7 citations · 9 across the 7 of their papers we have counts for
7 papers · 1 filter
MLGCN: An Ultra Efficient Graph Convolution Neural Model For 3D Point Cloud Analysis
Mohammad Khodadad, Morteza Rezanejad, Ali Shiraee Kasmaee +3
The analysis of 3D point clouds has diverse applications in robotics, vision and graphics. Processing them presents specific challenges since they are naturally sparse, can vary in…
Contour Completion using Deep Structural Priors
Ali Shiraee, Morteza Rezanejad, Mohammad Khodadad +2
Humans can easily perceive illusory contours and complete missing forms in fragmented shapes. This work investigates whether such capability can arise in convolutional neural netwo…
RxRx1: A Dataset for Evaluating Experimental Batch Correction Methods
Maciej Sypetkowski, Morteza Rezanejad, Saber Saberian +9
High-throughput screening techniques are commonly used to obtain large quantities of data in many fields of biology. It is well known that artifacts arising from variability in the…
Medial Spectral Coordinates for 3D Shape Analysis
Morteza Rezanejad, Mohammad Khodadad, Hamidreza Mahyar +4
In recent years there has been a resurgence of interest in our community in the shape analysis of 3D objects represented by surface meshes, their voxelized interiors, or surface po…
Contour-guided Image Completion with Perceptual Grouping
Morteza Rezanejad, Sidharth Gupta, Chandra Gummaluru +4
Humans are excellent at perceiving illusory outlines. We are readily able to complete contours, shapes, scenes, and even unseen objects when provided with images that contain broke…
Appearance Shock Grammar for Fast Medial Axis Extraction from Real Images
Charles-Olivier Dufresne Camaro, Morteza Rezanejad, Stavros Tsogkas +2
We combine ideas from shock graph theory with more recent appearance-based methods for medial axis extraction from complex natural scenes, improving upon the present best unsupervi…
Scene Categorization from Contours: Medial Axis Based Salience Measures
Morteza Rezanejad, Gabriel Downs, John Wilder +4
The computer vision community has witnessed recent advances in scene categorization from images, with the state-of-the art systems now achieving impressive recognition rates on cha…