Who leads the msda benchmark?

MetaSelf-Learning currently leads msda with a score of 42 on Accuracy.

What is the state-of-the-art score on msda?

The state-of-the-art result on msda is 42 (Accuracy), achieved by MetaSelf-Learning as of 2021.

How many models are tracked on msda?

Codesota tracks 2 models on msda.

When was the msda leaderboard last updated?

The msda leaderboard on Codesota includes results through 2021, with the earliest tracked result from 2018.

Codesota · Benchmark · msdaHome/Leaderboards/Vision & Documents/Scene Text Recognition/msda

Unknown

msda.

Name: msda Benchmark Results
Creator: Unknown
Published: 2018-01-01
License: https://creativecommons.org/licenses/by/4.0/

msda is a state-of-the-art machine learning benchmark indexed on Codesota. This page tracks published model results, top scores per metric, and the SOTA timeline for msda.

Paper ↗Leaderboard ↓

§ 01 · SOTA history

Year over year.

§ 02 · Leaderboard

Results by metric.

Only 2 models on this benchmark

Help build the community leaderboard — submit your model results.

Found a wrong score or missing run?

Use row edits to send a sourced correction into moderation.

Add / edit result ↗Report issue ↗

Accuracy

Accuracy is the reported evaluation metric for msda. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.

Higher is better

Trust tiers for Accuracyverifiedpapervendorcommunityunverified

Rank	Model	Trust	Score	Year	Links	Fix
01	MetaSelf-Learning From paper: Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark	verified	42	2021	Paper ↗Code ↗	Looks wrong?
02	MLDG From paper: Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond	verified	19.02	2018	Paper ↗Code ↗	Looks wrong?

§ 04 · Submit a result

Add to the leaderboard.

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