SOTAVerified

Multimodal Machine Translation

Multimodal machine translation is the task of doing machine translation with multiple data sources - for example, translating "a bird is flying over water" + an image of a bird over water to German text.

( Image credit: Findings of the Third Shared Task on Multimodal Machine Translation )

Papers

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Showing 76–100 of 108 papers

TitleStatusHype
CUNI System for the WMT18 Multimodal Translation Task—0
Findings of the 2018 Conference on Machine Translation (WMT18)—0
Findings of the Third Shared Task on Multimodal Machine TranslationCode0
Sheffield Submissions for WMT18 Multimodal Translation Shared Task—0
The AFRL-Ohio State WMT18 Multimodal System: Combining Visual with Traditional—0
Adversarial Evaluation of Multimodal Machine Translation—0
Ensemble Sequence Level Training for Multimodal MT: OSU-Baidu WMT18 Multimodal Machine Translation System Report—0
The MeMAD Submission to the WMT18 Multimodal Translation Task—0
A Visual Attention Grounding Neural Model for Multimodal Machine TranslationCode0
Doubly Attentive Transformer Machine Translation—0
Multimodal Machine Translation with Reinforcement Learning—0
Multimodal Lexical TranslationCode0
A Dataset and Reranking Method for Multimodal MT of User-Generated Image Captions—0
MultiNews: A Web collection of an Aligned Multimodal and Multilingual Corpus—0
Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image Description—0
OSU Multimodal Machine Translation System Report—0
NICT-NAIST System for WMT17 Multimodal Translation Task—0
Generating Image Descriptions using Multilingual Data—0
Sheffield MultiMT: Using Object Posterior Predictions for Multimodal Machine Translation—0
Findings of the 2017 Conference on Machine Translation (WMT17)—0
The AFRL-OSU WMT17 Multimodal Translation System: An Image Processing Approach—0
Attention Is All You NeedCode3
NMTPY: A Flexible Toolkit for Advanced Neural Machine Translation SystemsCode0
Doubly-Attentive Decoder for Multi-modal Neural Machine Translation—0
Incorporating Global Visual Features into Attention-Based Neural Machine Translation—0
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All datasetsMulti30KHindi Visual Genome (Challenge Set)Hindi Visual Genome (Test Set)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1delMeteor (EN-FR)74.6—Unverified
2ERNIE-UniX2BLEU (EN-DE)49.3—Unverified
3IKD-MMTBLEU (EN-DE)41.28—Unverified
4DCCNBLEU (EN-DE)39.7—Unverified
5CaglayanBLEU (EN-DE)39.4—Unverified
6Gumbel-Attention MMTBLEU (EN-DE)39.2—Unverified
7Multimodal TransformerBLEU (EN-DE)38.7—Unverified
8ImagiTBLEU (EN-DE)38.4—Unverified
9del+objBLEU (EN-DE)38—Unverified
10VMMTFBLEU (EN-DE)37.6—Unverified
#ModelMetricClaimedVerifiedStatus
1ViTABLEU (EN-HI)51.6—Unverified
#ModelMetricClaimedVerifiedStatus
1ViTABLEU (EN-HI)44.6—Unverified