16 citations · 18 across the 3 of their papers we have counts for
4 papers · 1 filter
FSMDet: Vision-guided feature diffusion for fully sparse 3D detector
Tianran Liu, Morteza Mousa Pasandi, Robert Laganiere
Fully sparse 3D detection has attracted an increasing interest in the recent years. However, the sparsity of the features in these frameworks challenges the generation of proposals…
What You See Is What You Detect: Towards better Object Densification in 3D detection
Tianran Liu, Zeping Zhang, Morteza Mousa Pasandi +1
Recent works have demonstrated the importance of object completion in 3D Perception from Lidar signal. Several methods have been proposed in which modules were used to densify the…
Convolutional Neural Network Pruning Using Filter Attenuation
Morteza Mousa-Pasandi, Mohsen Hajabdollahi, Nader Karimi +2
Filters are the essential elements in convolutional neural networks (CNNs). Filters are corresponded to the feature maps and form the main part of the computational and memory requ…
Modeling of Pruning Techniques for Deep Neural Networks Simplification
Morteza Mousa Pasandi, Mohsen Hajabdollahi, Nader Karimi +1
Convolutional Neural Networks (CNNs) suffer from different issues, such as computational complexity and the number of parameters. In recent years pruning techniques are employed to…