60 citations · 82 across the 16 of their papers we have counts for
16 papers
AdaKAN: A dual-branch adaptive Kolmogorov-Arnold network for medical image segmentation
Dalia Alzu'bi, Deep Bhattacharyya, Ali Ayub +1
Medical image segmentation is a fundamental task in computer-aided diagnosis, yet it remains challenging due to the complexity of anatomical structures and the variability across i…
On Improving Robustness of Deepfake Image Detectors
Abu Taib Mohammed Shahjahan, Mohammad Mannan, Abdessamad Ben Hamza +1
The rapid advancement of Generative AI has introduced remarkable opportunities while simultaneously raising critical concerns regarding content authenticity. While recent work has…
Flexible graph convolutional network for 3D human pose estimation
Abu Taib Mohammed Shahjahan, A. Ben Hamza
Although graph convolutional networks exhibit promising performance in 3D human pose estimation, their reliance on one-hop neighbors limits their ability to capture high-order depe…
PEEKABOO: Hiding parts of an image for unsupervised object localization
Hasib Zunair, A. Ben Hamza
Localizing objects in an unsupervised manner poses significant challenges due to the absence of key visual information such as the appearance, type and number of objects, as well a…
RSUD20K: A Dataset for Road Scene Understanding In Autonomous Driving
Hasib Zunair, Shakib Khan, A. Ben Hamza
Road scene understanding is crucial in autonomous driving, enabling machines to perceive the visual environment. However, recent object detectors tailored for learning on datasets…
Adaptive spectral graph wavelets for collaborative filtering
Osama Alshareet, A. Ben Hamza
Collaborative filtering is a popular approach in recommender systems, whose objective is to provide personalized item suggestions to potential users based on their purchase or brow…
Classification of developmental and brain disorders via graph convolutional aggregation
Ibrahim Salim, A. Ben Hamza
While graph convolution based methods have become the de-facto standard for graph representation learning, their applications to disease prediction tasks remain quite limited, part…
Learning to recognize occluded and small objects with partial inputs
Hasib Zunair, A. Ben Hamza
Recognizing multiple objects in an image is challenging due to occlusions, and becomes even more so when the objects are small. While promising, existing multi-label image recognit…
Spatio-temporal MLP-graph network for 3D human pose estimation
Tanvir Hassan, A. Ben Hamza
Graph convolutional networks and their variants have shown significant promise in 3D human pose estimation. Despite their success, most of these methods only consider spatial corre…
Iterative Graph Filtering Network for 3D Human Pose Estimation
Zaedul Islam, A. Ben Hamza
Graph convolutional networks (GCNs) have proven to be an effective approach for 3D human pose estimation. By naturally modeling the skeleton structure of the human body as a graph,…
A Graph Encoder-Decoder Network for Unsupervised Anomaly Detection
Mahsa Mesgaran, A. Ben Hamza
A key component of many graph neural networks (GNNs) is the pooling operation, which seeks to reduce the size of a graph while preserving important structural information. However,…
Regular Splitting Graph Network for 3D Human Pose Estimation
Tanvir Hassan, A. Ben Hamza
In human pose estimation methods based on graph convolutional architectures, the human skeleton is usually modeled as an undirected graph whose nodes are body joints and edges are…
Fill in Fabrics: Body-Aware Self-Supervised Inpainting for Image-Based Virtual Try-On
H. Zunair, Y. Gobeil, S. Mercier +1
Previous virtual try-on methods usually focus on aligning a clothing item with a person, limiting their ability to exploit the complex pose, shape and skin color of the person, as…
Sharp U-Net: Depthwise Convolutional Network for Biomedical Image Segmentation
Hasib Zunair, A. Ben Hamza
The U-Net architecture, built upon the fully convolutional network, has proven to be effective in biomedical image segmentation. However, U-Net applies skip connections to merge se…
Graph Fairing Convolutional Networks for Anomaly Detection
Mahsa Mesgaran, A. Ben Hamza
Graph convolution is a fundamental building block for many deep neural networks on graph-structured data. In this paper, we introduce a simple, yet very effective graph convolution…
Global spectral graph wavelet signature for surface analysis of carpal bones
Majid Masoumi, A. Ben Hamza
In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of human wrist. We apply a metric called global spectral graph wavelet signature for…