Alternatives and similar repositories for show-control-and-tell

Users that are interested in show-control-and-tell are comparing it to the libraries listed below

• poojahira / image-captioning-bottom-up-top-down
  PyTorch implementation of Image captioning with Bottom-up, Top-down Attention
  ☆167Updated 6 years ago
• husthuaan / AoANet
  Code for paper "Attention on Attention for Image Captioning". ICCV 2019
  ☆335Updated 4 years ago
• fengyang0317 / unsupervised_captioning
  Code for Unsupervised Image Captioning
  ☆219Updated 2 years ago
• peteanderson80 / Up-Down-Captioner
  Automatic image captioning model based on Caffe, using features from bottom-up attention.
  ☆249Updated 2 years ago
• yahoo / object_relation_transformer
  Implementation of the Object Relation Transformer for Image Captioning
  ☆179Updated last year
• njchoma / transformer_image_caption
  Image Captioning based on Bottom-Up and Top-Down Attention model
  ☆104Updated 6 years ago
• aditya12agd5 / convcap
  ☆129Updated 6 years ago
• yangxuntu / SGAE
  ☆219Updated 3 years ago
• ruotianluo / Transformer_Captioning
  Use transformer for captioning
  ☆156Updated 6 years ago
• jiasenlu / NeuralBabyTalk
  Pytorch code of for our CVPR 2018 paper "Neural Baby Talk"
  ☆524Updated 6 years ago
• lukemelas / image-paragraph-captioning
  [EMNLP 2018] Training for Diversity in Image Paragraph Captioning
  ☆90Updated 6 years ago
• JDAI-CV / image-captioning
  Implementation of 'X-Linear Attention Networks for Image Captioning' [CVPR 2020]
  ☆275Updated 4 years ago
• nocaps-org / updown-baseline
  Baseline model for nocaps benchmark, ICCV 2019 paper "nocaps: novel object captioning at scale".
  ☆76Updated 2 years ago
• Cadene / murel.bootstrap.pytorch
  MUREL (CVPR 2019), a multimodal relational reasoning module for VQA
  ☆195Updated 5 years ago
• furkanbiten / GoodNews
  Good News Everyone! - CVPR 2019
  ☆128Updated 3 years ago
• violetteshev / bottom-up-features
  Bottom-up features extractor implemented in PyTorch.
  ☆72Updated 5 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
  ☆86Updated 5 years ago
• InnerPeace-Wu / densecap-tensorflow
  Re-implement CVPR2017 paper: "dense captioning with joint inference and visual context" and minor changes in Tensorflow. (mAP 8.296 after…
  ☆60Updated 6 years ago
• yufengm / Adaptive
  Pytorch Implementation of Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning
  ☆108Updated 8 years ago
• salesforce / densecap
  ☆191Updated 4 months ago
• ruotianluo / DiscCaptioning
  Code for Discriminability objective for training descriptive captions(CVPR 2018)
  ☆109Updated 5 years ago
• Cyanogenoid / vqa-counting
  [ICLR 2018] Learning to Count Objects in Natural Images for Visual Question Answering
  ☆207Updated 6 years ago
• aimbrain / vqa-project
  Code for our paper: Learning Conditioned Graph Structures for Interpretable Visual Question Answering
  ☆150Updated 6 years ago
• jnhwkim / ban-vqa
  Bilinear attention networks for visual question answering
  ☆546Updated last year
• cshizhe / asg2cap
  Code accompanying the paper "Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs" (Chen et al., …
  ☆200Updated 2 years ago
• kacky24 / stylenet
  A pytorch implemention of "StyleNet: Generating Attractive Visual Captions with Styles"
  ☆63Updated 4 years ago
• cvlab-tohoku / Dense-CoAttention-Network
  Improved Fusion of Visual and Language Representations by Dense Symmetric Co-Attention for Visual Question Answering
  ☆107Updated 6 years ago
• hengyuan-hu / bottom-up-attention-vqa
  An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge.
  ☆761Updated last year
• shilrley6 / Faster-R-CNN-with-model-pretrained-on-Visual-Genome
  Faster RCNN model in Pytorch version, pretrained on the Visual Genome with ResNet 101
  ☆239Updated 3 years ago
• facebookresearch / grid-feats-vqa
  Grid features pre-training code for visual question answering
  ☆269Updated 4 years ago