28 citations · 44 across the 4 of their papers we have counts for
4 papers
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…
S3Net: 3D LiDAR Sparse Semantic Segmentation Network
Ran Cheng, Ryan Razani, Yuan Ren +1
Semantic Segmentation is a crucial component in the perception systems of many applications, such as robotics and autonomous driving that rely on accurate environmental perception…
(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…