activity
20162022
most citedBinary Generative Adversarial Networks for Image Retrieval

84 citations · 197 across the 10 of their papers we have counts for

collaborators

14 papers

cs.MM20221 cited

Evaluating the Impact of Tiled User-Adaptive Real-Time Point Cloud Streaming on VR Remote Communication

Shishir Subramanyam, Irene Viola, Jack Jansen +3

Remote communication has rapidly become a part of everyday life in both professional and personal contexts. However, popular video conferencing applications present limitations in…

cs.IR20216 cited

New Insights into Metric Optimization for Ranking-based Recommendation

Roger Zhe Li, Julián Urbano, Alan Hanjalic

Direct optimization of IR metrics has often been adopted as an approach to devise and develop ranking-based recommender systems. Most methods following this approach aim at optimiz…

cs.IR202127 cited

Leave No User Behind: Towards Improving the Utility of Recommender Systems for Non-mainstream Users

Roger Zhe Li, Julián Urbano, Alan Hanjalic

In a collaborative-filtering recommendation scenario, biases in the data will likely propagate in the learned recommendations. In this paper we focus on the so-called mainstream bi…

cs.IR20207 cited

Partially Synthetic Data for Recommender Systems: Prediction Performance and Preference Hiding

Manel Slokom, Martha Larson, Alan Hanjalic

This paper demonstrates the potential of statistical disclosure control for protecting the data used to train recommender systems. Specifically, we use a synthetic data generation…

cs.LG20201 cited

S2IGAN: Speech-to-Image Generation via Adversarial Learning

Xinsheng Wang, Tingting Qiao, Jihua Zhu +2

An estimated half of the world's languages do not have a written form, making it impossible for these languages to benefit from any existing text-based technologies. In this paper,…

cs.CV2019

Matching Images and Text with Multi-modal Tensor Fusion and Re-ranking

Tan Wang, Xing Xu, Yang Yang +3

A major challenge in matching images and text is that they have intrinsically different data distributions and feature representations. Most existing approaches are based either on…