https://github.com/AaronCCWong/Show-Attend-and-Tell
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Papers with Code 아카이브
Image Captioning
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Image Captioning is the task of describing the content of an image in words. This task lies at the intersection of computer vision and natural language processing. Most image captioning systems use an encoder-decoder framework, where an input image is encoded into an intermediate representation of the information in the image, and then decoded into a descriptive text sequence. The most popular benchmarks are nocaps and COCO, and models are typically evaluated according to a BLEU or CIDER metric.
( Image credit: Reflective Decoding Network for Image Captioning, ICCV'19)
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Adk2001tech/Molecular-Translation-with-Deep-Learning
https://github.com/AhmadQasim/FixMatch
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
https://github.com/Aman-4-Real/MMTG
WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training
https://github.com/AndreiMoraru123/ContextCollector
https://github.com/AndreiMoraru123/Watch-and-Tell
https://github.com/Anjaney1999/image-captioning-seqgan
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
https://github.com/Arizona-Voice/blossom
https://github.com/ArnaudBru/Generative-Pseudo-label-Refinement-for-Unsupervised-Domain-Adaptation
Generative Pseudo-label Refinement for Unsupervised Domain Adaptation
https://github.com/Atharva-Phatak/Generating-Webpages-from-Screenshots
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
https://github.com/AtluriNikhil/Image-Captioning
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
https://github.com/BAAI-DCAI/Training-Data-Synthesis
https://github.com/BAAI-WuDao/BriVl
WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training
https://github.com/BJennWare/ImcaptionNet
Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning
https://github.com/Bennie-Han/Image-augementation-pytorch
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/BestiVictory/AMAN
https://github.com/BierOne/VQA-AttReg
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/BigRedT/info-ground
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/BugOMan/summary_generator
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
https://github.com/CSDN-AI7/image_caption
https://github.com/Carlisle-Liu/SBNet
Learning structure-aware semantic segmentation with image-level supervision
https://github.com/Cathy-t/HELLO_image
https://github.com/Celiali/FixMatch
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
https://github.com/Chen-Yang-Liu/Awesome-RS-SpatioTemporal-VLMs
Remote Sensing Temporal Vision-Language Models: A Comprehensive Survey
https://github.com/ChiZhangRIT/BNRHN
Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge
https://github.com/Chloejay/image_caption_app
https://github.com/Chumsy0725/DGWM
https://github.com/Chung-I/Variational-Recurrent-Autoencoder-Tensorflow
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
https://github.com/Cloud-CV/visual-chatbot
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/CoinCheung/fixmatch
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
https://github.com/CoinCheung/fixmatch-pytorch
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
https://github.com/CristianoPatricio/zsl-methods
https://github.com/Danyache/skoltech_image_cap
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
https://github.com/Data-drone/cvnd_image_captioning
https://github.com/DeepRNN/image_captioning
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
https://github.com/DevBruce/CutMixImageDataGenerator_For_Keras
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.