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One Million Scenes for Autonomous Driving: ONCE Dataset
Jiageng Mao · Niu Minzhe · ChenHan Jiang · hanxue liang · Jingheng Chen · Xiaodan Liang · Yamin Li · Chaoqiang Ye · Wei Zhang · Zhenguo Li · Jie Yu · Hang Xu · Chunjing XU

Current perception models in autonomous driving have become notorious for greatly relying on a mass of annotated data to cover unseen cases and address the long-tail problem. On the other hand, learning from unlabeled large-scale collected data and incrementally self-training powerful recognition models have received increasing attention and may become the solutions of next-generation industry-level powerful and robust perception models in autonomous driving. However, the research community generally suffered from data inadequacy of those essential real-world scene data, which hampers the future exploration of fully/semi/self-supervised methods for 3D perception. In this paper, we introduce the ONCE (One millioN sCenEs) dataset for 3D object detection in the autonomous driving scenario. The ONCE dataset consists of 1 million LiDAR scenes and 7 million corresponding camera images. The data is selected from 144 driving hours, which is 20x longer than the largest 3D autonomous driving dataset available (\eg nuScenes and Waymo), and it is collected across a range of different areas, periods and weather conditions. To facilitate future research on exploiting unlabeled data for 3D detection, we additionally provide a benchmark in which we reproduce and evaluate a variety of self-supervised and semi-supervised methods on the ONCE dataset. We conduct extensive analyses on those methods and provide valuable observations on their performance related to the scale of used data. Data, code, and more information are available at \href{https://once-for-auto-driving.github.io/index.html}{http://www.once-for-auto-driving.com}.

Author Information

Jiageng Mao (The Chinese University of Hong Kong)
Niu Minzhe (Huawei)
ChenHan Jiang (Sun Yat-sen University)
hanxue liang (Swiss Federal Institute of Technology)
Jingheng Chen (Beihang University, Tsinghua University)
Xiaodan Liang (Sun Yat-sen University)
Yamin Li (Southern Methodist University)
Chaoqiang Ye (Huawei Technologies Ltd.)
Wei Zhang (Noah's Ark Lab, Huawei Inc.)
Zhenguo Li (Noah's Ark Lab, Huawei Tech Investment Co Ltd)
Jie Yu (University of Texas, San Antonio)
Hang Xu (Huawei Noah's Ark Lab)
Chunjing XU (Huawei Technologies)

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