Awesome-Image-Captioning

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awesome-image-captioning is an Open Source Research & Education tool that provides a curated list of image captioning and related area resources. It offers a comprehensive collection of papers and implementations for researchers.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is awesome-image-captioning?

awesome-image-captioning is an open-source GitHub repository offering a meticulously curated list of resources focused on image captioning and related fields. It serves as a valuable hub for researchers and practitioners, providing an extensive collection of academic papers categorized by year, from before 2015 up to 2020. The repository also includes information on datasets, image captioning challenges, and popular implementations in frameworks like PyTorch and TensorFlow. Contributions are welcomed via pull requests or email, fostering a collaborative environment for keeping the resource up-to-date and comprehensive.

Best used for

Ideal for researchers and students who need to conduct literature reviews, explore state-of-the-art image captioning techniques, and find relevant datasets or code implementations. Especially valuable for those looking to quickly grasp the historical and current landscape of image captioning research.

Common actions

find research papers

explore image captioning

discover implementations

review academic literature

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Capabilities

Key features

Curated paper list
Categorized by year
Dataset information
Challenge details
Popular implementations

Target Audience

professorresearcherstudent

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

How can I contribute to the awesome-image-captioning list?

You can contribute to the list by sending pull requests on GitHub or by emailing the maintainer directly. The preferred format for contributions is Markdown, including the paper name, link, authors, conference year, and an optional link to the code.

What kind of resources are included in this repository?

The repository includes a comprehensive list of academic papers on image captioning and related areas, categorized by publication year. It also features sections for datasets, image captioning challenges, and popular code implementations in frameworks like PyTorch and TensorFlow.

Is there a specific focus on certain image captioning techniques or models?

The list covers a broad range of image captioning techniques, from early approaches to more recent advancements, including deep learning models, attention mechanisms, and generative adversarial networks. Papers are organized chronologically, allowing users to trace the evolution of the field.

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Subcategories trending in Research & Education

Study Assistants Knowledge Management Course Creation Scientific Computing Summarization Language Learning

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This tool also appears in

Coding & Development › Open Source & Models

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