8 citations · 12 across the 2 of their papers we have counts for
5 papers
T-VSE: Transformer-Based Visual Semantic Embedding
Muhammet Bastan, Arnau Ramisa, Mehmet Tek
Transformer models have recently achieved impressive performance on NLP tasks, owing to new algorithms for self-supervised pre-training on very large text corpora. In contrast, rec…
Orderless Recurrent Models for Multi-label Classification
Vacit Oguz Yazici, Abel Gonzalez-Garcia, Arnau Ramisa +2
Recurrent neural networks (RNN) are popular for many computer vision tasks, including multi-label classification. Since RNNs produce sequential outputs, labels need to be ordered f…
Learning Metrics from Teachers: Compact Networks for Image Embedding
Lu Yu, Vacit Oguz Yazici, Xialei Liu +3
Metric learning networks are used to compute image embeddings, which are widely used in many applications such as image retrieval and face recognition. In this paper, we propose to…
Visually-Aware Personalized Recommendation using Interpretable Image Representations
Charles Packer, Julian McAuley, Arnau Ramisa
Visually-aware recommender systems use visual signals present in the underlying data to model the visual characteristics of items and users' preferences towards them. In the domain…
BreakingNews: Article Annotation by Image and Text Processing
Arnau Ramisa, Fei Yan, Francesc Moreno-Noguer +1
Building upon recent Deep Neural Network architectures, current approaches lying in the intersection of computer vision and natural language processing have achieved unprecedented…