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  3. 飞桨学习赛:文档图像摩尔纹消除

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Baidu AI StudioComputer VisionBeginnerRegistration unverifiedRegistration unverified

飞桨学习赛:文档图像摩尔纹消除

适合已有计算机视觉和图像复原基础、能用 PaddlePaddle 2.0 及以上版本训练端到端模型的个人参赛者。参赛者应能处理成对的源图像与 GT 图像,并生成与测试输入同名、同尺寸的输出图片;比赛仅支持个人参赛。

Open official pageSign in to saveOpen guide

Suggested next step

Decide whether this contest fits your current stage before you sink time into the leaderboard.

Beginner score

78/100

Higher means a safer real starting point for your current stage.

Learning value

72/100

Measures whether the competition teaches habits you can transfer elsewhere.

Estimated effort

4-12 hours

Use this to check whether the task fits your current time budget.

Metric

Official scoring is published on the Ba…

If you cannot explain this metric clearly yet, you probably still need a bit of prep.

Who this competition fits

适合已有计算机视觉和图像复原基础、能用 PaddlePaddle 2.0 及以上版本训练端到端模型的个人参赛者。参赛者应能处理成对的源图像与 GT 图像,并生成与测试输入同名、同尺寸的输出图片;比赛仅支持个人参赛。

Official blurb (unedited)
百度网盘AI大赛由百度网盘开放平台发起,鼓励选手结合计算机视觉技术与图像处理技术,完成模型设计搭建与训练优化,产出基于飞桨框架的开源模型方案。 Official tags: 图像处理. Sign-ups: 188.

What this competition gives you

There is a baseline you can run as-is — starting from it is usually far faster than building from scratch.

BaselineForkable PaddlePaddle competition baseline notebook
Data

Competition training and test image datasets

TutorialBaseline explanation video
Reference paperMBCNN demoireing paper
Reference paperWDNet demoireing paper
Reference paperCamera-captured screen image demoireing paper
Reference paperMSSSIM reference paper
Reference paperAIM 2019 demoireing dataset study paper
DataTIP 2018 dataset on Google Drive
DataTIP 2018 dataset on Baidu Netdisk
DataAIM 2019 validation moiré images
DataAIM 2019 validation clear images
DataAIM 2019 testing dataset
BaselineMBCNN open-source reference code
BaselineWDNet open-source reference code

Prep before joining

If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.

PaddlePaddle 2.0+

图像到图像模型

图像去摩尔纹

图像预处理与尺寸对齐

PSNR 与 MS-SSIM

ZIP 结果文件打包

Where the real difficulty shows up

The real friction is usually not library usage. It is validation, time allocation, and task framing.

核心难点是在真实场景采集的屏摄图像中去除摩尔纹,同时尽量恢复原图细节,并兼顾未公开 GT 测试集上的泛化表现。排名同时考察像素误差和多尺度结构相似性,因此模型不能只做平滑降噪,还要保留视觉结构;提交还须严格满足同名同尺寸图片、根目录 ZIP 和 readme.txt 的格式要求。

Read this first

This guide is the best pre-read if you want a cleaner start instead of trial-and-error.

A pre-flight checklist for image competitions when you only have free cloud GPU access.

Your First CV Baseline Checklist

Your decision

Use these fields to make a quick decision before you dive deeper.

Status
Registration unverified
Registration
Registration unverified
Eligibility
Needs official confirmation
Reward
奖励积分
Compute
Free GPU OK
Official metric
Official scoring is published on the Baidu AI Studio competition page.
Verification
Source page verified

Registration is unverified; confirm availability on the official page before investing.

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Official source

Rules, files, submission details, and the live deadline still come from the official page.

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Data and review state

Separate what is confirmed from what still needs review. Official rules and deadlines win — report anything that looks wrong.

Source page verifiedMetric confirmedReviewed
Published on this site
Jul 21, 2026

Official metric is not published on the Baidu AI Studio competition listing; verify scoring on the competition page.