Real-Time 3D Semantic Segmentation
3 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Real-Time 3D Semantic Segmentation
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SemanticKITTI
Most implemented papers
Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platform
sj-li/minet
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Real-time semantic segmentation of LiDAR data is crucial for autonomously driving vehicles, which are usually equipped with an embedded platform and have limited computational resources.
3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic Segmentation
Fast and efficient semantic segmentation methods are needed to match the strong computational and temporal restrictions of many of these real-world applications.
COLA: COarse LAbel pre-training for 3D semantic segmentation of sparse LiDAR datasets
Transfer learning is a proven technique in 2D computer vision to leverage the large amount of data available and achieve high performance with datasets limited in size due to the cost of acquisition or annotation.
