Methods › Computer Vision › Image Restoration Models › TLC

Test-time Local Converter

TLC

10 papers tagged archive 2025-07-28

Introduced by Xiaojie Chu et al. in Improving Image Restoration by Revisiting Global Information Aggregation

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

TLC convert the global operation to a local one so that it extract representations based on local spatial region of features as in training phase.

PaperSource

Papers archive 2025-07-28

10 shown of 10, 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

20 shown of 31 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
All1
Class Incremental Learning1
Color Image Denoising1
Continual Learning1
Deblurring1
Denoising1
Feature Engineering1
Generalization Bounds1
Grayscale Image Denoising1
Hallucination1
Image Captioning1
Image Deblurring1
Image Defocus Deblurring1
Image Dehazing1
Image Denoising1
Image Restoration1
Incremental Learning1
Language Modelling1
Learning Theory1
Management1

Usage over time archive 2025-07-28

Papers per year tagged with TLC: 2021 to 2025, peak 4 4 0 2021: 1 paper 2021 2022: 1 paper 2022 2023: 4 papers 2023 2024: 3 papers 2024 2025: 1 paper 2025
Papers per year the archive tags with this method, by the paper's archive date (10 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

Image Restoration Models

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