From Binary to Semantic: Utilizing Large-Scale Binary Occupancy Data for 3D Semantic Occupancy Prediction

TL;DR

This paper introduces a novel framework that leverages large-scale binary occupancy data to improve 3D semantic occupancy prediction for autonomous driving, reducing reliance on costly annotated LiDAR data.

Contribution

It proposes a binary occupancy-based approach that enhances semantic prediction through pre-training and auto-labeling, demonstrating superior performance over existing methods.

Findings

Outperforms existing methods in semantic occupancy prediction

Effective utilization of large-scale binary data for pre-training

Improves auto-labeling accuracy for semantic segmentation

Abstract

Accurate perception of the surrounding environment is essential for safe autonomous driving. 3D occupancy prediction, which estimates detailed 3D structures of roads, buildings, and other objects, is particularly important for vision-centric autonomous driving systems that do not rely on LiDAR sensors. However, in 3D semantic occupancy prediction -- where each voxel is assigned a semantic label -- annotated LiDAR point clouds are required, making data acquisition costly. In contrast, large-scale binary occupancy data, which only indicate occupied or free space without semantic labels, can be collected at a lower cost. Despite their availability, the potential of leveraging such data remains unexplored. In this study, we investigate the utilization of large-scale binary occupancy data from two perspectives: (1) pre-training and (2) learning-based auto-labeling. We propose a novel binary occupancy-based framework that decomposes the prediction process into binary and semantic occupancy modules, enabling effective use of binary occupancy data. Our experimental results demonstrate that the proposed framework outperforms existing methods in both pre-training and auto-labeling tasks, highlighting its effectiveness in enhancing 3D semantic occupancy prediction. The code will be available at https://github.com/ToyotaInfoTech/b2s-occupancy