Papers with Code 아카이브

Image Captioning

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 8
평가표: 34
보존된 평가 기록: 419

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/uzi0espil/research-papers-implementation/tree/master/Show%2C%20Attend%20and%20Tell%2C%20Neural%20Image%20Caption%20Generation%20with%20Visual%20Attention

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

Image Captioning

코드

https://github.com/uzi0espil/research-papers-implementation/tree/master/Show%2C%20Attend%20and%20Tell%2C%20Neural%20Image%20Caption%20Generation%20with%20Visual%20Attention

https://github.com/valencebond/FixMatch_pytorch

https://github.com/varun-bhaseen/Image-caption-generation-using-attention-model

https://github.com/vikramnitin9/nnfl

https://github.com/viplazylmht/image-captioning-inference

https://github.com/vipulgupta1011/swapmix

https://github.com/vis-nlp/chart-to-text

https://github.com/vladsandulescu/hatefulmemes

https://github.com/vlmaps/vlmaps

https://github.com/vlue-c/PyTorch-Explanations

https://github.com/vlue-c/Visual-Explanation-Methods-PyTorch

https://github.com/voxmenthe/OmniNet_1

https://github.com/vrama91/cider

https://github.com/vrama91/coco-caption

https://github.com/waggle-sensor/plugin-water-detector

https://github.com/walking-shadow/official_tssun

https://github.com/wangermeng2021/FastClassification

https://github.com/wangxiao5791509/Tracking-with-Deep-Reinforcement-Learning

https://github.com/weihaox/UMBRAE

https://github.com/wenhuchen/data-to-text-evaluation-metric

https://github.com/wickstrom/relax

https://github.com/widzemin/audio_project

https://github.com/windweller/PragmaticVQA

https://github.com/wisdomikezogwo/quilt1m

https://github.com/wl-research/nubia

https://github.com/wongkinyiu/yolov9

https://github.com/woodfrog/vse_infty

https://github.com/woonhahaha/place-classification

https://github.com/wtliao/layout2img

https://github.com/wubaoyuan/adversarial-attack-to-caption

https://github.com/x-plug/mplug

https://github.com/xden2331/attentive_cutmix

https://github.com/xiaobai714/image_caption

https://github.com/xmed-lab/dfg

https://github.com/xuewyang/Fashion-Image-Captioning-Benchmark

https://github.com/yangbang18/clfm