trajdata: 複数の人間軌道データセットへの統合インターフェース
trajdata: A Unified Interface to Multiple Human Trajectory Datasets
自動運転車や歩行者の軌道予測研究で使われる複数のデータセットを、共通のAPIとデータ形式で扱えるようにする統合ライブラリを提案し、既存データセットの比較評価も行った。
著者: Boris Ivanovic, Guanyu Song, Igor Gilitschenski, Marco Pavone
分類: cs.CV, cs.LG, cs.RO
原文アブストラクト
The field of trajectory forecasting has grown significantly in recent years, partially owing to the release of numerous large-scale, real-world human trajectory datasets for autonomous vehicles (AVs) and pedestrian motion tracking. While such datasets have been a boon for the community, they each use custom and unique data formats and APIs, making it cumbersome for researchers to train and evaluate methods across multiple datasets. To remedy this, we present trajdata: a unified interface to multiple human trajectory datasets. At its core, trajdata provides a simple, uniform, and efficient representation and API for trajectory and map data. As a demonstration of its capabilities, in this work we conduct a comprehensive empirical evaluation of existing trajectory datasets, providing users with a rich understanding of the data underpinning much of current pedestrian and AV motion forecasting research, and proposing suggestions for future datasets from these insights. trajdata is permissively licensed (Apache 2.0) and can be accessed online at https://github.com/NVlabs/trajdata
