Meshed-Memory Transformer for Image Captioning. CVPR 2020

Show, Control and Tell: A Framework for Generating Controllable and Grounded Captions. CVPR 2019

A neural network to generate captions for an image using CNN and RNN with BEAM Search.

A modular library built on top of Keras and TensorFlow to generate a caption in natural language for any input image.

Positive-Augmented Contrastive Learning for Image and Video Captioning Evaluation. CVPR 2023

PyTorch code for: Learning to Generate Grounded Visual Captions without Localization Supervision

Display an image and text file side-by-side for easy manual caption editing.

A tool for downloading from public image boards (which allow scraping) / preview your images & tags / edit your images & tags. Additional tabs for downloading other desired code repositories as well as S.O.T.A. diffusion and clips models for your purposes. Custom datasets can be added!

A simple implementation of neural image caption generator

CaMEL: Mean Teacher Learning for Image Captioning. ICPR 2022

Code of our recently published attack FDA: Feature Disruptive Attack. Colab Notebook: https://colab.research.google.com/drive/1WhkKCrzFq5b7SNrbLUfdLVo5-WK5mLJh

End-to-end deep learning model for image captioning

Caption generator for live camera feed

A QT5 GUI to assist in captioning images for stablediffusion

Evaluating Visual Fidelity of Image Descriptions

Smart-I is an android application aimed at helping the visually impaired using artificial intelligence and cloud computing.

oCaption: Leveraging OpenAI's GPT-4 Vision for Advanced Image Captioning

Aid for blinds. This AI will describe the surrounding, it will tell who is in front of him (if that person is a known person to AI using Facial Recognition) and it will also help him to know what is written (Optical Character Recognition)

The BlipProcessor and BlipForConditionalGeneration are likely classes specific to a model called "Blip," which seems to be a transformer-based model for conditional text generation.

Public repo for the paper: "COSMic: A Coherence-Aware Generation Metric for Image Descriptions" by Mert İnan, Piyush Sharma, Baber Khalid, Radu Soricut, Matthew Stone, Malihe Alikhani