Alternatives and similar repositories for py-bottom-up-attention

Users that are interested in py-bottom-up-attention are comparing it to the libraries listed below

• MILVLG / bottom-up-attention.pytorch
  A PyTorch reimplementation of bottom-up-attention models
  ☆301Updated 3 years ago
• yikuan8 / Transformers-VQA
  An implementation that downstreams pre-trained V+L models to VQA tasks. Now support: VisualBERT, LXMERT, and UNITER
  ☆164Updated 2 years ago
• poojahira / image-captioning-bottom-up-top-down
  PyTorch implementation of Image captioning with Bottom-up, Top-down Attention
  ☆166Updated 6 years ago
• facebookresearch / grid-feats-vqa
  Grid features pre-training code for visual question answering
  ☆268Updated 3 years ago
• pzzhang / VinVL
  project page for VinVL
  ☆355Updated last year
• yangxuntu / SGAE
  ☆219Updated 3 years ago
• JDAI-CV / image-captioning
  Implementation of 'X-Linear Attention Networks for Image Captioning' [CVPR 2020]
  ☆274Updated 3 years ago
• shilrley6 / Faster-R-CNN-with-model-pretrained-on-Visual-Genome
  Faster RCNN model in Pytorch version, pretrained on the Visual Genome with ResNet 101
  ☆238Updated 2 years ago
• husthuaan / AoANet
  Code for paper "Attention on Attention for Image Captioning". ICCV 2019
  ☆333Updated 4 years ago
• krasserm / fairseq-image-captioning
  Transformer-based image captioning extension for pytorch/fairseq
  ☆317Updated 4 years ago
• jiasenlu / vilbert_beta
  ☆478Updated 2 years ago
• LuoweiZhou / VLP
  Vision-Language Pre-training for Image Captioning and Question Answering
  ☆419Updated 3 years ago
• MILVLG / mcan-vqa
  Deep Modular Co-Attention Networks for Visual Question Answering
  ☆453Updated 4 years ago
• salaniz / pycocoevalcap
  Python 3 support for the MS COCO caption evaluation tools
  ☆322Updated 10 months ago
• yahoo / object_relation_transformer
  Implementation of the Object Relation Transformer for Image Captioning
  ☆178Updated 9 months ago
• violetteshev / bottom-up-features
  Bottom-up features extractor implemented in PyTorch.
  ☆72Updated 5 years ago
• aimagelab / meshed-memory-transformer
  Meshed-Memory Transformer for Image Captioning. CVPR 2020
  ☆538Updated 2 years ago
• forence / Awesome-Visual-Captioning
  This repository focus on Image Captioning & Video Captioning & Seq-to-Seq Learning & NLP
  ☆412Updated 2 years ago
• MILVLG / openvqa
  A lightweight, scalable, and general framework for visual question answering research
  ☆325Updated 3 years ago
• peteanderson80 / Up-Down-Captioner
  Automatic image captioning model based on Caffe, using features from bottom-up attention.
  ☆246Updated 2 years ago
• cshizhe / asg2cap
  Code accompanying the paper "Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs" (Chen et al., …
  ☆199Updated 2 years ago
• YiwuZhong / Sub-GC
  [ECCV 2020] Official code for "Comprehensive Image Captioning via Scene Graph Decomposition"
  ☆97Updated 10 months ago
• lukemelas / image-paragraph-captioning
  [EMNLP 2018] Training for Diversity in Image Paragraph Captioning
  ☆89Updated 5 years ago
• KunpengLi1994 / VSRN
  PyTorch code for ICCV'19 paper "Visual Semantic Reasoning for Image-Text Matching"
  ☆302Updated 5 years ago
• linjieli222 / VQA_ReGAT
  Research Code for ICCV 2019 paper "Relation-aware Graph Attention Network for Visual Question Answering"
  ☆183Updated 4 years ago
• ruotianluo / coco-caption
  ☆67Updated 2 years ago
• Cadene / murel.bootstrap.pytorch
  MUREL (CVPR 2019), a multimodal relational reasoning module for VQA
  ☆195Updated 5 years ago
• KaihuaTang / VQA2.0-Recent-Approachs-2018.pytorch
  A pytroch reimplementation of "Bilinear Attention Network", "Intra- and Inter-modality Attention", "Learning Conditioned Graph Structures…
  ☆294Updated 10 months ago
• fengyang0317 / unsupervised_captioning
  Code for Unsupervised Image Captioning
  ☆218Updated 2 years ago
• ezeli / BUTD_model
  A pytorch implementation of "Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering" for image captioning.
  ☆47Updated 3 years ago