Methods › Computer Vision › Image Super-Resolution Models › ClassSR
ClassSR
Introduced by Xiangtao Kong et al. in ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
ClassSR is a framework to accelerate super-resolution (SR) networks on large images (2K-8K). ClassSR combines classification and SR in a unified framework. In particular, it first uses a Class-Module to classify the sub-images into different classes according to restoration difficulties, then applies an SR-Module to perform SR for different classes. The Class-Module is a conventional classification network, while the SR-Module is a network container that consists of the to-be-accelerated SR network and its simplified versions.
Papers archive 2025-07-28
1 shown of 1, 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.
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ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic 6 Mar 2021 · 3 repositories · arXiv:2103.04039Syntology ran 7 of 9 samples · 2 unverified · 9 pointer-only (licence)
Tasks archive 2025-07-28
5 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| 2k | 1 |
| 8k | 1 |
| Classification | 1 |
| General Classification | 1 |
| Super-Resolution | 1 |
Usage over time archive 2025-07-28
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
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