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20152023
most citedUnsupervised Label Noise Modeling and Loss Correction

198 citations · 422 across the 35 of their papers we have counts for

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Showing 2017 · cs.CVShow all

7 papers · 2 filters

cs.CV2017

Saliency Weighted Convolutional Features for Instance Search

Eva Mohedano, Kevin McGuinness, Xavier Giro-i-Nieto +1

This work explores attention models to weight the contribution of local convolutional representations for the instance search task. We present a retrieval framework based on bags o…

cs.CV2017★ 1 cited

People, Penguins and Petri Dishes: Adapting Object Counting Models To New Visual Domains And Object Types Without Forgetting

Mark Marsden, Kevin McGuinness, Suzanne Little +2

In this paper we propose a technique to adapt a convolutional neural network (CNN) based object counter to additional visual domains and object types while still preserving the ori…

cs.CV2017★ 111 cited

SaltiNet: Scan-path Prediction on 360 Degree Images using Saliency Volumes

Marc Assens, Kevin McGuinness, Xavier Giro-i-Nieto +1

We introduce SaltiNet, a deep neural network for scanpath prediction trained on 360-degree images. The model is based on a temporal-aware novel representation of saliency informati…

cs.CV2017★ 1 cited

ResnetCrowd: A Residual Deep Learning Architecture for Crowd Counting, Violent Behaviour Detection and Crowd Density Level Classification

Mark Marsden, Kevin McGuinness, Suzanne Little +1

In this paper we propose ResnetCrowd, a deep residual architecture for simultaneous crowd counting, violent behaviour detection and crowd density level classification. To train and…

cs.CV2017★ 1 cited

Automatic Detection of Knee Joints and Quantification of Knee Osteoarthritis Severity using Convolutional Neural Networks

Joseph Antony, Kevin McGuinness, Kieran Moran +1

This paper introduces a new approach to automatically quantify the severity of knee OA using X-ray images. Automatically quantifying knee OA severity involves two steps: first, aut…

cs.CV2017

Fully Convolutional Crowd Counting On Highly Congested Scenes

Mark Marsden, Kevin McGuinness, Suzanne Little +1

In this paper we advance the state-of-the-art for crowd counting in high density scenes by further exploring the idea of a fully convolutional crowd counting model introduced by (Z…