https://github.com/pokurin123/pix2pix_try
Image-to-Image Translation with Conditional Adversarial Networks
Papers with Code 아카이브
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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pomonam/AttentionCluster
https://github.com/pooriyasafaei/cityscapes_pix2pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/pprett/nut
Cross-Lingual Adaptation using Structural Correspondence Learning
https://github.com/ppriyank/Deep-neural-network-for-traffic-sign-recognition-systems
https://github.com/prabhakar267/LASER-improved
Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings
https://github.com/prabhupad26/100daysofML
https://github.com/prachetaphadnis/NMT_Seq2Seq_LexicalModel
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/prajjwal1/adaptive_transformer
https://github.com/prajjwal1/fluence
https://github.com/prajjwal1/language-modelling
https://github.com/prakashpandey9/BicycleGAN
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/prakhargurawa/Neural-Machine-Translation-Keras-Attention
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/prakhargurawa/Neural-Machine-Translation-Keras-German-English
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/pranavbudhwant/ACVAEGAN
Autoencoding beyond pixels using a learned similarity metric
https://github.com/pranay185417/delight
https://github.com/prasadsana/Eye_for_blind
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
https://github.com/pravn/vaegan
Autoencoding beyond pixels using a learned similarity metric
https://github.com/preetam1997/Self-Driven-Car
Virtual to Real Reinforcement Learning for Autonomous Driving
https://github.com/primecai/pix2nerf
Pix2NeRF: Unsupervised Conditional $π$-GAN for Single Image to Neural Radiance Fields Translation
https://github.com/princewang1994/R-FCN.pytorch
R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/princewang1994/RFCN_CoupleNet.pytorch
R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/pritam1322/Machine-Translation-with-Transformer
https://github.com/prithviraj-maurya/alexa-point-of-view-dataset
Converting the Point of View of Messages Spoken to Virtual Assistants
https://github.com/priyamtejaswin/multistep-retrieve-summarize
https://github.com/proroklab/popgym
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
https://github.com/pscmap13/pix2pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/pskrunner14/descriptor
https://github.com/pskugit/custom-conv2d
An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution
https://github.com/psunlpgroup/xsemplr
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
https://github.com/purvaten/punny_captions
Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge
https://github.com/puxinhe/im2txt_v3
Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge
https://github.com/pwc-1/Paper-10/tree/main/seamless_m4t
SeamlessM4T: Massively Multilingual & Multimodal Machine Translation
https://github.com/pwc-1/Paper-10/tree/main/speech_to_text
https://github.com/pwc-1/Paper-5/tree/main/mbart
https://github.com/pwc-1/Paper-5/tree/main/mbart50
IndicBART: A Pre-trained Model for Indic Natural Language Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.