# Srameo/LED

<https://repo.masters-masters.com/en/repos/Srameo/LED>

[Home](https://repo.masters-masters.com/en) › [Srameo](https://repo.masters-masters.com/en/owners/Srameo) › [LED](https://repo.masters-masters.com/en/repos/Srameo/LED)

Srameo/LED has 412 stars on GitHub. Its RepoMasters card: Alpha tier. \[ICCV 2023\] Lighting Every Darkness in Two Pairs: A Calibration-Free Pipeline for RAW…

| Field | Value |
| --- | --- |
| Owner | [Srameo](https://repo.masters-masters.com/en/owners/Srameo) |
| Stars | 412 |
| Forks | 43 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2023 |
| Topics | denoising, fast-deploy, fewshot, low-light, noise-modeling, pytorch, raw, raw-image, deep-learning, unet |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [Srameo/LED](https://github.com/Srameo/LED) |

## Repository

\[ICCV 2023\] Lighting Every Darkness in Two Pairs: A Calibration-Free Pipeline for RAW Denoising && \[Arxiv 2023\] Make Explicit Calibration Implicit: Calibrate Denoiser Instead of the Noise Model && \[NeurIPS 2025\] UltraLED: Learning to See Everything in Ultra-High Dynamic Range Scenes

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.