Methods › Computer Vision › Video Super-Resolution Models › BasicVSR

BasicVSR

5 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

BasicVSR is a video super-resolution pipeline including optical flow and residual blocks. It adopts a typical bidirectional recurrent network. The upsampling module U contains multiple pixel-shuffle and convolutions. In the Figure, red and blue colors represent the backward and forward propagations, respectively. The propagation branches contain only generic components. S, W, and R refer to the flow estimation module, spatial warping module, and residual blocks, respectively.

Source: BasicVSR: The Search for Essential Components in Video...

Papers archive 2025-07-28

5 shown of 5, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

12 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Super-Resolution5
Video Super-Resolution5
Video Restoration2
Video deraining2
Analog Video Restoration1
Deblurring1
Denoising1
Optical Flow Estimation1
Snow Removal1
Video Deblurring1
Video Enhancement1
Video Reconstruction1

Usage over time archive 2025-07-28

Papers per year tagged with BasicVSR: 2020 to 2024, peak 1 1 0 2020: 1 paper 2020 2021: 1 paper 2021 2022: 1 paper 2022 2023: 1 paper 2023 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (5 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Video Super-Resolution Models

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