Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome
awesome grounding: A curated list of research papers in visual grounding
Meshed-Memory Transformer for Image Captioning. CVPR 2020
Learning to ground explanations of affect for visual art.
A neural network to generate captions for an image using CNN and RNN with BEAM Search.
Show, Control and Tell: A Framework for Generating Controllable and Grounded Captions. CVPR 2019
A modular library built on top of Keras and TensorFlow to generate a caption in natural language for any input image.
Automatic image captioning model based on Caffe, using features from bottom-up attention.
📸 Generates hashtags for Instagram posts. Upload your photo and it will suggest the relevant #hashtags for you. 🏷️ 
This repository contains my solutions to the assignments for Stanford's CS231n "Convolutional Neural Networks for Visual Recognition" (Spring 2020).
[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow
Semantic Propositional Image Caption Evaluation
VisText is a benchmark dataset for semantically rich chart captioning.
Implementation of Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space
Positive-Augmented Contrastive Learning for Image and Video Captioning Evaluation. CVPR 2023
Give your computer an AI Brain
EMNLP 2018. Learning to Describe Differences Between Pairs of Similar Images. Harsh Jhamtani, Taylor Berg-Kirkpatrick.
Adds SPICE metric to coco-caption evaluation server codes
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.
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