mlsanityData to 7 Oct 2026

Toward Unified Practices in Trajectory Prediction Research on Bird's-Eye-View Datasets

arXiv 2405.00604 ↗First posted 1 May 2024cs.RO cs.CVcited by 2

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Abstract (arXiv)

The availability of high-quality datasets is crucial for the development of behavior prediction algorithms in autonomous vehicles. This paper highlights the need to standardize the use of certain datasets for motion forecasting research to simplify comparative analysis and proposes a set of tools and practices to achieve this. Drawing on extensive experience and a comprehensive review of current literature, we summarize our proposals for preprocessing, visualization, and evaluation in the form of an open-sourced toolbox designed for researchers working on trajectory prediction problems. The clear specification of necessary preprocessing steps and evaluation metrics is intended to alleviate development efforts and facilitate the comparison of results across different studies. The toolbox is available at: https://github.com/westny/dronalize.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 36 of its 60 references that are in the map. First posted on arXiv 1 May 2024.

Builds on

36 of 60 references.

References · 36

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24 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026HetroD: A High-Fidelity Drone Dataset and Benchmark for Autonomous Driving in Heterogeneous Trafficcited by 1
  2. 2026Unveiling Transferability in Trajectory Prediction via Latent Scene Embeddingscited by 0