Image Caption GeneratorA neural network to generate captions for an image using CNN and RNN with BEAM Search.
Stars: ✭ 126 (+162.5%)
SightseqComputer vision tools for fairseq, containing PyTorch implementation of text recognition and object detection
Stars: ✭ 116 (+141.67%)
Gisgis (go image server) go 实现的图片服务,实现基本的上传,下载,存储,按比例裁剪等功能
Stars: ✭ 108 (+125%)
Video2descriptionVideo to Text: Generates description in natural language for given video (Video Captioning)
Stars: ✭ 107 (+122.92%)
Medical Report GenerationA pytorch implementation of On the Automatic Generation of Medical Imaging Reports.
Stars: ✭ 100 (+108.33%)
ArnetCVPR 2018 - Regularizing RNNs for Caption Generation by Reconstructing The Past with The Present
Stars: ✭ 94 (+95.83%)
CameramanagerSimple Swift class to provide all the configurations you need to create custom camera view in your app
Stars: ✭ 1,130 (+2254.17%)
Coco CnEnriching MS-COCO with Chinese sentences and tags for cross-lingual multimedia tasks
Stars: ✭ 57 (+18.75%)
Image CaptioningImage Captioning: Implementing the Neural Image Caption Generator with python
Stars: ✭ 52 (+8.33%)
Image captioninggenerate captions for images using a CNN-RNN model that is trained on the Microsoft Common Objects in COntext (MS COCO) dataset
Stars: ✭ 51 (+6.25%)
Bottom Up AttentionBottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome
Stars: ✭ 989 (+1960.42%)
Punny captionsAn implementation of the NAACL 2018 paper "Punny Captions: Witty Wordplay in Image Descriptions".
Stars: ✭ 31 (-35.42%)
Im2pTensorflow implementation of paper: A Hierarchical Approach for Generating Descriptive Image Paragraphs
Stars: ✭ 15 (-68.75%)
Neural Image CaptioningImplementation of Neural Image Captioning model using Keras with Theano backend
Stars: ✭ 12 (-75%)
Self Critical.pytorchUnofficial pytorch implementation for Self-critical Sequence Training for Image Captioning. and others.
Stars: ✭ 716 (+1391.67%)
OmninetOfficial Pytorch implementation of "OmniNet: A unified architecture for multi-modal multi-task learning" | Authors: Subhojeet Pramanik, Priyanka Agrawal, Aman Hussain
Stars: ✭ 448 (+833.33%)
NeuralmonkeyAn open-source tool for sequence learning in NLP built on TensorFlow.
Stars: ✭ 400 (+733.33%)
OscarOscar and VinVL
Stars: ✭ 396 (+725%)
Virtex[CVPR 2021] VirTex: Learning Visual Representations from Textual Annotations
Stars: ✭ 323 (+572.92%)
ScanPyTorch source code for "Stacked Cross Attention for Image-Text Matching" (ECCV 2018)
Stars: ✭ 306 (+537.5%)
AdaptiveattentionImplementation of "Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning"
Stars: ✭ 303 (+531.25%)
Image CaptioningImage Captioning using InceptionV3 and beam search
Stars: ✭ 290 (+504.17%)
im2pTensorflow implement of paper: A Hierarchical Approach for Generating Descriptive Image Paragraphs
Stars: ✭ 43 (-10.42%)
captioning chainerA fast implementation of Neural Image Caption by Chainer
Stars: ✭ 17 (-64.58%)
stylenetA pytorch implemention of "StyleNet: Generating Attractive Visual Captions with Styles"
Stars: ✭ 58 (+20.83%)
CS231nMy solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition
Stars: ✭ 30 (-37.5%)
image-captioning-DLCTOfficial pytorch implementation of paper "Dual-Level Collaborative Transformer for Image Captioning" (AAAI 2021).
Stars: ✭ 134 (+179.17%)
Machine-LearningThe projects I do in Machine Learning with PyTorch, keras, Tensorflow, scikit learn and Python.
Stars: ✭ 54 (+12.5%)
Image-CaptionUsing LSTM or Transformer to solve Image Captioning in Pytorch
Stars: ✭ 36 (-25%)
RSTNetRSTNet: Captioning with Adaptive Attention on Visual and Non-Visual Words (CVPR 2021)
Stars: ✭ 71 (+47.92%)
Awesome-CaptioningA curated list of Multimodal Captioning related research(including image captioning, video captioning, and text captioning)
Stars: ✭ 56 (+16.67%)
Show-Attend-and-TellA PyTorch implementation of the paper Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Stars: ✭ 58 (+20.83%)
AdaptivePytorch Implementation of Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning
Stars: ✭ 97 (+102.08%)
MIACode for "Aligning Visual Regions and Textual Concepts for Semantic-Grounded Image Representations" (NeurIPS 2019)
Stars: ✭ 57 (+18.75%)
gramtionTwitter bot for generating photo descriptions (alt text)
Stars: ✭ 21 (-56.25%)
Image-CaptioiningThe objective is to process by generating textual description from an image – based on the objects and actions in the image. Using generative models so that it creates novel sentences. Pipeline type models uses two separate learning process, one for language modelling and other for image recognition. It first identifies objects in image and prov…
Stars: ✭ 20 (-58.33%)
Show and TellShow and Tell : A Neural Image Caption Generator
Stars: ✭ 74 (+54.17%)
LaBERTA length-controllable and non-autoregressive image captioning model.
Stars: ✭ 50 (+4.17%)
BUTD modelA pytorch implementation of "Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering" for image captioning.
Stars: ✭ 28 (-41.67%)
UdacityThis repo includes all the projects I have finished in the Udacity Nanodegree programs
Stars: ✭ 57 (+18.75%)
udacity-cvnd-projectsMy solutions to the projects assigned for the Udacity Computer Vision Nanodegree
Stars: ✭ 36 (-25%)
catrImage Captioning Using Transformer
Stars: ✭ 206 (+329.17%)
Node Sdk☄️ Node.js library to access IBM Watson services.
Stars: ✭ 1,471 (+2964.58%)
Deep Learning DrizzleDrench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Stars: ✭ 9,717 (+20143.75%)
G-SimCLRThis is the code base for paper "G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling" by Souradip Chakraborty, Aritra Roy Gosthipaty and Sayak Paul.
Stars: ✭ 69 (+43.75%)
InvolutionPyTorch reimplementation of the paper "Involution: Inverting the Inherence of Convolution for Visual Recognition" (2D and 3D Involution) [CVPR 2021].
Stars: ✭ 98 (+104.17%)
watson-waste-sorterCreate an iOS phone application that sorts waste into three categories (landfill, recycling, compost) using a Watson Visual Recognition custom classifier
Stars: ✭ 45 (-6.25%)