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  3. 飞桨学习赛:手写文字擦除

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Baidu AI StudioComputer VisionBeginnerRegistration unverifiedRegistration unverified

飞桨学习赛:手写文字擦除

适合已能用 PaddlePaddle 训练端到端视觉模型的开发者,尤其是想练习图像到图像转换、图像修复或场景文字擦除的人。个人即可参赛,且页面说明面向全社会开放;但提交模型必须使用 PaddlePaddle 2.0 及以上版本。

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

适合已能用 PaddlePaddle 训练端到端视觉模型的开发者,尤其是想练习图像到图像转换、图像修复或场景文字擦除的人。个人即可参赛,且页面说明面向全社会开放;但提交模型必须使用 PaddlePaddle 2.0 及以上版本。

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: 250.

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 baseline notebook
Data

Competition training and test image datasets

Reference paperMSSSIM reference paper
Reference paperEraseNet reference paper
Reference paperEnsNet reference paper
Reference paperCascaded text removal reference paper
Reference paperMTRNet++ reference paper
Reference paperMTRNet reference paper
DataSCUT-EnsText public dataset
DataSynthText public dataset
BaselineEraseNet open-source code
BaselineOfficial SceneTextRemoval TensorFlow implementation
BaselineMinimal SceneTextRemover PyTorch implementation
BaselineMTRNet/MTRNet++ open-source code
BaselineEnsNet open-source 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

图像修复与文本擦除

PSNR 与 MS-SSIM 优化

PNG 图像批量处理

ZIP 提交文件组织

Where the real difficulty shows up

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

难点是既要去除试卷图像中的手写痕迹,又要精确恢复被笔迹遮挡的原始内容;测试集 GT 不公开,需让模型在真实场景处理而来的图像上保持泛化。除训练效果外,还必须严格生成与输入同名、同尺寸的 PNG,并将结果与 readme.txt 以无文件夹层级的 ZIP 提交。

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.