Alternatives and similar repositories for awesome-image-captioning

Users that are interested in awesome-image-captioning are comparing it to the libraries listed below

• peteanderson80 / bottom-up-attention
  Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome
  ☆1,453Updated 2 years ago
• ruotianluo / self-critical.pytorch
  Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning. and others.
  ☆1,004Updated last year
• ruotianluo / ImageCaptioning.pytorch
  I decide to sync up this repo and self-critical.pytorch. (The old master is in old master branch for archive)
  ☆1,471Updated last year
• aimagelab / meshed-memory-transformer
  Meshed-Memory Transformer for Image Captioning. CVPR 2020
  ☆542Updated 2 years ago
• microsoft / Oscar
  Oscar and VinVL
  ☆1,051Updated 2 years ago
• jokieleung / awesome-visual-question-answering
  A curated list of Visual Question Answering(VQA)(Image/Video Question Answering),Visual Question Generation ,Visual Dialog ,Visual Common…
  ☆665Updated 2 years ago
• airsplay / lxmert
  PyTorch code for EMNLP 2019 paper "LXMERT: Learning Cross-Modality Encoder Representations from Transformers".
  ☆961Updated 2 years ago
• husthuaan / AoANet
  Code for paper "Attention on Attention for Image Captioning". ICCV 2019
  ☆333Updated 4 years ago
• tylin / coco-caption
  ☆1,195Updated last year
• hengyuan-hu / bottom-up-attention-vqa
  An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge.
  ☆759Updated last year
• LuoweiZhou / VLP
  Vision-Language Pre-training for Image Captioning and Question Answering
  ☆422Updated 3 years ago
• forence / Awesome-Visual-Captioning
  This repository focus on Image Captioning & Video Captioning & Seq-to-Seq Learning & NLP
  ☆412Updated 2 years ago
• krasserm / fairseq-image-captioning
  Transformer-based image captioning extension for pytorch/fairseq
  ☆317Updated 4 years ago
• facebookresearch / vilbert-multi-task
  Multi Task Vision and Language
  ☆817Updated 3 years ago
• yuewang-cuhk / awesome-vision-language-pretraining-papers
  Recent Advances in Vision and Language PreTrained Models (VL-PTMs)
  ☆1,155Updated 3 years ago
• sgrvinod / a-PyTorch-Tutorial-to-Image-Captioning
  Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning
  ☆2,864Updated 3 years ago
• MILVLG / mcan-vqa
  Deep Modular Co-Attention Networks for Visual Question Answering
  ☆455Updated 4 years ago
• jackroos / VL-BERT
  Code for ICLR 2020 paper "VL-BERT: Pre-training of Generic Visual-Linguistic Representations".
  ☆744Updated 2 years ago
• JDAI-CV / image-captioning
  Implementation of 'X-Linear Attention Networks for Image Captioning' [CVPR 2020]
  ☆274Updated 4 years ago
• ChenRocks / UNITER
  Research code for ECCV 2020 paper "UNITER: UNiversal Image-TExt Representation Learning"
  ☆797Updated 4 years ago
• salaniz / pycocoevalcap
  Python 3 support for the MS COCO caption evaluation tools
  ☆324Updated last year
• poojahira / image-captioning-bottom-up-top-down
  PyTorch implementation of Image captioning with Bottom-up, Top-down Attention
  ☆166Updated 6 years ago
• kuanghuei / SCAN
  PyTorch source code for "Stacked Cross Attention for Image-Text Matching" (ECCV 2018)
  ☆566Updated 2 years ago
• jiasenlu / NeuralBabyTalk
  Pytorch code of for our CVPR 2018 paper "Neural Baby Talk"
  ☆525Updated 6 years ago
• uclanlp / visualbert
  Code for the paper "VisualBERT: A Simple and Performant Baseline for Vision and Language"
  ☆537Updated 2 years ago
• fawazsammani / knowing-when-to-look-adaptive-attention
  PyTorch Implementation of Knowing When to Look: Adaptive Attention via a Visual Sentinal for Image Captioning
  ☆85Updated 5 years ago
• MILVLG / bottom-up-attention.pytorch
  A PyTorch reimplementation of bottom-up-attention models
  ☆302Updated 3 years ago
• jiasenlu / vilbert_beta
  ☆478Updated 2 years ago
• airsplay / py-bottom-up-attention
  PyTorch bottom-up attention with Detectron2
  ☆235Updated 3 years ago
• peteanderson80 / Up-Down-Captioner
  Automatic image captioning model based on Caffe, using features from bottom-up attention.
  ☆246Updated 2 years ago