ChenRocks/UNITER

Research code for ECCV 2020 paper "UNITER: UNiversal Image-TExt Representation Learning"

39
/ 100
Emerging

This project helps researchers and developers working with computer vision and natural language processing tasks. It takes images and text as input and produces a unified representation that can be used for various downstream applications like image-text retrieval or visual question answering. It is intended for machine learning practitioners and researchers who need to train or fine-tune models for complex visual-linguistic understanding.

800 stars. No commits in the last 6 months.

Use this if you need to build or improve models that understand the relationship between images and text, such as systems that describe images, answer questions about visuals, or retrieve images based on text queries.

Not ideal if you are looking for a plug-and-play application for general users or if you don't have access to NVIDIA GPUs and a Docker environment.

Computer Vision Natural Language Processing Image-Text Understanding Multimodal AI Visual Question Answering
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 21 / 25

How are scores calculated?

Stars

800

Forks

113

Language

Python

License

Last pushed

Jun 30, 2021

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/transformers/ChenRocks/UNITER"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.