Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome
captioning-images 开源项目推荐(198 个)
captioning-images 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 198 个仓库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
Desktop image library for photographers and creators. Search by content, face or the text in a picture, get help from local AI models to tag and organise your images. Connect ComfyUI to generate and edit pictures, and AI-toolkit to train LoRAs. Also runs as a headless server.
VisText is a benchmark dataset for semantically rich chart captioning.
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.
Advanced AI tagging and prompt generation studio.
EMNLP 2018. Learning to Describe Differences Between Pairs of Similar Images. Harsh Jhamtani, Taylor Berg-Kirkpatrick.
[CVPR 2023 & IJCV 2025] Positive-Augmented Contrastive Learning for Image and Video Captioning Evaluation
Windows工具,用于并排图片与文本浏览、手动标题/标签编辑以及批量数据集操作。 非常适合LoRA和机器学习数据集准备,完全离线,私密且易于使用。
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/captioning-images。
- 该话题在 GitHub 上共有 198 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 5930 Star,覆盖 5 种主要语言,数据更新于 2026-11-10。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。