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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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하위 태스크

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평가표

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보존된 평가 기록

5

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/youngwanLEE/CenterMask

YOLACT: Real-time Instance Segmentation

https://github.com/yoyotv/Image-derain-via-CGAN

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/ypeleg/MinimalIsAllYouNeed

Attention Is All You Need

https://github.com/yuanmu97/secure-transformer-inference

Attention Is All You Need

https://github.com/yuantiku/fairseq-gec

Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data

https://github.com/yuekai146/NMT

Revisiting Low-Resource Neural Machine Translation: A Case Study

https://github.com/yueyongjiao/Transformer-Contextual

Attention Is All You Need

https://github.com/yueyongjiao/attention_is_all_you_need_pytorch

Attention Is All You Need

https://github.com/yuhangT/tf_bert

Attention Is All You Need

https://github.com/yuhui-zh15/nlg_metrics

BERTScore: Evaluating Text Generation with BERT

https://github.com/yukio326/gan-nmt

Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets

https://github.com/yukio326/reconstructor-nmt

English-Japanese Neural Machine Translation with Encoder-Decoder-Reconstructor

https://github.com/yumoh/speech-keras

Attention Is All You Need

https://github.com/yunjey/StarGAN

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

https://github.com/yunjey/mnist-svhn-transfer

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/yunjey/show-attend-and-tell

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

https://github.com/yunsukim86/sockeye-noise

Sockeye: A Toolkit for Neural Machine Translation

https://github.com/yunsukim86/wbw-lm

Word Translation Without Parallel Data

https://github.com/yurakuratov/t5-experiments

Adafactor: Adaptive Learning Rates with Sublinear Memory Cost

https://github.com/yurayli/image-caption-pytorch

Show and Tell: A Neural Image Caption Generator

https://github.com/yurayli/image_caption_pytorch

Show and Tell: A Neural Image Caption Generator

https://github.com/yurayli/stanford-cs224n-sol

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/yuriak/PPDAI

QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension

https://github.com/yuval-alaluf/restyle-encoder

Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation

https://github.com/yuwfan/FILTER

FILTER: An Enhanced Fusion Method for Cross-lingual Language Understanding

https://github.com/yuyay/chainer_nic

Show and Tell: A Neural Image Caption Generator

https://github.com/yuyuz/Variational-Reasoning-Networks

Variational Reasoning for Question Answering with Knowledge Graph

https://github.com/yuzhenmao/MI_P2V

MCMI: Multi-Cycle Image Translation with Mutual Information Constraints

https://github.com/yxgeee/MMT-plus

Improved Mutual Mean-Teaching for Unsupervised Domain Adaptive Re-ID

https://github.com/yxue3357/CycleGAN_pt

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/yxue3357/CycleGAN_tf

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/yxue3357/Mask-CycleGAN

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/yydai/bert_test

Attention Is All You Need

https://github.com/zankner/Transformer

Attention Is All You Need

https://github.com/zapplea/bert

Attention Is All You Need

https://github.com/zawlin/cvpr17_vtranse

Visual Translation Embedding Network for Visual Relation Detection

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.