66 citations · 117 across the 7 of their papers we have counts for
8 papers
GP-S3Net: Graph-based Panoptic Sparse Semantic Segmentation Network
Ryan Razani, Ran Cheng, Enxu Li +3
Panoptic segmentation as an integrated task of both static environmental understanding and dynamic object identification, has recently begun to receive broad research interest. In…
Lite-HDSeg: LiDAR Semantic Segmentation Using Lite Harmonic Dense Convolutions
Ryan Razani, Ran Cheng, Ehsan Taghavi +1
Autonomous driving vehicles and robotic systems rely on accurate perception of their surroundings. Scene understanding is one of the crucial components of perception modules. Among…
(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Network
Ran Cheng, Ryan Razani, Ehsan Taghavi +2
Autonomous robotic systems and self driving cars rely on accurate perception of their surroundings as the safety of the passengers and pedestrians is the top priority. Semantic seg…
TORNADO-Net: mulTiview tOtal vaRiatioN semAntic segmentation with Diamond inceptiOn module
Martin Gerdzhev, Ryan Razani, Ehsan Taghavi +1
Semantic segmentation of point clouds is a key component of scene understanding for robotics and autonomous driving. In this paper, we introduce TORNADO-Net - a neural network for…
Adaptive Hierarchical Down-Sampling for Point Cloud Classification
Ehsan Nezhadarya, Ehsan Taghavi, Ryan Razani +2
While several convolution-like operators have recently been proposed for extracting features out of point clouds, down-sampling an unordered point cloud in a deep neural network ha…
Object Recognition and Identification Using ESM Data
E. Taghavi, D. Song, R. Tharmarasa +3
Recognition and identification of unknown targets is a crucial task in surveillance and security systems. Electronic Support Measures (ESM) are one of the most effective sensors fo…