captioning-images

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

[CVPR 2020] Meshed-Memory Transformer for Image Captioning

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.

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

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.

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

Official Repository of OmniCaptioner

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

Semantic Propositional Image Caption Evaluation

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

VisText is a benchmark dataset for semantically rich chart captioning.

PixlStash helps you find things in an image library that's gotten out of hand. It imports and tags your images automatically, then lets you search by content or face, sort the keepers from the rubbish, and serve data to other tools (like ComfyUI) with a REST API. Use the desktop version or run it headless as a server.

From dataset to trained LoRA to finished image or video. One browser workspace for your models, datasets, training, and generation. LoRA Pilot supports 50+ training model groups, with ComfyUI, Kohya, AI Toolkit, and Diffusion Pipe included. Run on your own GPU or RunPod, and connect AI agents through MCP.

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

Advanced AI tagging and prompt generation studio.

[CVPR 2023 & IJCV 2025] Positive-Augmented Contrastive Learning for Image and Video Captioning Evaluation

Windows tool for side-by-side image & text viewing, manual caption/tag editing, and batch dataset operations. Perfect for LoRA & ML dataset prep. 100% offline, private, and easy to use.