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Found 5 papers, 3 papers with code
e-CLIP: Large-Scale Vision-Language Representation Learning in E-commerce
Understanding vision and language representations of product content is vital for search and recommendation applications in e-commerce.
Learning a Word-Level Language Model with Sentence-Level Noise Contrastive Estimation for Contextual Sentence Probability Estimation
While word-level language models (LMs) have been widely adopted for computing the joint probabilities of word sequences, they have difficulty in capturing a context long enough for sentence probability estimation (SPE).
A Body Part Embedding Model With Datasets for Measuring 2D Human Motion Similarity
Furthermore, in order to compute the motion similarity from these datasets, we propose a deep learning model that produces motion embeddings suitable for measuring the similarity between different motions of each human body part.
Image-to-Image Retrieval by Learning Similarity between Scene Graphs
Based on this idea, we propose a novel approach for image-to-image retrieval using scene graph similarity measured by graph neural networks.
A Bi-directional Transformer for Musical Chord Recognition
It turns out that the model was able to divide segments of chords by utilizing adaptive receptive field of the attention mechanism.
