rese1f/aurora
[ICLR 2025] AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark
This project helps you create highly detailed descriptions for videos. You provide a video file and, in return, receive a comprehensive text caption explaining the visual content and events. This is ideal for content creators, marketers, educators, or anyone needing to automatically generate rich, descriptive text from video footage.
139 stars. No commits in the last 6 months.
Use this if you need to generate very precise and descriptive captions for your videos efficiently.
Not ideal if you only need very short, basic summaries or keyword tags for videos, as this focuses on detailed descriptions.
Stars
139
Forks
6
Language
Python
License
Apache-2.0
Category
Last pushed
Jun 04, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/rese1f/aurora"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
zarzouram/image_captioning_with_transformers
Pytorch implementation of image captioning using transformer-based model.
senadkurtisi/pytorch-image-captioning
Transformer & CNN Image Captioning model in PyTorch.
tojiboyevf/image_captioning
Deep Learning Final project 2022
Hamtech-ai/Persian-Image-Captioning
A Persian Image Captioning model based on Vision Encoder Decoder Models of the transformers🤗.
tanishqgautam/Image-Captioning
Implemented 3 different architectures to tackle the Image Caption problem, i.e, Merged...