AILab-CVC/UniRepLKNet

[CVPR 2024 & TPAMI 2025] UniRepLKNet

43
/ 100
Emerging

This project offers a unified deep learning model that processes various types of data, including images, audio, and time-series, to perform tasks like object recognition, sound classification, and environmental forecasting. It provides a single architecture that can adapt to different data without extensive customization, producing highly accurate predictions. Researchers and practitioners in fields requiring strong general perception models for diverse data will find this useful.

1,069 stars. No commits in the last 6 months.

Use this if you need a high-performing, adaptable model that can effectively analyze different data types, like images, audio, and global weather patterns, with a single unified architecture.

Not ideal if you require highly specialized, domain-specific models that are already optimized for a single data modality with unique architectural needs.

image-recognition audio-analysis time-series-forecasting multimodal-data environmental-prediction
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 15 / 25

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Stars

1,069

Forks

61

Language

Python

License

Apache-2.0

Last pushed

Aug 10, 2025

Commits (30d)

0

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