Argoverse is a tracking benchmark with over 30K scenarios collected in Pittsburgh and Miami. Each scenario is a sequence of frames sampled at 10 HZ. Each sequence has an interesting object called “agent”, and the task is to predict the future locations of agents in a 3 seconds future horizon. The sequences are split into training, validation and test sets, which have 205,942, 39,472 and 78,143 sequences respectively. These splits have no geographical overlap.
Source: Learning Lane Graph Representations for Motion Forecasting
Image Source: https://arxiv.org/pdf/1911.02620.pdf
Variants: Argoverse, Argoverse CVPR 2020
This dataset is used in 2 benchmarks:
| Task | Model | Paper | Date |
|---|---|---|---|
| Trajectory Prediction | HeteroGCN | Dynamic Scenario Representation Learning for … | 2023-03-08 |
Recent papers with results on this dataset: