Translation
3185 papers with code • 2 benchmarks • 15 datasets
Benchmarks
These leaderboards are used to track progress in Translation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
Libraries
Use these libraries to find Translation models and implementationsDatasets
WMT 2016
xP3
CVSS
Oxford Radar RobotCar Dataset
Duolingo STAPLE Shared Task
Demetr
SpeechMatrix
ACES
FRMT
Most implemented papers
Attention Is All You Need
tensorflow/tensor2tensor
•
•
NeurIPS 2017
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration.
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
junyanz/pytorch-CycleGAN-and-pix2pix
•
•
ICCV 2017
Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image using a training set of aligned image pairs.
Image-to-Image Translation with Conditional Adversarial Networks
phillipi/pix2pix
•
•
CVPR 2017
We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems.
Neural Machine Translation by Jointly Learning to Align and Translate
Neural machine translation is a recently proposed approach to machine translation.
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
sgrvinod/a-PyTorch-Tutorial-to-Image-Captioning
•
•
Inspired by recent work in machine translation and object detection, we introduce an attention based model that automatically learns to describe the content of images.
Show and Tell: A Neural Image Caption Generator
karpathy/neuraltalk
•
•
CVPR 2015
Experiments on several datasets show the accuracy of the model and the fluency of the language it learns solely from image descriptions.
R-FCN: Object Detection via Region-based Fully Convolutional Networks
daijifeng001/r-fcn
•
•
NeurIPS 2016
In contrast to previous region-based detectors such as Fast/Faster R-CNN that apply a costly per-region subnetwork hundreds of times, our region-based detector is fully convolutional with almost all computation shared on the entire image.
YOLACT: Real-time Instance Segmentation
Then we produce instance masks by linearly combining the prototypes with the mask coefficients.
Effective Approaches to Attention-based Neural Machine Translation
philipperemy/keras-attention-mechanism
•
•
EMNLP 2015
Our ensemble model using different attention architectures has established a new state-of-the-art result in the WMT'15 English to German translation task with 25. 9 BLEU points, an improvement of 1. 0 BLEU points over the existing best system backed by NMT and an n-gram reranker.
Regularizing and Optimizing LSTM Language Models
salesforce/awd-lstm-lm
•
•
ICLR 2018
Recurrent neural networks (RNNs), such as long short-term memory networks (LSTMs), serve as a fundamental building block for many sequence learning tasks, including machine translation, language modeling, and question answering.
