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MMFeat: A Toolkit for Extracting Multi-Modal Features
Douwe Kiela
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Paper Details:
Month: August
Year: 2016
Location: Berlin, Germany
Venue:
ACL |
Citations
URL
Comparing Data Sources and Architectures for Deep Visual Representation Learning in Semantics
Douwe Kiela
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Anita Lilla Verő
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Stephen Clark
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Speaking, Seeing, Understanding: Correlating semantic models with conceptual representation in the brain
Luana Bulat
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Stephen Clark
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Ekaterina Shutova
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Visual Denotations for Recognizing Textual Entailment
Dan Han
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Pascual Martínez-Gómez
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Koji Mineshima
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Bridging Languages through Images with Deep Partial Canonical Correlation Analysis
Guy Rotman
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Ivan Vulić
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Roi Reichart
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Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search
Jamie Kiros
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William Chan
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Geoffrey Hinton
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Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image Description
Desmond Elliott
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Stella Frank
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Loïc Barrault
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Fethi Bougares
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Lucia Specia
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If Sentences Could See: Investigating Visual Information for Semantic Textual Similarity
Goran Glavaš
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Ivan Vulić
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Simone Paolo Ponzetto
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https://github.com/evanmiltenburg/soundmodels-iwcs
https://images.google.com
https://www.bing.com/images
https://www.freesound.org
http://www.vlfeat.org
https://github.com/bmcfee/librosa
http://caffe.berkeleyvision.org
Field Of Study
Linguistic Trends
Distributional Semantics
Embeddings
Task
Semantic Similarity
Approach
Deep Learning
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