4 citations · 5 across the 5 of their papers we have counts for
7 papers · 1 filter
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…
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…