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Found 12 papers, 5 papers with code
Are These Birds Similar: Learning Branched Networks for Fine-grained Representations
In recent years, natural language descriptions are used to obtain information on discriminative parts of the object.
Ranked #1 on
Multi-Modal Document Classification
on CUB-200-2011
Deep Latent Space Learning for Cross-modal Mapping of Audio and Visual Signals
We quantitatively and qualitatively evaluate the proposed approach on VoxCeleb, a benchmarks audio-visual dataset on a multitude of tasks including cross-modal verification, cross-modal matching, and cross-modal retrieval.
A Classification Methodology based on Subspace Graphs Learning
The objective is to select the best structures created during the training phase using an ensemble of spanning trees.
Picture What you Read
Visualization refers to our ability to create an image in our head based on the text we read or the words we hear.
Do Cross Modal Systems Leverage Semantic Relationships?
Our proposed measure evaluates the semantic similarity between the image and text representations in the latent embedding space.
Binary Classification using Pairs of Minimum Spanning Trees or N-ary Trees
One-class classifiers are trained with target class only samples.
Aiding Intra-Text Representations with Visual Context for Multimodal Named Entity Recognition
With massive explosion of social media such as Twitter and Instagram, people daily share billions of multimedia posts, containing images and text.
Learning Inward Scaled Hypersphere Embedding: Exploring Projections in Higher Dimensions
Majority of the current dimensionality reduction or retrieval techniques rely on embedding the learned feature representations onto a computable metric space.
Image and Encoded Text Fusion for Multi-Modal Classification
To learn feature representations of resulting images, standard Convolutional Neural Networks (CNNs) are employed for the classification task.
Seeing Colors: Learning Semantic Text Encoding for Classification
The question we answer with this work is: can we convert a text document into an image to exploit best image classification models to classify documents?
Git Loss for Deep Face Recognition
Conventionally, CNNs have been trained with softmax as supervision signal to penalize the classification loss.
Ranked #8 on
Face Verification
on YouTube Faces DB
Revisiting Cross Modal Retrieval
We show that text encodings can capture semantic relationships between multiple modalities.
