DeepAI AI Chat
Log In Sign Up

CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation

07/20/2022
by   Cristiano Saltori, et al.
Università di Trento
0

3D LiDAR semantic segmentation is fundamental for autonomous driving. Several Unsupervised Domain Adaptation (UDA) methods for point cloud data have been recently proposed to improve model generalization for different sensors and environments. Researchers working on UDA problems in the image domain have shown that sample mixing can mitigate domain shift. We propose a new approach of sample mixing for point cloud UDA, namely Compositional Semantic Mix (CoSMix), the first UDA approach for point cloud segmentation based on sample mixing. CoSMix consists of a two-branch symmetric network that can process labelled synthetic data (source) and real-world unlabelled point clouds (target) concurrently. Each branch operates on one domain by mixing selected pieces of data from the other one, and by using the semantic information derived from source labels and target pseudo-labels. We evaluate CoSMix on two large-scale datasets, showing that it outperforms state-of-the-art methods by a large margin. Our code is available at https://github.com/saltoricristiano/cosmix-uda.

READ FULL TEXT
08/28/2023

Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation

Deep-learning models for 3D point cloud semantic segmentation exhibit li...
07/20/2022

GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation

3D point cloud semantic segmentation is fundamental for autonomous drivi...
07/16/2020

Complete Label: A Domain Adaptation Approach to Semantic Segmentation of LiDAR Point Clouds

We study an unsupervised domain adaptation problem for the semantic labe...
04/04/2022

DODA: Data-oriented Sim-to-Real Domain Adaptation for 3D Indoor Semantic Segmentation

Deep learning approaches achieve prominent success in 3D semantic segmen...
08/28/2023

Attention-Guided Lidar Segmentation and Odometry Using Image-to-Point Cloud Saliency Transfer

LiDAR odometry estimation and 3D semantic segmentation are crucial for a...
10/12/2022

Hierarchical Instance Mixing across Domains in Aerial Segmentation

We investigate the task of unsupervised domain adaptation in aerial sema...