334 citations · 1.3k across the 54 of their papers we have counts for
11 papers · 1 filter
Investigating Memorability of Dynamic Media
Phuc H. Le-Khac, Ayush K. Rai, Graham Healy +2
The Predicting Media Memorability task in MediaEval'20 has some challenging aspects compared to previous years. In this paper we identify the high-dynamic content in videos and dat…
Temporal Bilinear Encoding Network of Audio-Visual Features at Low Sampling Rates
Feiyan Hu, Eva Mohedano, Noel O'Connor +1
Current deep learning based video classification architectures are typically trained end-to-end on large volumes of data and require extensive computational resources. This paper a…
Multi-Objective Interpolation Training for Robustness to Label Noise
Diego Ortego, Eric Arazo, Paul Albert +2
Deep neural networks trained with standard cross-entropy loss memorize noisy labels, which degrades their performance. Most research to mitigate this memorization proposes new robu…
ATSal: An Attention Based Architecture for Saliency Prediction in 360 Videos
Yasser Dahou, Marouane Tliba, Kevin McGuinness +1
The spherical domain representation of 360 video/image presents many challenges related to the storage, processing, transmission and rendering of omnidirectional videos (ODV). Mode…
Unsupervised Contrastive Learning of Sound Event Representations
Eduardo Fonseca, Diego Ortego, Kevin McGuinness +2
Self-supervised representation learning can mitigate the limitations in recognition tasks with few manually labeled data but abundant unlabeled data---a common scenario in sound ev…
How important are faces for person re-identification?
Julia Dietlmeier, Joseph Antony, Kevin McGuinness +1
This paper investigates the dependence of existing state-of-the-art person re-identification models on the presence and visibility of human faces. We apply a face detection and blu…
Utilising Visual Attention Cues for Vehicle Detection and Tracking
Feiyan Hu, Venkatesh G M, Noel E. O'Connor +2
Advanced Driver-Assistance Systems (ADAS) have been attracting attention from many researchers. Vision-based sensors are the closest way to emulate human driver visual behavior whi…
Reliable Label Bootstrapping for Semi-Supervised Learning
Paul Albert, Diego Ortego, Eric Arazo +2
Reducing the amount of labels required to train convolutional neural networks without performance degradation is key to effectively reduce human annotation efforts. We propose Reli…
Chroma Intra Prediction with attention-based CNN architectures
Marc Górriz, Saverio Blasi, Alan F. Smeaton +2
Neural networks can be used in video coding to improve chroma intra-prediction. In particular, usage of fully-connected networks has enabled better cross-component prediction with…
Interpreting CNN for Low Complexity Learned Sub-pixel Motion Compensation in Video Coding
Luka Murn, Saverio Blasi, Alan F. Smeaton +2
Deep learning has shown great potential in image and video compression tasks. However, it brings bit savings at the cost of significant increases in coding complexity, which limits…
Investigating Class-level Difficulty Factors in Multi-label Classification Problems
Mark Marsden, Kevin McGuinness, Joseph Antony +6
This work investigates the use of class-level difficulty factors in multi-label classification problems for the first time. Four class-level difficulty factors are proposed: freque…