most cited(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Network

28 citations · 46 across the 6 of their papers we have counts for

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cs.CV20211 cited

SMAC-Seg: LiDAR Panoptic Segmentation via Sparse Multi-directional Attention Clustering

Enxu Li, Ryan Razani, Yixuan Xu +1

Panoptic segmentation aims to address semantic and instance segmentation simultaneously in a unified framework. However, an efficient solution of panoptic segmentation in applicati…

cs.CV20211 cited

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…

cs.CV2021

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…

cs.CV20211 cited

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…

cs.CV202128 cited

(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…

cs.CV202015 cited

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…