35 citations · 90 across the 12 of their papers we have counts for
31 papers
ReferGPT: Towards Zero-Shot Referring Multi-Object Tracking
Tzoulio Chamiti, Leandro Di Bella, Adrian Munteanu +1
Tracking multiple objects based on textual queries is a challenging task that requires linking language understanding with object association across frames. Previous works typicall…
Traffic Event Detection as a Slot Filling Problem
Xiangyu Yang, Giannis Bekoulis, Nikos Deligiannis
In this paper, we introduce the new problem of extracting fine-grained traffic information from Twitter streams by also making publicly available the two (constructed) traffic-rela…
Learned Gradient Compression for Distributed Deep Learning
Lusine Abrahamyan, Yiming Chen, Giannis Bekoulis +1
Training deep neural networks on large datasets containing high-dimensional data requires a large amount of computation. A solution to this problem is data-parallel distributed tra…
Temporal Collaborative Filtering with Graph Convolutional Neural Networks
Esther Rodrigo Bonet, Duc Minh Nguyen, Nikos Deligiannis
Temporal collaborative filtering (TCF) methods aim at modelling non-static aspects behind recommender systems, such as the dynamics in users' preferences and social trends around i…
A Deep-Unfolded Reference-Based RPCA Network For Video Foreground-Background Separation
Huynh Van Luong, Boris Joukovsky, Yonina C. Eldar +1
Deep unfolded neural networks are designed by unrolling the iterations of optimization algorithms. They can be shown to achieve faster convergence and higher accuracy than their op…
A Review on Fact Extraction and Verification
Giannis Bekoulis, Christina Papagiannopoulou, Nikos Deligiannis
We study the fact checking problem, which aims to identify the veracity of a given claim. Specifically, we focus on the task of Fact Extraction and VERification (FEVER) and its acc…