no code implementations • 3 Nov 2022 • Matthew Kowal, Mennatullah Siam, Md Amirul Islam, Neil D. B. Bruce, Richard P. Wildes, Konstantinos G. Derpanis
(ii) Some datasets that are assumed to be biased toward dynamics are actually biased toward static information.
1 code implementation • CVPR 2022 • Matthew Kowal, Mennatullah Siam, Md Amirul Islam, Neil D. B. Bruce, Richard P. Wildes, Konstantinos G. Derpanis
To show the efficacy of our approach, we analyse two widely studied tasks, action recognition and video object segmentation.
no code implementations • 20 Oct 2021 • Md Amirul Islam, Matthew Kowal, Sen Jia, Konstantinos G. Derpanis, Neil D. B. Bruce
Extensive experiments demonstrate the high quality of our generated pseudo-labels and effectiveness of the proposed framework in a variety of domains.
no code implementations • 23 Aug 2021 • Md Amirul Islam, Matthew Kowal, Konstantinos G. Derpanis, Neil D. B. Bruce
The premise is based on the notion of feature binding, which is defined as the process by which activations spread across space and layers in the network are successfully integrated to arrive at a correct inference decision.
1 code implementation • ICCV 2021 • Md Amirul Islam, Matthew Kowal, Sen Jia, Konstantinos G. Derpanis, Neil D. B. Bruce
In this paper, we challenge the common assumption that collapsing the spatial dimensions of a 3D (spatial-channel) tensor in a convolutional neural network (CNN) into a vector via global pooling removes all spatial information.
no code implementations • 28 Jan 2021 • Md Amirul Islam, Matthew Kowal, Sen Jia, Konstantinos G. Derpanis, Neil D. B. Bruce
; (ii) Does position encoding affect the learning of semantic representations?
no code implementations • 13 Aug 2020 • Md Amirul Islam, Matthew Kowal, Konstantinos G. Derpanis, Neil D. B. Bruce
In this paper, we present a strategy for training convolutional neural networks to effectively resolve interference arising from competing hypotheses relating to inter-categorical information throughout the network.
1 code implementation • CVPR 2020 • Sen Jia, Neil D. B. Bruce
Our experiment shows FN-AUC can measure spatial biases, central and peripheral, more effectively than S-AUC without penalizing the fixation locations.
2 code implementations • ICLR 2020 • Md Amirul Islam, Sen Jia, Neil D. B. Bruce
In contrast to fully connected networks, Convolutional Neural Networks (CNNs) achieve efficiency by learning weights associated with local filters with a finite spatial extent.
no code implementations • 28 Sep 2019 • Rezaul Karim, Md Amirul Islam, Neil D. B. Bruce
In this paper, we present a canonical structure for controlling information flow in neural networks with an efficient feedback routing mechanism based on a strategy of Distributed Iterative Gating (DIGNet).
no code implementations • 8 Jan 2019 • Sen Jia, Neil D. B. Bruce
Recent Salient Object Detection (SOD) systems are mostly based on Convolutional Neural Networks (CNNs).
1 code implementation • 20 Dec 2018 • Calden Wloka, Toni Kunić, Iuliia Kotseruba, Ramin Fahimi, Nicholas Frosst, Neil D. B. Bruce, John K. Tsotsos
The Saliency Model Implementation Library for Experimental Research (SMILER) is a new software package which provides an open, standardized, and extensible framework for maintaining and executing computational saliency models.
no code implementations • 20 Nov 2018 • Rezaul Karim, Md Amirul Islam, Neil D. B. Bruce
The iterative nature of this mechanism allows for gating to spread in both spatial extent and feature space.
no code implementations • 3 Oct 2018 • Mahmoud Kalash, Md Amirul Islam, Neil D. B. Bruce
Further to this, we present data, analysis and baseline benchmark results towards addressing the problem of salient object ranking.
no code implementations • 25 Jul 2018 • Md Amirul Islam, Mahmoud Kalash, Neil D. B. Bruce
With that said, there is an apparent relationship between these two problem domains in that the composition of a scene and associated semantic categories is certain to play into what is deemed salient.
no code implementations • 29 Jun 2018 • Md Amirul Islam, Mrigank Rochan, Shujon Naha, Neil D. B. Bruce, Yang Wang
In order to address this issue, we also propose Gated Feedback Refinement Network (G-FRNet) that addresses this limitation.
no code implementations • 2 May 2018 • Sen Jia, Neil D. B. Bruce
Furthermore, the encoder can contain more than one CNN model to extract features, and models can have different architectures or be pre-trained on different datasets.
no code implementations • CVPR 2018 • Md Amirul Islam, Mahmoud Kalash, Neil D. B. Bruce
In this paper, we argue that work to date has addressed a problem that is relatively ill-posed.
no code implementations • CVPR 2017 • Md Amirul Islam, Mrigank Rochan, Neil D. B. Bruce, Yang Wang
Effective integration of local and global contextual information is crucial for dense labeling problems.
no code implementations • CVPR 2016 • Neil D. B. Bruce, Christopher Catton, Sasa Janjic
In this paper we consider the problem of visual saliency modeling, including both human gaze prediction and salient object segmentation.