper cites Efficient video super-resolution through recurrent latent space propagation.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Efficient video super-resolution through recurrent latent space propagation

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.686033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.322757Z digest=sha256:de5ae521a591b169e10a671d0657c67f87bd40b3f1d091ce32c9dc3c0d953261

Observation 4542add8-51ff-4216-9b7e-eae02b0c9d27 · outbound

This paper cites Bidirectional recurrent convolutional networks for multi-frame su- perresolution.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Bidirectional recurrent convolutional networks for multi-frame su- perresolution

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.670758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.327356Z digest=sha256:30dbfaa0e5f7d93e7c58a777a449097be6af87c124787a617e831881df54b2d9

Observation 49c91e7d-ece5-4835-a106-93c49719f185 · outbound

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

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Video super- resolution with recurrent structure-detail network

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.655732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.332000Z digest=sha256:43b72837637294bb9f2b4f07e7de9fec3d91a3d1e270d1ac6b9a8c8ab5204681

Observation 30e57f17-7fdb-4b29-a49e-6ce53d0311f5 · outbound

This paper cites Chan, Xintao Wang and Chen Change Loy.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Chan, Xintao Wang and Chen Change Loy

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.640277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.336425Z digest=sha256:75e6d98daf698fd66a53e4c95d9be57369610b73f46b73a1ffb32b3a2f8f2cd7

Observation a0493abd-cb77-45c8-9bc3-dbb7e5f49b0e · outbound

This paper cites Takashi Isobe, Fang Zhu.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Takashi Isobe, Fang Zhu

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.625008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.340850Z digest=sha256:afe04800ccb5c5bc8857959ac672e55d3bf4f56cf89aab121d7a3c178f7bbf33

Observation 9bbc8110-44fe-4c10-9e6e-c8bf85e54050 · outbound

This paper cites Neural architecture search for lightweight non-local networks.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Neural architecture search for lightweight non-local networks

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.607784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.345248Z digest=sha256:efb2fb36f7f6b761a764fc434341d5362532ff34b5de07d843f151de67e63eeb

Observation 948d43d5-03b3-45e1-9bf6-d94506096555 · outbound

This paper cites Fast, accurate, and lightweight super- resolution with neural architecture search.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Fast, accurate, and lightweight super- resolution with neural architecture search

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.591653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.349752Z digest=sha256:c6f2dfc33ff51e403b528e253fccced0ed6346ed6d11f07880e42e1a45f6f959

Observation 6e88bb9c-a79b-4e11-be5c-30442fd66ec3 · outbound

This paper cites Multi-objective neural architecture search for fast and accurate image super-resolution.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Multi-objective neural architecture search for fast and accurate image super-resolution

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.576799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.354005Z digest=sha256:115a3287040fc1121b343d0b6bda482b71294f17c1a330d9512997126c58e435

Observation 782833dd-f3ef-4a72-b1be-2d56225bf2e6 · outbound

This paper cites Repvgg: Making vgg-style convnets great again.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Repvgg: Making vgg-style convnets great again

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.561973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.358658Z digest=sha256:d43e2a8631b8d56be1ec1a0979753941cf3b7577e5f44c280ff785e021ad42c2

Observation a3ef11d4-e42e-46e6-8e5b-840ed500a8d6 · outbound

This paper cites Ecbsr: Edge-oriented convolution block for real-time super- resolution.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Ecbsr: Edge-oriented convolution block for real-time super- resolution

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.546988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.363141Z digest=sha256:0666bb03ad9645f9758b567cf0c58dffa4ded9853482eba0107ad22cc1992f61

Observation 0da79af0-90bc-4d95-a96d-a7175ead981d · outbound

This paper cites Repsr: Training efficient vgg- style super-resolution networks with structural re- parameterization.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Repsr: Training efficient vgg- style super-resolution networks with structural re- parameterization

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.532254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.367632Z digest=sha256:fb8b8d7c8255c8c8758c6584a00725688419eb5e7d100289bf7be631e8cf1bc3

Observation 9cfc37c5-6184-4da4-9b67-37bcb7f79b5d · outbound

This paper cites Numerical simulations of prominence oscillations triggered by external perturbations.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Numerical simulations of prominence oscillations triggered by external perturbations

Reference 31

Resolution
metadata mismatch
local_arxiv, observed 2026-08-16T11:25:39.438937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.371966Z digest=sha256:dee05a33faf549366607fec165c29a3ab8842a932b46fb1f40693d3b1172281f

Observation 172b8e95-ab2b-4080-a97a-130a40376303 · outbound

This paper cites Evsrnet: Efficient video super- resolution with neural architecture search.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Evsrnet: Efficient video super- resolution with neural architecture search

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.516176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.376622Z digest=sha256:598916b9a354e75a37a4cb8a682999d44edc986777d3385cbb234685a9f36f95

Observation 77282744-5f70-4a9d-9457-ab1a089094cc · outbound

This paper cites M., and Meng Z.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution M., and Meng Z

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.500207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.380973Z digest=sha256:4cb72bf364c184a42b285f96f4aefb542a089958fe7d08c47e850484d0a8204c

Observation 5617bc75-a765-4e95-8647-e7f232061ca0 · outbound

This paper cites Power efficient video super-resolution on mo- bile npus with deep learning, mobile ai & aim 2022 challenge: Report.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Power efficient video super-resolution on mo- bile npus with deep learning, mobile ai & aim 2022 challenge: Report

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.484774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.385324Z digest=sha256:4189752903a96a5289dc13e22cdb01b5b6aebf5d78831607b8e46088aedbe5e2

Observation 19cd42cb-bd17-4174-a32b-657589882a2e · outbound

This paper cites an unresolved cited work.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-16T11:25:39.469465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.389706Z digest=sha256:92d68d02bd7c5a309f1c62f3c5963f25c4f9c26a005e5d9ce0ce6a8a7ed9ddaf

Observation 09415124-8fea-4d30-9b3d-dd2f13d80704 · outbound

This paper cites Ntire 2019 challenge on video deblur- ring and superresolution: Dataset and study.

RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution Ntire 2019 challenge on video deblur- ring and superresolution: Dataset and study

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:39.454751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T11:25:39.394007Z digest=sha256:92105ce381cdc1b9d8ffab0ba81094f790a53e70a0bce807b6359a074fa7c371

Pith citing papers

No inbound Pith citation observations are available.