Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome

Meshed-Memory Transformer for Image Captioning. CVPR 2020

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

awesome grounding: A curated list of research papers in visual grounding

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

Automatic image captioning model based on Caffe, using features from bottom-up attention.

This repository contains my solutions to the assignments for Stanford's CS231n "Convolutional Neural Networks for Visual Recognition" (Spring 2020).

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

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

📸 Generates hashtags for Instagram posts. Upload your photo and it will suggest the relevant #hashtags for you. 🏷️

Adds SPICE metric to coco-caption evaluation server codes

Semantic Propositional Image Caption Evaluation

Learning to ground explanations of affect for visual art.

A simple implementation of neural image caption generator

CaMEL: Mean Teacher Learning for Image Captioning. ICPR 2022

Implementation of Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space

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)

EMNLP 2018. Learning to Describe Differences Between Pairs of Similar Images. Harsh Jhamtani, Taylor Berg-Kirkpatrick.

Deep CNN-LSTM for Generating Image Descriptions 😈

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 auto-tag/caption models for your purposes. Custom datasets can be added!