Papers with Code 아카이브
NLP based Person Retrival
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/gmum/dl-mo-2021
https://github.com/going-doer/paper2code
https://github.com/goldenbili/Bert_Test2
https://github.com/goldenbili/Bert_Test3
https://github.com/goldenbili/bert_lamb_pretrain
https://github.com/goluck-konuko/animation-based-codecs
Ultra-low bitrate video conferencing using deep image animation
https://github.com/gonglinyuan/metro_t0
Multitask Prompted Training Enables Zero-Shot Task Generalization
https://github.com/gongrennengzhi/nmt
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/gongshuangshuang/deep-text-corrector
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/goodluck4s/bert-
https://github.com/google-deepmind/spriteworld
Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs
https://github.com/google-research/bigbird
Leveraging Pre-trained Checkpoints for Sequence Generation Tasks
https://github.com/google-research/deeplab2
Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation
https://github.com/google-research/google-research/tree/master/tide
https://github.com/google-research/longt5
PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
https://github.com/google-research/scenic
https://github.com/google-research/t5x_retrieval
Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models
https://github.com/google/flax/tree/master/examples/wmt
https://github.com/google/lyra
https://github.com/google/sentencepiece
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
https://github.com/googlx/lasertagger
https://github.com/gooofy/zbrain
https://github.com/gooppe/transformer-summarization
https://github.com/gordicaleksa/pytorch-original-transformer
https://github.com/gotutiyan/GEC-BART
Stronger Baselines for Grammatical Error Correction Using Pretrained Encoder-Decoder Model
https://github.com/gouqi666/rast
https://github.com/gouthamvgk/coreml_conversion_hub
https://github.com/gpcv-liujin/REDNet
https://github.com/gpspelle/Crowd-Counting
MRCNet: Crowd Counting and Density Map Estimation in Aerial and Ground Imagery
https://github.com/gradio-app/saliency
Contextual Encoder-Decoder Network for Visual Saliency Prediction
https://github.com/graykode/gpt-2-Pytorch
https://github.com/graykode/nlp-tutorial
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://github.com/greentfrapp/adversarialautoencoder
https://github.com/greentfrapp/keras-aae
https://github.com/gtboauthors/gtbo
Noisy Adaptive Group Testing using Bayesian Sequential Experimental Design
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.