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
Papers with Code 아카이브
Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 4
- 보존된 평가 기록
- 5
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/uzielroy/CUT
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/vGkatsis/Chat_Bot_DL
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://github.com/vadimkantorov/ctc
A Stable and Effective Learning Strategy for Trainable Greedy Decoding
https://github.com/vaibhavjindal/pix2pix-pytorch
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/valentinmace/noisy-text
https://github.com/vamsi3/pix2pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/vanhuyz/CycleGAN-TensorFlow
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/vanpersie32/Multigpu-Bert
https://github.com/vanslerry/long_text
https://github.com/varshinireddyt/ULMFiT
https://github.com/varun-bhaseen/Image-caption-generation-using-attention-model
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/vchopin/GNMT_v2
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
https://github.com/veekaybee/what_are_embeddings
https://github.com/vene/sparse-structured-attention
A Regularized Framework for Sparse and Structured Neural Attention
https://github.com/venkat-ravilla/DAP
Guiding attention in Sequence-to-sequence models for Dialogue Act prediction
https://github.com/venkateshdudipalli/Self-Driving-Car
Virtual to Real Reinforcement Learning for Autonomous Driving
https://github.com/verbeemen/south-park-avatar-generator
XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings
https://github.com/vergilus/NJUNMT-pytorch/tree/master/adversarials
A Reinforced Generation of Adversarial Examples for Neural Machine Translation
https://github.com/vg-sravan/Cycle-Consistent-Generative-Adversarial-Networks
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/vganesh46/awd-lstm-pytorch-implementation
https://github.com/vgaraujov/seq2seq-spanish-plms
https://github.com/vicsesi/PyTorch-STN
https://github.com/vict0rsch/ArxivTools
Attention-Guided Generative Adversarial Networks for Unsupervised Image-to-Image Translation
https://github.com/vict0rsch/PaperMemory
Attention-Guided Generative Adversarial Networks for Unsupervised Image-to-Image Translation
https://github.com/vict0rsch/arxiv-pdf-abs
Attention-Guided Generative Adversarial Networks for Unsupervised Image-to-Image Translation
https://github.com/vietai/SAT
https://github.com/vijay120/bert
https://github.com/vikashranjan/transformer
https://github.com/viking-sudo-rm/StackNN
https://github.com/vikua/keras-attention-models
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/vinairesearch/phogpt
https://github.com/vinayak19th/Brevis-2.0
https://github.com/vinayprabhu/X-is-all-you-need
https://github.com/vinod377/STN-OCR
https://github.com/vinod377/STN-OCR-Tensorflow
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.